Relative Strength Overlay [BackQuant]Relative Strength Overlay
Relative Strength Overlay is a new innovative proprietary adaptive calculation to get an assets relative strength. To ensure this is well put together and easy for traders to use we have made it into an overlay. Allowing traders and investors to spot clear trends in both the up and down directions. Providing clear signals, and an option for a gradient to allow users to screen assets with strong relative strength and potentially define a trading period.
Please take the time to read the following.
Importance and Concepts
1. Adaptive Relative Strength Calculation:
At the heart of this indicator lies an adaptive relative strength calculation, a pivotal concept that goes beyond the traditional RSI (Relative Strength Index) by dynamically adjusting its sensitivity based on recent price action. This adaptability ensures that the indicator is more responsive to current market conditions, enhancing its effectiveness in signaling potential reversals or continuations.
2. Volatility and Price Action Adaptivity:
Incorporating an adaptive approach to both volatility and price action, the indicator refines its signals to reflect the current market environment more accurately. This adaptability is achieved through a custom calculation that considers the volatility (using ATR - Average True Range) and price action (through DEMA - Double Exponential Moving Average), ensuring that the indicator remains sensitive to sudden changes in market dynamics.
3. DEMA Utilization:
The use of DEMA provides a price-adaptive mechanism that smoothens the indicator's output, making it more reliable during volatile periods. DEMA helps in reducing the lag associated with traditional moving averages, offering a quicker response to price changes and enhancing the adaptive nature of the relative strength calculation.
Main Features and Trading Applications
Comprehensive UI Settings:
The indicator comes with extensive user interface settings, allowing traders to customize various parameters according to their trading preferences. These settings include adjustment options for calculation periods, standard deviation factors, and the ability to toggle features like volatility bands and signal lines on or off.
Volatility-Adjusted Bands:
Utilizing a custom ATR calculation, the indicator plots volatility bands that adjust according to current market volatility. These bands serve as dynamic support and resistance levels, providing traders with potential entry and exit points based on the confluence of relative strength signals and band breaches.
Calibrated Trading Conditions:
The indicator features pre-modeled long and short conditions that have been backtested to ensure robustness. These conditions help in identifying high-probability trading setups, making the indicator a valuable tool for both discretionary and systematic traders, mainly looking to either define a trading period, or capture clear trends in confluence with other metrics.
Trading Range Identification:
By filtering assets based on their relative strength, traders can use the indicator to identify securities with strong momentum. This feature is particularly useful for portfolio selection and asset screening, allowing traders to focus on the most promising opportunities.
Gradient Background Hue:
The indicator offers a unique visual aid in the form of a gradient background hue, which assists in quickly screening assets based on their relative strength. This color-coding feature aids in identifying potential reversals as it highlights changes in the strength's direction.
Adaptive Volatility Bands with Standard Deviations:
The inclusion of three sets of volatility bands, each corresponding to different standard deviations, provides a probabilistic view of price movements. These bands adapt to current market volatility, offering traders insights into the likelihood of price staying within certain ranges. This goes up to +-3 Standard Deviations.
Alert Conditions and Signal Visualization:
With built-in alert conditions for long and short signals, along with the ability to paint candles according to the prevailing trend, traders can stay informed about significant market movements. This feature enhances the decision-making process by visually representing the strength and direction of the trend.
alertcondition(ta.crossover(BackQuant, 0), title="Positive RS", message="Positive RS {{exchange}}:{{ticker}}")
alertcondition(ta.crossunder(BackQuant, 0), title="Negative RS", message="Negative RS {{exchange}}:{{ticker}}")
Concluding Remarks.
In conclusion our Relative Strength Overlay indicator is a comprehensive tool that leverages adaptive calculations and volatility adjustments to provide traders with nuanced insights into market conditions. By combining traditional concepts with innovative features, this indicator offers a versatile solution for traders seeking to enhance their market analysis and identify high-probability trading opportunities.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Cari skrip untuk "backtest"
TestedFX Pitchfork Intersections v1.4TestedFX Sexy Pitchfork Intersection Strategy Trading Rules:
All trades are 4R !! If you don’t understand this, please DO NOT TRADE until you have researched Risk to Reward ratios. Basically 4R means you win 4x your risk. Ie. SL = 25 pips and TP is 100 pips so you win 4x your risk.
AUTHOR’S NOTE: Statistically Pitchforks reach the median line 80% of the time. Yet they are the most overlooked and underused tool used by traders. Of course you will NOT get an 80% win rate with this strategy because we can never know for sure if price will bounce on a line or bust through.
WARNING: TRADE ON 4 HOUR OR HIGHER TIMEFRAME. Less than expert level traders should trade on 4 hour or higher time frames. Getting in and out of a trade will likely cost you 2 to 3 pips with spread and commission. This strategy produces precision entries which sounds good BUT on smaller time frames this will affect your average R significantly and eat up much of your profits. For example on a 15 min timeframe this strategy will often give you 6 or 7 pip SL. When you add 2 or 3 pips your Risk to Reward ratio will often be 3R instead of 4R. Our long term backtests show an average win of 1.3R when losses are factored in. So on a 15 min time frame you would only be left with 0.3R average win which is ok but not optimal. Inexperienced traders to this strategy will likely make mistakes which will eat up the rest of the profits. So please all new traders keep to the 4H or higher time frames and backtest a lot before you start trading.
1) Trade with the Pitchfork ONLY.
At least one line must be pushing in the direction of the trade. Breakouts tend to occur when multiple lines are facing the same direction.
2) Sexy Line Touch: Enter the trade when the sexy line is touched just outside a fib zone. A sexy line is a line just outside the fib rejection zone or outer line of a pitchfork. Price loves to reach out and touch or almost touch it before reversing which is your key to precision entries.
a) 3+ LINES: Only trade with 3+ confirmation lines.
b) EMPTY SPACE: Trade the outermost line. There should be no more sexy lines to touch nearby.
3) NO MESS
Don't trade when there are so many lines you can't see what is going on. The cost to not trade is exactly $0. So skip areas where trend direction is not clear and pitchforks are going in too many conflicting directions.
4) Set TP just past the next level.
5) Set SL at 4R.
Recommendations:
1) Once you lose on a pitchfork move on to the next pitchfork. In choppy markets I also apply this rule to wins since a long term trend is unlikely.
2) Search for trades using Andrew's Pitchforks in a trend. In consolidation search for trades using Modified-Schiff Pitchforks. Confirm trades by turning on both pitchforks momentarily to find sexy line touches.
3) Backtest, Backtest, Backtest !! This strategy isn’t for traders who want clear easy entries. Often multiple pitchforks give conflicting or overlapping signals. Practice to know when the market is too complex and you need to “Skip the Mess” takes practice. Also knowing how much "Empty Space" is enough takes practice too.
Quickie (Free) IndicatorQuickie is a free tradingview Indicator developed by HFT Research. It works in sideways and trending markets depending the way you set it as well as both on short time frame and long time frame. It comes with backtesting abilities on tradingview.
You can find the alerts to go long and short here, please check the backtester to fine tune your strategy.
Use Bollinger Bands
This piece of the settings will turn and off Bollinger band’s input in the decision making. BB Length will determine the Moving average you are using to take the standard deviation off of which is named as BB Multiplier. Default settings will use 20 moving average and take standard deviation of 2 to create lower and upper bands. Increasing the Multiplier will give you fewer but safer entries
Use RSI
You can also turn on and off the RSI as well. Alternatively, there is an option to use RSI on a different time frame than you are currently on. For example, if you are looking at the 5min chart to use Bollinger bands but you would like to look at the RSI value on the 15min chart. You can do so by selecting the custom RSI timeframe as well as adjusting the Oversold and Overbought value.
Use MA Filter
Lookback: The indicator has an option to look back x number of candles to validate the price crossing. If the market is choppy and the price keeps crossing up and down the moving average you have chosen, it will generate a lot of “noisy” signals. This option allows you to confirm the cross by selecting how many candles the price needs to stay above or below the moving average. Setting it 0 will turn it off.
MA Filter Type: There is a selection of moving averages that is available on TradingView currently. You can choose from 14 different moving average types to detect the trend as accurate as possible.
Filter Length: You can select the length of your moving average. Most commonly used length being 50,100 and 200.
Filter Type: This is our propriety smoothing method in order to make the moving averages lag less and influence the way they are calculated slightly. Type 1 being the normal calculation and type 2 being the secret sauce .
Reverse MA Filter: This option allows you to use the moving average in reverse. For example, the strategy will go long when the price is above the moving average. However, if you use the reserve MA Filter, you will go short when the price is above the moving average. This method works best in sideways market where price usually retraces back to the moving average. So, in an anticipation of price reverting back to the moving average, it is a useful piece of option to use during sideway markets.
For more information please check out our website
Super Trend Daily 2.0 Alerts BFThis is an alerts script for my Super Trend 2.0 indicator . It is intended as a companion script so you can backtest using the Strategy script and generate alerts using this Study script.
This Study script has the same default settings as the Strategy script and its only purpose is to provide alerts for the long and short signals the Strategy generates. Obviously, if you want to generate alerts based on a Strategy backtest, please ensure the settings are the same in the Study as in the Strategy.
For illustration, I have plotted arrows on the chart for long and short signals, and also colored the background to show when the rate of change function determines a choppy/sideways market.
ALERTS
There are 2 alerts set up:
Long Entry
Short Entry
ILLUSTRATION
Green arrow = Long Entry
Red arrow = Short Entry
White background = No short trades
Aqua background = No long trades
EXAMPLE USE CASE
1. Open a Bitcoin/USD chart on 1D timeframe.
2. Open this script and the Super Trend 2.0 indicator script.
3. Backtest with the Strategy Backtester and change the settings if you like until you get a desirable outcome for your own purposes.
4. Once you are happy with the backtest, change the settings in the Alerts script (this one) so they match the Strategy settings.
5. Set up the alerts according to your preferences.
Cyatophilum Bands Pro Trader V5 [ALERTSETUP]Alert Setup version
Get the Free Backtest version here :
This version includes a new feature.
Trailing Take Profit with % deviation.
For those seeing the indicator for the first time, it works like Donchian Channels with lag and a channel width condition to detect breakouts. On top of that I integrated a Stop Loss and Take Profit system to pinescript.
Backtest results below are calculated with :
Short + Long Strategy
0.05% Commission
100% of 10 000% equity per trade
Strategy data from 25/04/2019 to 18/05/2019
Default Configuration for BITFINEX:ETHBTC 3 minutes timeframe.
This version also has the Stop Loss / Take Profit system included in the previous version, plus a short / long setup distinction. For example you can choose a different stop loss % for long and for short trades.
Previous version:
Get access to the Alert Setup version and automate the strategy today !
Purchase the Cyatophilum Indicators pack
I will publish backtests and configurations so make sure to follow me if you don't want to miss anything !
My Website - blockchainfiesta.com -
My Discord channel - discord.gg -
TrendShikari NTS - StudyTrendShikari NTS is a Nifty Index, Swing trading system with great profitability. This is the STUDY file for you to generate E-mail / SMS signal alerts (based on your TV plan) and to see crisp and clear graphical Daily trade level plotting. For seeing backtest results and next day trading levels in advance use the STRATEGY file from indicator library. Access to this system will be limited. See my profile status field to see how you can gain access.
Salient Features
1. Daily Bar System. System analyzes a Daily chart of NIFTY to give signals with average holding period of 5 days.
2. Automatic Long and Short signal generation. No need to draw waves / lines and other fancy stuff on your charts to analyze NIFTY any more.
3. Backtester Results Available - Thanks to TradingView, backtest results for previous years (from 1990) are available right in the charting platform for NIFTY.
Having a good trading system is one thing and trading it to make money is a whole different ball game. One thing you must always do if you want to mimic the backtest results in live trading is to follow the rules mentioned below as if your life depends on it.
Trading Rules
1. Each day the system gives you a Long and Short trading level. You go Long on NIFTY when the Daily Long level is breached and you go Short on NIFTY when the Daily Short Level is breached.
2. Trade using Nifty Options, In the Money calls, one strike below the nearest strike price for going Long using Call Option or one strike above the nearest strike price for going Short using Put Option.
3. Preset exit and entry orders of appropriate option contracts every day at market open. To set the levels see the difference in Nifty spot price and the trading levels given by system and then multiply it with 0.8 to give an approximate order trigger price in both directions for the corresponding option contracts.
4. Book profit when Nifty moves significantly along signal direction. Every time NIFTY moves 100 points in your direction you exit the current option contract and enter a trade in the next strike price in the same direction.
5. Rollover before expiry. Its important that you rollover (ideally one day before the expiry day) your Option contact positions by exiting the current month contract and take a new position in the next month contract of the same type and strike price of the current month contract.
6. Trade only Nifty using this system. Also Daily chart has to be used for trading. System parameters have been tested and optimized for Nifty Index Daily patterns only and hence is likely to give stated results with Nifty Daily chart only.
7. Trade all signals. Don't pick and choose or add your own or someone else's analysis to filter the signals. Take confidence from the objective backtest results and not any subjective interpretations.
8. Trade with only that amount of money you can afford to loose. Initial capital that you need to have to trade one lot of NIFTY Option using this system should be at least INR 150000. You need only INR 7500 - 15000 to open a position and the rest is the margin of safety you need to have in your trading account to account for drawdowns in trading. You can add the capital in a staggered need to basis to your trading account. But make sure you have the initial capital mentioned above at your disposal, if need be.
As always your thoughts and inputs are welcome. Happy Trading !!!
Kinetic Scalper [BULLBYTE]KINETIC SCALPER - ADVANCED MOMENTUM & CONFLUENCE TRADING SYSTEM
A SOPHISTICATED MULTI-FACTOR ANALYSIS INDICATOR FOR PRECISION ENTRIES
The Kinetic Scalper is a comprehensive trading analysis tool that combines volume-weighted momentum calculations, multi-oscillator divergence detection, and a proprietary 15-factor confluence scoring system to identify high-probability reversal setups across all timeframes.
WHAT MAKES THIS INDICATOR ORIGINAL
This is NOT a simple mashup of existing indicators.
The Kinetic Scalper features a completely custom momentum engine called the "Kinetic Pulse" - a volume-weighted momentum oscillator with Fisher Transform normalization that fundamentally differs from standard RSI or other momentum indicators. Every component feeds into a unified algorithmic framework designed specifically for this system.
KEY INNOVATIONS:
KINETIC PULSE ENGINE
Unlike standard RSI which uses simple price changes, the Kinetic Pulse applies:
→ Volume weighting to price movements (high-volume moves carry more weight)
→ EMA smoothing instead of traditional SMA (faster response to changes)
→ Fisher Transform normalization for improved signal clarity
→ Adaptive period adjustment based on current volatility regime
→ Result: A momentum oscillator that responds to conviction, not just price noise
15-FACTOR CONFLUENCE SCORING SYSTEM
Every signal is graded based on the number of confirming factors present:
→ Momentum position (oversold/overbought extremes)
→ Momentum velocity (direction change confirmation)
→ Momentum acceleration (strength of reversal)
→ Multi-oscillator divergence (price vs. 3 oscillators)
→ Volume confirmation (above-average participation)
→ Volume delta analysis (buying vs. selling pressure)
→ Higher timeframe alignment (trend confirmation from larger timeframe)
→ Session timing (major forex session awareness)
→ Structure clearance (clear path to profit targets)
→ Support/resistance proximity (confluence with key levels)
→ Market regime filtering (trending vs. choppy conditions)
Signals are graded A+, A, or B based on how many factors align:
• CONSERVATIVE MODE: A+ requires 12+ factors, A requires 9+, B requires 7+
• BALANCED MODE: A+ requires 10+ factors, A requires 7+, B requires 5+
• AGGRESSIVE MODE: A+ requires 8+ factors, A requires 5+, B requires 3+
TRADE ANALYSIS STATE MACHINE
A sophisticated monitoring system that tracks trade conditions in real-time using:
→ 5-state analysis framework (Factors Aligned / Positive Bias / Mixed Signals / Factors Weakening / Negative Bias)
→ Hysteresis-based transitions (different thresholds to enter vs. exit states)
→ Confidence smoothing with EMA (reduces noise, prevents flip-flopping)
→ Minimum commitment periods before state changes
→ Override logic for significant events (near TP/SL, momentum reversals)
→ Result: Stable, actionable guidance that doesn't change on every bar
INSTRUMENT-AWARE CALIBRATION
Automatically detects what you're trading and applies optimized parameters:
→ Forex Majors: Standard ATR, high session weight
→ Forex Crosses: Tighter stops, moderate session weight
→ Crypto: Wider stops (1.8x multiplier), reduced session weight (24/7 markets)
→ Indices: Moderate-wide stops, high session weight
→ Commodities: Moderate stops, moderate session weight
WHAT THIS INDICATOR DOES
The Kinetic Scalper is designed to identify high-confluence reversal opportunities by analyzing multiple dimensions of market behavior simultaneously.
CORE FUNCTIONS:
1. SIGNAL GENERATION
→ Identifies potential reversal points at oversold/overbought extremes
→ Confirms with multi-oscillator divergence detection
→ Validates with volume, higher timeframe, and structural analysis
→ Filters out low-probability setups automatically
→ Grades signals based on total confluence factors present
2. AUTOMATED TRADE TRACKING
→ Calculates structure-based or ATR-based stop loss levels
→ Projects take profit targets using risk-to-reward ratios
→ Monitors live position status (P/L, distance to targets, R-multiple)
→ Tracks TP1 and TP2 hits automatically
→ Displays outcome markers (TP HIT, PARTIAL WIN, STOPPED)
3. REAL-TIME CONDITION MONITORING
→ Analyzes 6 factor categories during active trades
→ Provides confidence scoring (0-100 scale)
→ Generates actionable guidance based on current market state
→ Alerts when conditions deteriorate or improve
→ Helps with trade management decisions
4. COMPREHENSIVE MARKET ANALYSIS
→ Session detection (Asian, London, New York, Overlap)
→ Volatility regime identification (Low, Normal, High, Extreme)
→ Trend state classification (Trending Up/Down, Ranging, Transitioning)
→ Volume analysis (relative volume and delta approximation)
→ Choppiness filtering (blocks signals in ranging markets)
WHY USE THIS INDICATOR
PROBLEM: Most momentum indicators generate too many false signals at extremes.
SOLUTION: The Kinetic Scalper requires MULTIPLE confirming factors before generating a signal, dramatically reducing noise and focusing on high-confluence setups.
ADVANTAGES:
✓ QUALITY OVER QUANTITY
→ Signal grading ensures you can filter for only the highest-quality setups
→ A+ signals have 10-12+ confirming factors aligned
→ Cooldown periods prevent over-trading the same move
✓ COMPLETE TRADE FRAMEWORK
→ Entry signals with confluence justification
→ Calculated stop loss based on market structure or ATR
→ Two profit targets with clear risk-to-reward ratios
→ Live trade monitoring with factor analysis
→ Outcome tracking and visual markers
✓ ADAPTIVE TO MARKET CONDITIONS
→ Volatility-based period adjustment for momentum calculations
→ Instrument-specific ATR multipliers
→ Session awareness for forex traders
→ Higher timeframe trend filtering
→ Automatic regime detection (trending vs. choppy)
✓ TRANSPARENT METHODOLOGY
→ Every input has detailed tooltips explaining its purpose
→ Signal tooltips show exactly why a signal was generated
→ Dashboard displays all relevant market conditions
→ Factor scores are visible during trades
→ No "black box" mystery calculations
✓ NON-REPAINTING & RELIABLE
→ All signals use barstate.isconfirmed (only on closed bars)
→ Higher timeframe data uses lookahead_off with historical offset
→ No future data access or repainting behavior
→ What you see is what you get - signals don't disappear or move
HOW THE INDICATOR WORKS
SIGNAL GENERATION PROCESS:
STEP 1: MOMENTUM ANALYSIS
The Kinetic Pulse engine calculates volume-weighted momentum:
→ Price changes are weighted by volume ratio vs. 20-bar average
→ High-volume moves have more influence on the oscillator
→ Gains and losses are smoothed using EMA (not SMA like RSI)
→ Fisher Transform is applied for normalization to 0-100 scale
→ Result: Momentum reading that emphasizes conviction, not noise
STEP 2: REVERSAL DETECTION
The indicator looks for potential reversal conditions:
→ Kinetic Pulse reaching oversold zone (below dynamic lower threshold)
→ Momentum velocity turning positive after being negative (for longs)
→ OR bullish divergence detected on multiple oscillators
→ Price making lower lows while oscillators make higher lows = divergence
STEP 3: MULTI-OSCILLATOR DIVERGENCE CONFIRMATION
Divergence is validated across three sources:
→ Kinetic Pulse divergence
→ CCI divergence
→ Stochastic divergence
→ Multiple oscillators confirming divergence increases signal reliability
STEP 4: CONFLUENCE FACTOR SCORING
The system evaluates all 15 possible confirming factors:
→ Momentum position: Is pulse oversold/overbought? (+0 to +2 points)
→ Momentum direction: Is velocity reversing? (+0 to +2 points)
→ Momentum acceleration: Is reversal strengthening? (+0 to +1 point)
→ Divergence count: How many oscillators show divergence? (+0 to +2 points)
→ Volume strength: Is volume above 1.3x average? (+0 to +1 point)
→ Volume delta: Is cumulative delta positive/negative? (+0 to +1 point)
→ HTF alignment: Does higher timeframe support direction? (+0 to +2 points)
→ Session timing: Is it a prime trading session? (+0 to +1 point)
→ Clear air: Is path to targets clear of obstacles? (+0 to +1 point)
→ Structure confluence: Are we near support/resistance? (+0 to +1 point)
→ Market regime: Is market trending, not choppy? (+0 to +1 point)
Total possible score: 15 points
Minimum for signal: 3-12 points depending on sensitivity mode
STEP 5: FILTER VALIDATION
Before generating a signal, additional checks are performed:
→ Volume must be above minimum threshold (if filter enabled)
→ Higher timeframe must not oppose the signal direction (if filter enabled)
→ Target path must be clear of major resistance/support (if filter enabled)
→ Volatility must not be EXTREME (blocks signals in chaos)
→ Risk-to-reward ratio must meet minimum requirement
→ Cooldown period must have elapsed since last signal
STEP 6: SIGNAL GRADING
If all filters pass, the signal is graded based on score:
→ A+ Grade: Highest confluence (8-12+ factors depending on sensitivity)
→ A Grade: High confluence (5-9+ factors)
→ B Grade: Moderate confluence (3-7+ factors)
Only graded signals (A+, A, or B) are displayed.
STEP 7: TRADE LEVEL CALCULATION
Stop loss and targets are calculated automatically:
STOP LOSS METHODS:
• Structure-Based: Uses recent swing low/high with ATR buffer, constrained by min/max ATR limits
• ATR-Based: Pure ATR multiplier with min/max constraints
• Fixed ATR: Simple ATR multiplier, no adjustments
TARGET CALCULATION:
• TP1: Entry ± (Stop Distance × Target 1 R:R)
• TP2: Entry ± (Stop Distance × Target 2 R:R)
• Default: TP1 at 1.0 R:R (1:1), TP2 at 2.0 R:R (1:2)
STEP 8: TRADE MONITORING
Once a signal is taken, the indicator tracks:
→ Current P/L in ticks and R-multiples
→ Distance to each target in ATR units
→ Distance to stop loss in ATR units
→ TP1 hit detection (marks with label, updates lines)
→ TP2 hit detection (closes trade, marks outcome)
→ Stop loss hit detection (closes trade, differentiates partial vs. full loss)
STEP 9: FACTOR ANALYSIS (DURING TRADES)
The Trade Analysis Panel monitors 6 key factor categories:
→ Momentum: Is momentum still aligned with trade direction? (-15 to +15 pts)
→ Position: Current R-multiple position (-12 to +12 pts)
→ Volume: Is volume still supportive? (-6 to +6 pts)
→ HTF Alignment: Does HTF still support trade? (-6 to +8 pts)
→ Target Proximity: How close are we to targets? (0 to +10 pts)
→ Stop Proximity: Are we dangerously close to stop? (-15 to +3 pts)
Raw scores are summed and smoothed using 5-bar EMA to create Confidence Score (0-100).
STEP 10: STATE MACHINE TRANSITIONS
Based on smoothed confidence, the system transitions between 5 states:
→ FACTORS ALIGNED (72+): Everything looks good
→ POSITIVE BIAS (58-72): Conditions favorable
→ MIXED SIGNALS (48-58): Neutral conditions
→ FACTORS WEAKENING (22-48): Concerning signals
→ NEGATIVE BIAS (<22): Poor conditions
Hysteresis prevents rapid flipping between states (different entry/exit thresholds).
RECOMMENDED TIMEFRAMES & INSTRUMENTS
TIMEFRAME VERSATILITY:
Despite the name "Scalper," this indicator works on ALL timeframes:
✓ LOWER TIMEFRAMES (1m - 15m)
→ Ideal for: Scalping and very short-term trades
→ Expect: More signals, faster trades, requires active monitoring
→ Best for: Forex majors, liquid crypto pairs
→ Tip: Use Conservative sensitivity to reduce noise
✓ MID TIMEFRAMES (15m - 1H)
→ Ideal for: Intraday trading and day trading
→ Expect: Moderate signal frequency, 1-4 hour trade duration
→ Best for: Forex, indices, major crypto
→ Tip: Balanced sensitivity works well here
✓ HIGHER TIMEFRAMES (4H - Daily)
→ Ideal for: Swing trading and position trading
→ Expect: Fewer signals, higher-quality setups, multi-day trades
→ Best for: All instruments
→ Tip: Can use Aggressive sensitivity for more opportunities
INSTRUMENT COMPATIBILITY:
✓ FOREX MAJORS (EUR/USD, GBP/USD, USD/JPY, etc.)
→ Auto-detected or manually select "Forex Major"
→ Session filtering is highly valuable here
→ London/NY overlap generates best signals
✓ FOREX CROSSES (EUR/GBP, AUD/NZD, etc.)
→ Auto-detected or manually select "Forex Cross"
→ Slightly tighter stops applied automatically
→ Session weight reduced vs. majors
✓ CRYPTOCURRENCIES (BTC, ETH, SOL, etc.)
→ Auto-detected or manually select "Crypto"
→ Wider stops (1.8x multiplier) due to volatility
→ Session filtering less relevant (24/7 markets)
→ Works well on both spot and perpetual futures
✓ INDICES (S&P 500, NASDAQ, DAX, etc.)
→ Auto-detected or manually select "Index"
→ Session opens (NY, London) are important
→ Moderate stop widths applied
✓ COMMODITIES (Gold, Silver, Oil, etc.)
→ Auto-detected or manually select "Commodity"
→ Moderate stops and session awareness
→ Works well on both spot and futures
VISUAL ELEMENTS EXPLAINED
SIGNAL MARKERS:
The indicator offers 3 display styles (choose in settings):
• PREMIUM STYLE (Default)
→ Signal appears below/above candles with connecting line
→ Background panel with grade badge (LONG , SHORT , etc.)
→ Entry price displayed
→ Direction arrow pointing to entry candle
→ Most informative, best for detailed analysis
• MINIMAL STYLE
→ Simple dot marker with grade text next to it
→ Clean, unobtrusive design
→ Best for mobile devices or cluttered charts
→ Less visual noise
• CLASSIC STYLE
→ Diamond marker with grade badge below/above
→ Traditional indicator aesthetic
→ Good balance between info and simplicity
ALL STYLES INCLUDE:
→ Signal tooltips with complete trade plan details
→ Grade display (A+, A, or B)
→ Color coding (bright colors for A+, standard for A/B)
SIGNAL TOOLTIP CONTENTS:
When you hover over any signal marker, you'll see:
→ Signal direction and grade
→ Confluence score (actual points vs. required)
→ Reason for signal (divergence type, reversal pattern)
→ Complete trade plan (Entry, Stop, TP1, TP2)
→ Risk in ticks
→ Risk-to-reward ratios
→ Market conditions at signal (Pulse value, HTF status, Volume, Session)
TRADE LEVEL LINES:
When Trade Tracking is enabled:
• ENTRY LINE (Yellow/Gold)
→ Solid horizontal line at entry price
→ Shaded zone around entry (±ATR buffer)
→ Label showing entry price
→ Extends 20-25 bars into future
• STOP LOSS LINE (Orange/Red)
→ Dashed line at stop level
→ Label showing stop price and distance in ticks
→ Turns dotted and changes color after TP1 hit (breakeven implied)
→ Deleted when trade closes
• TAKE PROFIT 1 LINE (Blue)
→ Dotted line at TP1 level
→ Label showing price and R:R ratio (e.g., "1:1.0")
→ Turns solid and changes to green when hit
→ Deleted after TP1 hit
• TAKE PROFIT 2 LINE (Blue)
→ Solid line at TP2 level
→ Label showing price and R:R ratio (e.g., "1:2.0")
→ This is the "full win" target
→ Deleted when trade closes
OUTCOME MARKERS:
When trade milestones are reached:
• - Green label appears when first target is touched
• - Green label when second target is touched (trade complete)
• - Red label if stop loss hit before any target
• - Orange label if TP1 hit but then stopped out
PREVIOUS DAY LEVELS:
If enabled (Show Previous Day Levels):
• PDH (Previous Day High) - Solid red/orange line
→ Label shows "PDH: "
→ Useful resistance reference for intraday trading
• PDL (Previous Day Low) - Solid green line
→ Label shows "PDL: "
→ Useful support reference for intraday trading
BACKGROUND TINTS:
Subtle background colors indicate states:
→ Light green tint: Active long position being tracked
→ Light red tint: Active short position being tracked
→ Light orange tint: Extreme volatility warning (signals blocked)
DASHBOARD GUIDE
The indicator features TWO dashboard panels:
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MAIN DASHBOARD (Top Right by default)
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WHEN NO TRADE IS ACTIVE:
→ Bias: Current market bias (BULLISH, BEARISH, NEUTRAL, LEAN LONG/SHORT)
→ Based on Kinetic Pulse position and velocity
→ Helps you understand overall momentum direction
→ Pulse: Current Kinetic Pulse value (0-100 scale)
→ <30 = Oversold (potential long setups developing)
→ >70 = Overbought (potential short setups developing)
→ 40-60 = Neutral zone
→ Volatility: Current volatility regime (LOW, NORMAL, HIGH, EXTREME)
→ Calculated from ATR ratio vs. 100-period average
→ EXTREME volatility blocks all signals (too chaotic)
→ Trend: Market state classification
→ TREND UP / TREND DOWN: ADX > 25, directional movement clear
→ RANGING: ADX < 20, choppy conditions
→ TRANSITIONING: ADX 20-25, developing conditions
→ VOLATILE: Extreme ATR regime
→ Session: Current forex session
→ ASIAN (00:00-08:00 UTC)
→ LONDON (07:00-16:00 UTC)
→ NEW YORK (13:00-22:00 UTC)
→ LDN/NY (13:00-16:00 UTC) - Overlap period, highest volatility
→ OFF-HOURS: Outside major sessions
→ Volume: Current volume vs. 20-bar average
→ Displayed as multiplier (e.g., "1.45x" = 45% above average)
→ Green if >1.3x (high volume, bullish for signal quality)
→ Red if <0.8x (low volume, bearish for signal quality)
→ HTF: Higher timeframe analysis status
→ BULLISH: HTF momentum supports longs
→ BEARISH: HTF momentum supports shorts
→ NEUTRAL: No clear HTF direction
→ Best Score: Highest confluence score currently available
→ Shows both long and short scores
→ Format: " / "
→ Example: "8/7 " means long score is 8, threshold is 7, long is leading
→ Helps you anticipate which direction might signal next
→ PDH/PDL: Previous day high and low prices
→ Quick reference for intraday support/resistance
WHEN TRADE IS ACTIVE:
→ Trade: Direction and grade (e.g., "LONG ")
→ Entry: Entry price of current trade
→ P/L: Current profit/loss
→ Shown in ticks and R-multiples
→ Format: "+45 | +0.75R" or "-20 | -0.35R"
→ Green when positive, red when negative
→ TP1: First target status
→ Shows price and distance if not hit
→ Shows "HIT" in green if reached
→ TP2: Second target price and distance
→ Stop: Stop loss price and current distance from stop
→ Bars: Number of bars since entry (trade duration)
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TRADE ANALYSIS PANEL (Bottom Left by default)
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This panel provides algorithmic analysis of market conditions. It does NOT provide investment advice or recommendations.
WHEN NO TRADE IS ACTIVE:
Shows scanning status and signal readiness:
→ Long/Short Readiness Gauges
→ Visual bar showing proximity to signal threshold
→ Score display (e.g., "8/7" means 8 points scored, 7 needed)
→ "RDY" indicator when threshold reached
→ Status Messages
→ "Scanning for setups..." - Normal scanning mode
→ "Long setup ready - cooldown: X bars" - Signal qualified but in cooldown
→ "Oversold conditions - watch for reversal" - Setup developing
→ "Choppy conditions detected" - Warning about market state
→ "Extreme volatility - signals blocked" - Safety filter active
WHEN TRADE IS ACTIVE:
Header shows current analysis state:
→ FACTORS ALIGNED (Green) - Everything looks good, confidence 72+
→ POSITIVE BIAS (Light Green) - Conditions favorable, confidence 58-72
→ MIXED SIGNALS (Blue) - Neutral conditions, confidence 48-58
→ FACTORS WEAKENING (Orange) - Concerning signals, confidence 22-48
→ NEGATIVE BIAS (Red) - Poor conditions, confidence <22
Confidence Score:
→ Displayed as percentage (0-100%)
→ Visual gauge (|||||.....)
→ Trend indicator (Rising, Falling, Stable)
→ Shows momentum of confidence change
Factor Breakdown (if enabled):
Shows 6 factor categories with individual scores:
→ Momentum: Is momentum aligned with trade? (-15 to +15 points)
→ Positive if velocity matches trade direction
→ Negative if momentum opposes trade
→ Position: Current R-multiple analysis (-12 to +12 points)
→ Positive if trade is in profit
→ Negative if underwater
→ Score increases as profit grows
→ Volume: Is volume supportive? (-6 to +6 points)
→ Positive if volume above average
→ Negative if volume weak
→ HTF Align: Higher timeframe status (-6 to +8 points)
→ Positive if HTF still supports trade direction
→ Negative if HTF turned against trade
→ Target: Proximity to profit targets (0 to +10 points)
→ Higher score when approaching targets
→ Bonus if TP1 already hit and near TP2
→ Stop Dist: Distance from stop loss (-15 to +3 points)
→ Negative if dangerously close to stop (<0.3 ATR)
→ Positive if well away from stop (>1.5 ATR)
Each factor shows:
• Score value with +/- indicator
• Trend symbol: + (improving), - (deteriorating), = (stable)
• Visual gauge
Guidance Messages:
→ "TARGET 2 APPROACHING" - TP2 within 0.3 ATR
→ "TARGET 1 APPROACHING" - TP1 within 0.3 ATR
→ "STOP PROXIMITY WARNING" - Stop within 0.3 ATR
→ "Factors aligned - Holding" - Positive state, stay in trade
→ "Conditions favorable" - Still looking good
→ "Conditions mixed - " - Neutral assessment
→ "Factors deteriorating" - Warning of weakening setup
→ "Confluence weakening - secure gains" - Consider exit if profitable
COMPACT MODE (Mobile-Friendly):
→ Reduces panel size by showing only essential info
→ Factor icons instead of full breakdowns
→ Simplified guidance messages
→ Perfect for smaller screens
SETTINGS GUIDE
MASTER SETTINGS:
Instrument Type
→ Purpose: Optimizes ATR multipliers and session weights for your asset
→ Options: Auto-Detect (recommended), Forex Major, Forex Cross, Crypto, Index, Commodity
→ Default: Auto-Detect
→ When to change: If auto-detection is incorrect for your symbol
Signal Sensitivity
→ Purpose: Controls how many factors required before generating signals
→ Options:
• Conservative: Requires 12+ for A+, 9+ for A, 7+ for B (fewer, highest quality)
• Balanced: Requires 10+ for A+, 7+ for A, 5+ for B (recommended)
• Aggressive: Requires 8+ for A+, 5+ for A, 3+ for B (more frequent)
→ Default: Balanced
→ When to change: If you want fewer signals (Conservative) or more opportunities (Aggressive)
Enable Trade Signals
→ Purpose: Master on/off switch for signal generation
→ Default: ON
→ When to disable: If you only want to use the analysis dashboards without signals
Enable Trade Tracking
→ Purpose: Tracks active trades and monitors conditions until TP/SL hit
→ Default: ON
→ When to disable: If you manage trades manually and don't want automatic tracking
Show Entry/Stop/Target Levels
→ Purpose: Displays trade plan lines and labels on chart
→ Default: ON
→ When to disable: If you prefer clean charts or manage levels yourself
DISPLAY SETTINGS:
Color Theme
→ Purpose: Optimizes colors for your chart background
→ Options: Dark (for dark charts), Light (for light charts)
→ Default: Dark
Signal Display Style
→ Purpose: Visual style of signal markers
→ Options:
• Premium: Badge with line and background panel (most detailed)
• Minimal: Simple dot with grade text (cleanest)
• Classic: Diamond marker with badge (traditional)
→ Default: Premium
Signal Distance
→ Purpose: How far signal labels appear from price bars (in ATR units)
→ Range: 0.5 to 10.0
→ Default: 2.0
→ When to adjust: Increase to 3.0-4.0 if signals hide behind candle wicks
TP/SL Label Distance
→ Purpose: Spacing of price labels to prevent overlap
→ Range: 0.5 to 5.0
→ Default: 1.5
Show Previous Day Levels
→ Purpose: Display PDH/PDL reference lines
→ Default: ON
→ Best for: Intraday traders who respect previous day levels
MAIN DASHBOARD:
Show Main Dashboard
→ Purpose: Toggle visibility of market conditions table
→ Default: ON
Main Dashboard Position
→ Options: Top Right, Top Left, Bottom Right, Bottom Left
→ Default: Top Right
→ When to change: To avoid overlap with TradingView's built-in panels
TRADE ANALYSIS PANEL:
Show Trade Analysis Panel
→ Purpose: Toggle factor analysis dashboard
→ Default: ON
Analysis Panel Position
→ Options: Top Right, Top Left, Bottom Right, Bottom Left, Middle Right, Middle Left
→ Default: Bottom Left
→ Recommended: Bottom Right or Middle Right to avoid overlap with Main Dashboard
Compact Mode
→ Purpose: Reduces panel size for mobile or smaller screens
→ Default: OFF
→ When to enable: Mobile trading, small screens, or minimalist preference
Show Factor Details
→ Purpose: Displays individual factor scores vs. overall confidence only
→ Default: ON
→ When to disable: For more compact view showing only state and confidence
RISK MANAGEMENT:
Stop Loss Method
→ Purpose: How stop loss distance is calculated
→ Options:
• Structure-Based: Uses swing highs/lows with ATR buffer (recommended)
• ATR-Based: Pure ATR multiplier with min/max constraints
• Fixed ATR: Simple multiplier, no adjustments
→ Default: Structure-Based
→ Impact: Structure-Based respects market geometry but constrains within safe limits
ATR Stop Multiplier
→ Purpose: Multiplier for ATR-based stop calculation
→ Range: 0.5 to 3.0
→ Default: 1.5
→ When to adjust:
• Increase to 2.0-2.5 for more breathing room (fewer false stops)
• Decrease to 1.0-1.2 for tighter stops (but more stop-outs)
Maximum Stop Distance (ATR)
→ Purpose: Cap on stop width to prevent excessive risk
→ Range: 1.0 to 5.0
→ Default: 2.5
→ Impact: If structure-based stop exceeds this, ATR-based stop is used instead
Minimum Stop Distance (ATR)
→ Purpose: Floor on stop width to avoid noise-induced stops
→ Range: 0.2 to 1.0
→ Default: 0.5
→ Impact: Prevents stops too tight to survive normal volatility
Target 1 Risk/Reward Ratio
→ Purpose: R:R for first profit target
→ Range: 0.5 to 2.0
→ Default: 1.0 (1:1 ratio)
→ Common values: 1.0 for quick profit taking, 1.5 for patient trading
Target 2 Risk/Reward Ratio
→ Purpose: R:R for second profit target (full win)
→ Range: 1.0 to 4.0
→ Default: 2.0 (1:2 ratio)
→ Common values: 2.0-3.0 for balanced risk/reward
Minimum R:R Required
→ Purpose: Filters out signals with poor risk/reward
→ Range: 0.5 to 2.0
→ Default: 1.0
→ Impact: Signals where potential reward doesn't meet this ratio are rejected
→ WARNING: Always ensure your position sizing means a stop loss = no more than 1-2% of your account, regardless of R:R ratio
SIGNAL FILTERS:
Session Awareness
→ Purpose: Weights signals higher during major forex sessions
→ Default: ON
→ Impact: Doesn't block signals, but session quality factors into scoring
→ Best for: Forex traders
Session Timezone
→ Purpose: Timezone for session calculations
→ Options: UTC, America/New_York, Europe/London, Asia/Tokyo, Asia/Hong_Kong
→ Default: UTC
→ When to change: Match your broker's server time
Higher Timeframe Alignment
→ Purpose: Checks HTF momentum before generating signals
→ Default: ON
→ Impact: Filters counter-trend signals, improves quality
→ Recommended: Keep enabled
HTF Timeframe
→ Purpose: Which higher timeframe to check
→ Default: Auto (blank field)
→ Auto selection:
• 1m chart → 5m HTF
• 5m chart → 15m HTF
• 15m chart → 1H HTF
• 1H chart → 4H HTF
• 4H+ chart → Daily HTF
→ Manual override: Enter any timeframe (e.g., "60" for 1-hour)
Volume Confirmation
→ Purpose: Requires above-average volume for signals
→ Default: ON
→ Impact: Filters low-liquidity false signals
→ Recommended: Keep enabled
Minimum Volume Ratio
→ Purpose: Volume threshold vs. 20-bar average
→ Range: 0.3 to 2.0
→ Default: 0.8 (80% of average)
→ When to adjust:
• Increase to 1.2-1.5 for only high-volume signals
• Decrease to 0.5-0.7 for more permissive filtering
Structure Clearance Check
→ Purpose: Ensures clear path to targets (no nearby resistance/support)
→ Default: ON
→ Impact: Prevents trades with immediate obstacles
→ Recommended: Keep enabled
Minimum Bars Between Signals
→ Purpose: Cooldown period after each signal
→ Range: 1 to 10
→ Default: 3
→ Impact: After a signal, this many bars must pass before another in same direction
→ When to adjust:
• Increase to 5-7 to prevent over-trading
• Decrease to 1-2 for faster re-entries
ADVANCED TUNING:
Momentum Period
→ Purpose: Base period for Kinetic Pulse calculation
→ Range: 5 to 30
→ Default: 14
→ When to adjust:
• Lower (8-10): More responsive, noisier
• Higher (18-21): Smoother, slower to react
→ Note: If Adaptive Period enabled, this is adjusted automatically
Adaptive Period
→ Purpose: Auto-adjusts momentum period based on volatility
→ Default: ON
→ Impact: Shortens period in high volatility, lengthens in low volatility
→ Recommended: Keep enabled for automatic optimization
Divergence Lookback
→ Purpose: How far back to search for divergence patterns
→ Range: 10 to 60
→ Default: 30
→ When to adjust:
• Shorter (15-20): Only recent divergences
• Longer (40-50): Catches older divergences (may be less relevant)
Swing Detection Bars
→ Purpose: Bars required on each side to confirm swing high/low
→ Range: 2 to 7
→ Default: 3
→ Impact on stops:
• Lower (2-3): More swing points, potentially tighter stops
• Higher (5-7): Only major swings, wider stops
Choppiness Index Threshold
→ Purpose: Threshold above which market considered choppy
→ Range: 38.2 to 80.0
→ Default: 61.8
→ Impact:
• Lower (50-55): Stricter quality filter (fewer signals in ranging markets)
• Higher (65-70): More permissive (allows signals in choppier conditions)
HOW TO READ SIGNALS
SIGNAL ANATOMY:
When a signal appears, you'll see:
1. DIRECTIONAL MARKER
→ Arrow, dot, or diamond pointing to entry candle (depends on style)
→ Positioned below price for LONG, above price for SHORT
→ Connected to price with line (Premium style)
2. GRADE BADGE
→ Displays signal quality: LONG , SHORT , etc.
→ Color coding:
• Bright green/cyan for A+ longs
• Standard green for A/B longs
• Bright pink/magenta for A+ shorts
• Standard red for A/B shorts
3. ENTRY PRICE (Premium style only)
→ Shows exact entry price at signal generation
4. TOOLTIP (all styles)
→ Hover over signal to see complete trade plan
→ Includes: Entry, Stop, TP1, TP2, Risk, R:R ratios, market conditions, signal reason, confluence score
INTERPRETING GRADES:
→ A+ SIGNALS (Highest Quality)
• 8-12+ confirming factors aligned
• Multiple divergences OR strong momentum reversal
• HTF alignment + volume + session timing + clear structure
• These are your highest-probability setups
• Recommended action: Give these priority, consider larger position size
→ A SIGNALS (High Quality)
• 5-9+ confirming factors aligned
• Good confluence, most key factors present
• Missing 1-2 optimal conditions
• These are still quality trades
• Recommended action: Standard position size, solid setups
→ B SIGNALS (Moderate Quality)
• 3-7+ confirming factors aligned
• Minimum viable confluence
• May be missing HTF alignment, volume, or session timing
• Higher variance outcomes
• Recommended action: Smaller position size or skip if conservative
SIGNAL NARRATIVE:
Each signal tooltip includes a narrative explaining WHY it was generated:
→ "Multi-divergence at oversold extreme"
• Multiple oscillators showing bullish divergence
• Kinetic Pulse in oversold zone
• High-quality reversal setup
→ "Bullish divergence near support"
• Divergence detected
• Price near key support level (swing low or PDL)
• Structure confluence
→ "Momentum reversal with HTF alignment"
• Kinetic Pulse velocity reversing
• Higher timeframe supports direction
• Strong trend-following setup
→ "Oversold momentum reversal"
• Extreme Kinetic Pulse reading reversing
• May not have divergence but strong momentum shift
READING THE TRADE PLAN:
Every signal comes with a complete trade plan:
→ ENTRY: The close price of the signal candle
• This is where the signal triggered
• If using limit orders, you might improve on this price
→ STOP: Calculated stop loss level
• Based on your Stop Loss Method setting
• Distance shown in ticks
• Risk tolerance: Ensure this represents ≤1-2% of your account
→ TP1: First profit target
• Default: 1:1 risk-reward
• This is your partial profit or first exit
• Consider taking 50% off at TP1
→ TP2: Second profit target
• Default: 1:2 risk-reward
• This is your "full win" target
• Hold remaining position for this level
SIGNAL FREQUENCY EXPECTATIONS:
Frequency varies by timeframe, sensitivity, and market conditions:
→ AGGRESSIVE MODE
• Lower timeframes (1m-5m): 5-15 signals per day
• Mid timeframes (15m-1H): 2-5 signals per day
• Higher timeframes (4H-D): 1-3 signals per week
→ BALANCED MODE (Default)
• Lower timeframes: 3-8 signals per day
• Mid timeframes: 1-3 signals per day
• Higher timeframes: 2-5 signals per week
→ CONSERVATIVE MODE
• Lower timeframes: 1-4 signals per day
• Mid timeframes: 0-2 signals per day
• Higher timeframes: 1-3 signals per week
Note: Frequency also depends on market volatility and trending vs. ranging conditions.
Example - Kinetic Scalper Trade Sequence
Here's an example showing the complete trade lifecycle with all dashboard transitions, annotations, and descriptions.
INSTRUMENT & TIMEFRAME DETAILS
Symbol: Nifty 50 Index (NSE)
Date: December 15, 2025
Session: London session (active trading hours)
Instrument Type: Index (auto-detected)
TRADE SEQUENCE BREAKDOWN
SCREENSHOT 1: Pre-Signal Setup Building (Image 1)
Time: ~12:00-14:30 UTC+5:30(approx.)
Price Action: Uptrend showing signs of exhaustion near 26,200
Market State: Price at session highs
Main Dashboard (Top Right):
- Bias: LEAN SHORT
- Pulse: 58.9 (approaching overbought)
- Volatility: NORMAL
- Trend: TRANSITIONING
- Session: LONDON (favorable timing)
- Volume: 0.98x (slightly below average)
- HTF: BULLISH (caution for counter-trend)
- Best Score: 9/5 (Short score building)
- PDH/PDL: 26098.25 / 25938.95
Trade Analysis Panel (Bottom Left):
- Status: NO ACTIVE TRADE
- Long Score: 5/5 (RDY)
- Short Score: 9/5 (RDY)
- Panel Message: "Short pattern developing - score: 9"
Description :
Setup Development Phase: The indicator identifies a potential short opportunity as price reaches the previous day's high. The short confluence score has climbed to 9/15 points, meeting the 'Balanced' sensitivity threshold for a Grade B signal. Notice the 'LEAN SHORT' bias and the Kinetic Pulse reading of 58.9 approaching overbought territory. The Trade Analysis panel shows 'Short pattern developing' with 9/5 factors aligned. Key factors: momentum approaching reversal zone, price at resistance (PDH), and London session providing favorable conditions.
SCREENSHOT 2: Signal Generated & Trade Entered (Image 2)
Time: ~13:00 UTC+5:30 (signal bar)
Entry Price: 26,184.65
Signal Grade: Grade
Main Dashboard (Top Right):
- Trade: SHORT
- Entry: 26184.65
- P/L: 5.95 pts | +0.2R (early positive movement)
- TP1: 26157.00 (33.2 pts away)
- TP2: 26129.35 (60.84 pts away)
- Stop: 26212.30 (22.1 pts away)
- Bars: 1 (just entered)
Trade Analysis Panel (Bottom Left):
- Header: TRADE ANALYSIS
- Status Bar: "Conditions mixed - improving 57%"
- Confidence: 57% RISING
- Factor Breakdown:
- Momentum: -4 (velocity not yet aligned)
- Position: +4 (slight profit)
- Volume: +2 = (volume present)
- HTF Align: +2 = (not strongly aligned)
- Target: +0 - (far from TP)
- Stop Dist: +3 - (good distance)
- Bottom Status: "Conditions mixed - Monitoring"
- Disclaimer: "Analysis only - Not financial advice"
Description:
Signal Activation: A Grade A short signal triggers at 26,184.65 after the short confluence score reached qualifying levels. The indicator places a structure-based stop loss at 26,212.30 (27.65 points risk) with dual targets at 1:1 and 1:2 risk-reward ratios.
The Trade Analysis Panel immediately begins monitoring with an initial confidence score of 57% - classified as 'MIXED SIGNALS' but showing a 'RISING' trend. Factor analysis reveals: momentum not yet aligned (-4 points as price just reversed), position slightly favorable (+4 points already +0.2R), volume adequate (+2), HTF showing weak alignment (+2 as we're counter-trend), stop well-placed (+3), but targets still distant (0 points).
Notice how the Main Dashboard switches from market scanning mode to active trade tracking, now displaying entry price, live P/L in both points (5.95 pts) and R-multiples (+0.2R), and distances to all key levels. The analysis panel provides real-time factor scoring to help monitor trade health.
SCREENSHOT 3: TP1 Hit - Trade Performing Well (Image 3)
Time: ~14:20 UTC+5:30(approx)
Price: ~26,154 (TP1 zone)
Bars in Trade: 29
Main Dashboard (Top Right):
- Trade: SHORT
- Entry: 26184.65
- P/L: 30.85 pts | +1.12R (excellent progress)
- TP1: HIT (displayed in green)
- TP2: 26129.35 (24.44 pts away)
- Stop: 26212.30 (58.5 pts away - well protected)
- Bars: 29
Trade Analysis Panel (Bottom Left):
- Header: TRADE ANALYSIS
- Status Bar: "Multiple factors positive"
- Confidence: 78% RISING
- Factor Breakdown:
- Momentum: +8 = (ALIGNED)
- Position: +8 + (strong profit zone)
- Volume: +2 + (continued support)
- HTF Align: +8 = (now strongly aligned)
- Target: +10 + (TP1 achieved, approaching TP2)
- Stop Dist: +3 + (excellent cushion)
- Bottom Status: "Multiple factors positive"
- Visual State: Green background (FACTORS ALIGNED state)
Description:
Trade Execution Phase - First Target Achieved: After 29 bars , price reaches the first take-profit target at 26,157.00. The ' ' marker confirms partial profit taking. Current P/L shows +30.85 points (+1.12R), exceeding the initial 1:1 risk-reward.
The Trade Analysis Panel shows dramatic improvement - confidence has surged to 78% (FACTORS ALIGNED state) with most factors now positive:
- Momentum factor improved to +8 (velocity aligned with trade direction)
- Position factor at +8 (over +1R profit zone)
- HTF Align jumped to +8 (higher timeframe now confirming the move)
- Target factor maxed at +10 (TP1 achieved, TP2 within reach)
- Stop Distance at +3 (58.5 points cushion providing safety)
Notice the panel status displays 'Multiple factors positive' with a green-tinted background, indicating optimal trade conditions. The confidence trend shows 'RISING' suggesting continued momentum. With TP1 secured and only 24.44 points to TP2, the trade is well-positioned for a full 1:2R win.
SCREENSHOT 4: TP2 Reached - Trade Complete (Image 4)
Time: ~15:00+ UTC+5:30
Final Exit: 26,129.35 (TP2)
Final Result: Full TP2 win
Main Dashboard (Top Right):
- Bias: NEUTRAL (reverted to scanning mode)
- Pulse: 45.2 (returned to neutral zone)
- Volatility: NORMAL
- Trend: TREND DOWN (confirmed the move)
- Session: LONDON
- Volume: 1.26x (increased as move developed)
- HTF: BEARISH (fully aligned post-trade)
- Best Score: 5/5 (neutral after completion)
Trade Analysis Panel (Bottom Left):
- Status: NO ACTIVE TRADE (reverted)
- Long Score: 5/5 (RDY)
- Short Score: 5/5 (RDY)
- Panel Message: "Scanning - prime session active"
- Light blue/cyan background (back to scanning mode)
Description:
Trade Completion - Full Target Achieved: The short trade reaches its second take-profit target at 26,129.35, securing a complete 1:2 risk-reward win. The ' ' marker confirms the exit. Final results:
- Entry: 26,184.65
- Exit: 26,129.35
- Profit: 55.30 points (approximately +2.0R)
- Outcome: Full TP2 success
Post-Trade Analysis: After trade closure, the indicator automatically returns to market scanning mode. The Main Dashboard reverts to showing market conditions rather than trade metrics. Notice how the 'Trend' now displays 'TREND DOWN' - confirming the move we captured. Volume increased to 1.26x during the winning move, validating the signal quality.
The Trade Analysis Panel switches back to 'NO ACTIVE TRADE' status and resumes displaying long/short setup scores. The confidence-based factor monitoring was instrumental throughout the trade:
- Initial entry at 57% confidence (MIXED SIGNALS)
- Peak confidence of 78% at TP1 (FACTORS ALIGNED)
- Real-time factor updates helped confirm trade validity
This example demonstrates the indicator's complete workflow: setup identification → signal generation → entry execution → live trade monitoring → systematic exit at targets.
KEY FEATURES DEMONSTRATED
1. Dual Dashboard System
- Main Dashboard: Market conditions (scanning) → Trade metrics (active position)
- Analysis Panel: Setup scores (scanning) → Factor-based confidence (in-trade)
2. Visual Trade Management
- Color-coded entry zones (yellow)
- Risk levels clearly marked (red dashed stop)
- Profit targets with R:R ratios labeled
- Achievement markers ( , )
3. Real-Time Factor Analysis
- 6-factor scoring system (Momentum, Position, Volume, HTF, Target, Stop Dist)
- Confidence percentage with trend indicators
- State machine (MIXED → FACTORS ALIGNED)
- Hysteresis prevents false state changes
4. Risk Management
- Structure-based stop placement (respects swing highs)
- Multiple take-profit levels (1:1 and 1:2 R:R)
- Live P/L tracking in points and R-multiples
- Distance monitoring to all key levels
This complete example showcases the indicator's progression from setup identification through trade completion, demonstrating how the dual-dashboard system and factor-based analysis provide continuous trade guidance. The structured stop-loss and dual-target approach delivered the planned 1:2 risk-reward ratio with systematic, rule-based execution.
ALERT SYSTEM
The indicator includes 9 built-in alert conditions:
SIGNAL ALERTS:
→ High-Grade Long Signal (A+)
• Triggers only on A+ long signals
• For traders who want only the highest-quality longs
• Message: "KINETIC SCALPER: LONG @ "
→ High-Grade Short Signal (A+)
• Triggers only on A+ short signals
• For traders who want only the highest-quality shorts
• Message: "KINETIC SCALPER: SHORT @ "
→ Long Signal
• Triggers on ANY qualified long signal (A+, A, or B)
• For traders who want all long opportunities
• Message: "KINETIC SCALPER: LONG @ "
→ Short Signal
• Triggers on ANY qualified short signal
• For traders who want all short opportunities
• Message: "KINETIC SCALPER: SHORT @ "
TRADE MANAGEMENT ALERTS:
→ TP1 Hit
• Triggers when first profit target is reached
• Useful for partial profit taking notifications
• Message: "KINETIC SCALPER: TP1 REACHED"
→ TP2 Reached
• Triggers when second profit target is reached
• Trade is complete, full win achieved
• Message: "KINETIC SCALPER: TP2 REACHED"
→ Stop Loss Hit
• Triggers when stop loss is reached
• Important for trade management and risk tracking
• Message: "KINETIC SCALPER: STOP LOSS"
ANALYSIS STATE ALERTS:
→ Analysis State: Negative Bias
• Triggers when factor analysis enters "Negative Bias" state
• Warning that trade conditions are deteriorating
• Consider reducing position or preparing to exit
• Message: "KINETIC SCALPER: Analysis state changed to NEGATIVE BIAS"
→ Analysis State: Factors Weakening
• Triggers when factor analysis enters "Factors Weakening" state
• Caution that confluence is diminishing
• Monitor trade closely
• Message: "KINETIC SCALPER: Analysis state changed to FACTORS WEAKENING"
HOW TO SET UP ALERTS:
1. Click the "Create Alert" button in TradingView
2. Condition: Select "Kinetic Scalper "
3. Choose your desired alert from the dropdown
4. Configure your alert options:
→ Once Per Bar Close (recommended for non-repainting)
→ Frequency: Once Per Bar Close or Only Once
5. Set expiration and notification methods (popup, email, webhook, etc.)
6. Create alert
RECOMMENDED ALERT STRATEGY:
For active traders:
→ Set "Long Signal" and "Short Signal" alerts for all opportunities
→ Set "TP1 Hit", "TP2 Reached", and "Stop Loss Hit" for trade management
→ Consider "Analysis State: Negative Bias" for trade monitoring
For selective traders:
→ Set only "High-Grade Long Signal (A+)" and "High-Grade Short Signal (A+)"
→ Focus on the absolute highest-quality setups
→ Set TP/SL alerts for position management
USAGE TIPS & BEST PRACTICES
SIGNAL SELECTION:
✓ GRADE MATTERS
→ A+ signals have statistically more confluence factors
→ If you're conservative, trade only A+ signals
→ B signals can work but require more discretion
✓ CONFLUENCE WITH YOUR ANALYSIS
→ Use this indicator as CONFIRMATION, not sole decision criteria
→ Combine with your own support/resistance analysis
→ Check for fundamental events (news, economic data)
→ Respect major round numbers and psychological levels
✓ SESSION TIMING (Forex)
→ Best signals often occur during London/NY overlap
→ Avoid signals 10 minutes before major news releases
→ Asian session signals can be valid but lower liquidity
✓ TIMEFRAME CONFLUENCE
→ If you get an A+ signal on 15m, check if 1H chart agrees
→ Higher timeframe confirmation adds conviction
→ Avoid signals that oppose the daily/4H trend
TRADE MANAGEMENT:
✓ POSITION SIZING
→ ALWAYS size positions so stop loss = 1-2% of account
→ Never risk more than you can afford to lose
→ Smaller position on B signals, standard on A, larger on A+ (within limits)
✓ PARTIAL PROFIT TAKING
→ Consider taking 50% off at TP1
→ Move stop to breakeven after TP1 hit
→ Let remaining position run to TP2
✓ TRAILING STOPS
→ The indicator doesn't auto-trail stops (manual decision)
→ After TP1, you might manually move stop to entry (breakeven)
→ Consider ATR-based trailing stop for runners
✓ WATCH THE ANALYSIS PANEL
→ If state changes to "Factors Weakening" while in profit, consider exit
→ "Negative Bias" during a trade is a strong warning
→ "Factors Aligned" confirms your trade thesis is still valid
RISK MANAGEMENT:
✓ NEVER IGNORE STOPS
→ The calculated stop is there for a reason
→ Moving stop further away increases risk exponentially
→ If stopped out, accept it and wait for next setup
✓ AVOID REVENGE TRADING
→ If you get stopped out, resist urge to immediately re-enter
→ Signal cooldown helps with this
→ Wait for next qualified signal
✓ RESPECT VOLATILITY WARNINGS
→ If indicator shows "EXTREME" volatility, signals are blocked for a reason
→ Don't force trades in chaotic conditions
→ Wait for regime to normalize
✓ CORRELATION RISK
→ Be aware of correlation if trading multiple pairs
→ EUR/USD and GBP/USD are highly correlated
→ Don't stack risk on correlated instruments
OPTIMIZATION:
✓ START WITH DEFAULTS
→ Default settings are well-tested
→ Don't over-optimize for recent market behavior
→ Give settings at least 20-30 trades before judging
✓ TIMEFRAME-SPECIFIC ADJUSTMENTS
→ Lower timeframes: Consider increasing Signal Distance to 3.0-4.0
→ Higher timeframes: ATR Stop Multiplier might go to 2.0-2.5
→ Crypto: Ensure Instrument Type is set to "Crypto" for proper stops
✓ SENSITIVITY CALIBRATION
→ Too many signals? Switch to Conservative
→ Missing good setups? Try Balanced or Aggressive
→ Quality > Quantity always
✓ KEEP A JOURNAL
→ Track which signal grades work best for you
→ Note which sessions produce best results
→ Review stopped trades for patterns
THINGS TO AVOID:
✗ DON'T chase signals after several bars have passed
✗ DON'T ignore the stop loss or move it further away
✗ DON'T overtrade by taking every B-grade signal
✗ DON'T trade during major news if you're not experienced
✗ DON'T use this as your only analysis tool
✗ DON'T expect 100% win rate (no indicator has this)
✗ DON'T risk more than 1-2% per trade regardless of signal grade
UNDERSTANDING THE METHODOLOGY
WHY VOLUME WEIGHTING?
Traditional momentum oscillators treat all price moves equally. A 10-point move on low volume is weighted the same as a 10-point move on high volume.
The Kinetic Pulse corrects this by:
→ Calculating volume ratio vs. 20-bar average
→ Applying square root transformation to volume ratio (prevents extreme weights)
→ Multiplying price changes by volume weight
→ Result: High-volume moves influence the oscillator more than low-volume noise
This helps filter false breakouts and emphasizes moves with participation.
WHY FISHER TRANSFORM?
Fisher Transform is a mathematical transformation that:
→ Normalizes probability distributions
→ Creates sharper turning points
→ Amplifies extremes while compressing the middle
→ Makes overbought/oversold levels more distinct
Applied to the Kinetic Pulse, it helps identify genuine extremes vs. noise.
WHY MULTI-OSCILLATOR DIVERGENCE?
Single-source divergence can give false signals. By requiring divergence confirmation across multiple oscillators (Kinetic Pulse, CCI, Stochastic), the system filters out:
→ Divergences caused by calculation quirks in one oscillator
→ Temporary momentum anomalies
→ False divergence on noisy, low-timeframe charts
Multiple sources confirming the same pattern increases reliability.
WHY ADAPTIVE PERIODS?
Fixed periods can be:
→ Too slow during high volatility (miss fast reversals)
→ Too fast during low volatility (generate noise)
The adaptive system:
→ Shortens period when ATR ratio > 1.3 (high volatility = need faster response)
→ Lengthens period when ATR ratio < 0.7 (low volatility = need noise filtering)
→ Keeps period in reasonable range (60% to 140% of base period)
→ Result: Oscillator adjusts to current market pace automatically
WHY HYSTERESIS IN STATE MACHINE?
Without hysteresis, the analysis state would flip-flop on every bar, creating:
→ Confusing, contradictory guidance
→ Analysis paralysis
→ Lack of actionable information
Hysteresis solves this by:
→ Using different thresholds to ENTER vs. EXIT a state
→ Example: Enter "Factors Aligned" at 72+ confidence, but don't exit until <62
→ This creates stable states that persist through minor fluctuations
→ Requires minimum commitment period (3 bars) before state changes
→ Overrides commitment for significant events (near TP/SL)
→ Result: Stable, trustworthy analysis that changes only when truly warranted
WHY CONFIDENCE SMOOTHING?
Raw factor scores fluctuate bar-by-bar based on momentary conditions. Smoothing:
→ Uses 5-period EMA on raw confidence scores
→ Filters out single-bar anomalies
→ Preserves genuine trends in confidence
→ Prevents false state transitions
→ Result: More reliable assessment of actual trade health
WHY INSTRUMENT-SPECIFIC PARAMETERS?
Different instruments have different characteristics:
→ Forex is highly liquid, respects technical levels well, standard ATR works
→ Crypto is extremely volatile, needs wider stops (1.8x) to avoid false stops
→ Indices respect session opens strongly, session weighting is important
→ Commodities fall in between
Auto-detection applies research-based multipliers automatically.
WHY STRUCTURE-BASED STOPS?
ATR-based stops can:
→ Place stop in middle of consolidation (easily hit)
→ Ignore obvious invalidation levels
→ Be too tight during expansion or too wide during contraction
Structure-based stops:
→ Use actual swing highs/lows (where traders actually place stops)
→ Add small ATR buffer to avoid stop hunting
→ Constrain within min/max ATR limits for safety
→ Result: Stops that respect market geometry while managing risk
DISCLAIMER & RISK WARNING
READ THIS CAREFULLY BEFORE USING THIS INDICATOR
This indicator is provided for EDUCATIONAL and INFORMATIONAL purposes only.
❌ NOT FINANCIAL ADVICE
This indicator does NOT constitute financial advice, investment recommendations, or solicitation to buy or sell any financial instrument. All information is for educational purposes only.
❌ NO GUARANTEES
→ Past performance does NOT guarantee future results
→ No indicator can predict future price movements with certainty
→ Signal grades represent confluence, NOT win probability
→ A+ signals can lose, B signals can win - markets are probabilistic
❌ SUBSTANTIAL RISK
Trading financial instruments involves SUBSTANTIAL RISK of loss:
→ You can lose your entire investment
→ Leveraged trading amplifies both gains AND losses
→ Never trade with money you cannot afford to lose
→ Never risk more than 1-2% of your account per trade
❌ YOUR RESPONSIBILITY
→ All trading decisions are YOUR responsibility
→ You must conduct your own analysis before entering trades
→ Consult a licensed financial advisor before trading
→ Understand the risks specific to your jurisdiction and situation
→ Only trade with capital you can afford to lose completely
❌ NO HOLY GRAIL
→ This indicator is a TOOL, not a complete trading system
→ It should be used as part of a broader analysis framework
→ Combine with your own technical analysis, risk management, and judgment
→ No indicator works 100% of the time in all market conditions
❌ ANALYSIS PANEL DISCLAIMER
The "Trade Analysis Panel" provides ALGORITHMIC ANALYSIS of market factors.
→ It does NOT provide investment advice or recommendations
→ Factor scores are mathematical calculations, not predictions
→ Guidance messages are informational, not directives
→ All trading decisions remain your responsibility
❌ BACKTESTING LIMITATIONS
→ This is an indicator, not a strategy, so no backtesting results are provided
→ Any backtesting you perform includes hindsight bias and optimization bias
→ Historical performance does not indicate future performance
→ Slippage, commissions, and real-world execution differ from backtests
❌ MARKET CONDITIONS
→ This indicator performs differently in trending vs. ranging markets
→ Extreme volatility can produce false signals or whipsaws
→ Low liquidity periods increase execution risk
→ Major news events can invalidate technical analysis
BY USING THIS INDICATOR, YOU ACKNOWLEDGE:
→ You have read and understood this disclaimer
→ You accept full responsibility for your trading decisions
→ You understand the substantial risks involved in trading
→ You will not hold the author liable for any losses incurred
→ You are using this tool as part of your own due diligence process
KEY FEATURES SUMMARY
✅ Volume-Weighted Kinetic Pulse Engine (proprietary momentum calculation)
✅ 15-Factor Confluence Scoring System (graded signals: A+, A, B)
✅ Multi-Oscillator Divergence Detection (Pulse + CCI + Stochastic)
✅ Higher Timeframe Trend Alignment Filter
✅ Adaptive Period Adjustment (volatility-responsive)
✅ Instrument-Aware Calibration (Forex, Crypto, Indices, Commodities)
✅ Structure-Based Stop Loss Calculation (respects swing highs/lows)
✅ Automated Trade Tracking (entry, stop, TP1, TP2, P/L)
✅ Real-Time Factor Analysis State Machine (5-state system with hysteresis)
✅ Session Awareness (Asian, London, New York, Overlap)
✅ Volatility Regime Detection (blocks signals in extreme conditions)
✅ Choppiness Filter (reduces signals in ranging markets)
✅ Volume Confirmation (relative volume and delta analysis)
✅ Clean Air Check (validates clear path to targets)
✅ Comprehensive Dashboards (market conditions + trade analysis)
✅ Customizable Display (3 signal styles, color themes, positioning)
✅ 9 Built-In Alert Conditions (signals, TP/SL hits, state changes)
✅ Fully Non-Repainting (barstate.isconfirmed, lookahead_off)
✅ Previous Day Levels (PDH/PDL reference lines)
✅ Mobile-Friendly Compact Mode (for smaller screens)
TECHNICAL SPECIFICATIONS
→ Pine Script Version: v6
→ Indicator Type: Overlay (displays on price chart)
→ License: Mozilla Public License 2.0
→ Copyright: BULLBYTE
→ Object Limits: 300 labels, 100 lines, 50 boxes
→ Memory Management: Automatic cleanup system (FIFO queue)
→ Repainting: Non-repainting (signals confirmed on bar close)
→ Timeframe Support: All timeframes (1s to Monthly)
→ Instrument Support: Forex, Crypto, Indices, Commodities, Stocks
→ HTF Data Handling: lookahead_off with historical offset
VERSION HISTORY
v1.0 - Initial Release
→ Kinetic Pulse engine with volume weighting and Fisher Transform
→ 15-factor confluence scoring system
→ Trade analysis state machine with hysteresis
→ Automated trade tracking and monitoring
→ Dual dashboard system (market conditions + factor analysis)
→ 9 alert conditions
→ 3 signal display styles
→ Instrument-aware calibration
→ Full risk management framework
WHO IS THIS INDICATOR FOR?
IDEAL FOR:
✓ Scalpers and day traders seeking high-confluence reversal entries
✓ Swing traders who want quality over quantity
✓ Traders who appreciate systematic, rules-based analysis
✓ Multi-timeframe traders who value HTF confirmation
✓ Forex traders who respect session timing
✓ Crypto traders needing volatility-adjusted parameters
✓ Traders who want complete trade management (entry, stop, targets)
✓ Analytical traders who want transparency in signal generation
NOT IDEAL FOR:
✗ Traders seeking a "set and forget" holy grail system
✗ Traders who don't want to learn the methodology
✗ Traders unwilling to accept losing trades as part of the process
✗ Traders who need constant signals (this is a quality-focused system)
✗ Traders who ignore risk management
FINAL THOUGHTS
The Kinetic Scalper is the result of extensive research into momentum behavior, volume confirmation, and multi-factor confluence analysis. It's designed to identify high-probability reversal setups while maintaining strict risk management and providing complete transparency.
This is NOT a magic solution. It's a sophisticated TOOL that requires:
→ Understanding of the methodology
→ Proper risk management discipline
→ Patience to wait for quality setups
→ Willingness to accept losses as part of trading
→ Integration with your own analysis and judgment
Used properly as part of a complete trading plan, the Kinetic Scalper can help you identify high-confluence opportunities and manage trades systematically.
Remember: Quality over quantity. Discipline over emotion. Risk management over everything.
Trade smart. Trade safe.
© 2025 BULLBYTE | Kinetic Scalper v1.0 | For Educational Purposes Only
Advanced ICC Multi-Timeframe 1.0Advanced ICC Multi-Timeframe Trading System
A comprehensive implementation and interpretation of the Indication, Correction, Continuation (ICC) trading methodology made popular by Trades by Sci, enhanced with advanced multi-timeframe analysis and automation features.
⚠️ CRITICAL TRADING WARNINGS:
DO NOT blindly follow BUY/SELL signals from this indicator
This indicator shows potential entry points but YOU must validate each trade
PAPER TRADE EXTENSIVELY before risking real capital
BACKTEST THOROUGHLY on your chosen instruments and timeframes
The ICC methodology requires understanding and discretion - automated signals are guidance only
This tool aids analysis but does not replace proper trade planning, risk management, or trader judgment
⚠️ Important Disclaimers:
This indicator is not endorsed by or affiliated with Trades by Sci
This is an early implementation and interpretation of the ICC methodology
May not work exactly as Trades by Sci executes his trades and entries
Requires further debugging, backtesting, and real-world validation
Completely free to use - no purchase required
I'm just one person obsessed with this method and wanted some better visualization of the chart/entries
About ICC:
The ICC method identifies complete market cycles through three phases: Indication (breakout), Correction (pullback), and Continuation (entry). This indicator automates the identification of these phases and adds powerful features for modern traders.
Key Features:
Multi-Timeframe Capabilities:
Automatic timeframe detection with optimized settings for 5m, 15m, 30m, 1H, 4H, and Daily charts
Higher timeframe overlay to view HTF ICC levels on lower timeframe charts for precise entry timing
Smart defaults that adjust swing length and consolidation detection based on your timeframe
Advanced Phase Tracking:
Complete ICC cycle tracking: Indication, Correction, Consolidation, Continuation, and No Setup phases
Live structure detection shows potential peaks/troughs before full confirmation
Intelligent invalidation logic detects failed setups when market structure reverses
Dynamic phase backgrounds for instant visual confirmation
Three Types of Entry Signals:
Traditional Entries - Price crosses back through the original indication level (strongest signals)
"BUY" (green) / "SELL" (red)
Breakout Entries - Price breaks out of consolidation range in the same direction
"BUY" (green) / "SELL" (red)
Reversal Entries (Optional, can be toggled off) - Price breaks consolidation in opposite direction, indicating failed setup
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
More aggressive, counter-trend signals
Can be disabled for more conservative trading
Professional Features:
Volatility-based support/resistance zones (ATR-adjusted) that adapt to market conditions
Historical zone tracking (0-3 configurable) with visual hierarchy
Comprehensive real-time info table displaying all key metrics
Full alert system for entries, indications, and consolidation detection
Visual distinction between high-confidence trend entries and cautionary reversal entries
📖 USAGE GUIDE
Entry Signal Types:
The indicator provides three types of entry signals with visual distinction:
Strong Entries (High Confidence):
"BUY" (bright green) / "SELL" (bright red)
Includes traditional entries (crossing back through indication level) and breakout entries (breaking consolidation in trend direction)
These are trend continuation or breakout signals with higher probability
Recommended for all traders
Reversal Entries (Caution - Counter-Trend):
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
Triggered when price breaks out of correction/consolidation in the OPPOSITE direction
Indicates a failed setup and potential trend reversal
More aggressive, counter-trend plays
Can be toggled off in settings for more conservative trading
Recommended only for experienced traders or after thorough backtesting
Swing Length Settings:
The swing length determines how many bars on each side are needed to confirm a swing high/low. This is the most important setting for tuning the indicator to your style.
Auto Mode (Recommended for beginners): Toggle "Use Auto Timeframe Settings" ON
5-minute: 30 bars
15-minute: 20 bars
30-minute: 12 bars
1-hour: 7 bars
4-hour: 5 bars
Daily: 3 bars
Manual Mode: Toggle "Use Auto Timeframe Settings" OFF
Lower values (3-7): More aggressive, detects smaller swings
Pros: More signals, faster entries, catches smaller moves
Cons: More noise, more false signals, requires tighter stops
Best for: Scalping, active day trading, volatile markets
Higher values (12-20): More conservative, only major swings
Pros: More reliable signals, fewer false breakouts, clearer structure
Cons: Fewer signals, delayed entries, might miss smaller opportunities
Best for: Swing trading, position trading, trending markets
Default Manual Setting: 7 bars (balanced for 1H charts)
Minimum: 3 bars
Consolidation Bars Setting:
Determines how many bars without new structure are needed before flagging consolidation.
Lower values (3-10): Faster detection, catches brief pauses, more sensitive
Best for: Lower timeframes, volatile markets, avoiding any chop
Higher values (20-40): More reliable, only flags true extended consolidation
Best for: Higher timeframes, trending markets, patient traders
Current defaults scale with timeframe (more bars needed on shorter timeframes)
Historical S/R Zones:
Shows previous support and resistance levels to provide context.
Default: 2 historical zones (shows current + 2 previous)
Range: 0-3 zones
Visual Hierarchy: Older zones are more transparent with dashed borders
Usage: Higher numbers (2-3) show more historical context but can clutter the chart. Start with 2 and adjust based on your preference.
Live Structure Feature (Yellow Warning ⚠):
Provides early warning of potential structure changes before full confirmation.
What it does: Detects potential swing highs/lows after just 2 bars instead of waiting for full swing_length confirmation
Live Peak: Shows when a high is followed by 2 lower closes (potential top forming)
Live Trough: Shows when a low is followed by 2 higher closes (potential bottom forming)
Important: These are UNCONFIRMED - they may be invalidated if price reverses
Use case: Get early awareness of potential reversals while waiting for confirmation
Displayed in: Info table only (no visual markers on chart to reduce clutter)
Only shows: Peaks higher than last swing high, or troughs lower than last swing low (filters out noise)
Higher Timeframe (HTF) Analysis:
View higher timeframe ICC structure while trading on lower timeframes.
How to enable: Toggle "Show Higher Timeframe ICC" ON
Setup: Set "Higher Timeframe" to your reference timeframe
Example: Trading on 15-minute? Set HTF to 240 (4-hour) or 60 (1-hour)
Example: Trading on 5-minute? Set HTF to 60 (1-hour) or 15 (15-minute)
What it shows:
HTF indication levels displayed as dashed lines
Blue = HTF Bullish Indication
Purple = HTF Bearish Indication
HTF phase and levels shown in info table
Trading workflow:
Check HTF phase for overall market direction
Wait for HTF correction phase
Drop to lower timeframe to find precise entries
Enter when lower TF shows continuation in alignment with HTF
Best practice: HTF should be 3-4x your trading timeframe for best results
Reversal Entries Toggle:
Default: ON (shows all signal types)
Toggle OFF for more conservative trading (only trend continuation signals)
Recommended: Backtest with both settings to see which works better for your style
New traders should consider disabling reversal entries initially
Volatility-Based Zones:
When enabled, support/resistance zones automatically adjust their height based on ATR (Average True Range).
More volatile = wider zones
Less volatile = tighter zones
Toggle OFF for fixed-width zones
Community Feedback Welcome:
This is an evolving project and your input is valuable! Please share:
Bug reports and issues you encounter
Feature requests and suggestions for improvement
Results from your backtesting and live trading experience
Feedback on the reversal entry feature (too aggressive? working well?)
Ideas for better aligning with the ICC methodology
Perfect for traders learning or implementing the ICC methodology with the benefit of modern automation, multi-timeframe analysis, and flexible entry signal options.
ICT订单块交易【实时不滞后】Used to identify "Order Blocks" (OB), based on Break of Structure (BOS) and Retest mechanisms. It detects candles in the opposite direction after swing highs/lows to form potential supply/demand zones, confirming and plotting valid OBs only upon price retest. The indicator emphasizes "real" OBs: requiring a strong impulse (> ATR * multiplier) and retest verification.
- **Core Functions**: Detect BOS (Break of Structure); find opposite candles after prior impulses; verify strength and retest; draw OB boxes and labels.
- **Applicable Scenarios**: Suitable for ICT strategies, supply-demand trading, or reversal identification. Helps filter false breakouts and shows only high-probability zones.
- **Display Mode**: Overlaid on the main chart, displaying OBs as boxes, supporting up to 500 boxes.
- **Limitations**: Retest period fixed at 15 bars; based on simple candlesticks (no volume filter); no automatic cleanup of old OBs (manual management required).
The indicator has no built-in alerts but can be extended. ATR is used dynamically to validate strength.
## Input Parameters
Input parameters are concise, divided into core settings and display group. Below explains each parameter’s default value, type, and function.
### Core Settings
- **Structure Lookback** (int, default: 10, min: 3): Lookback period for structure detection (length for ta.highest/lowest). Higher values detect stronger structures.
- **Minimum Impulse Strength (ATR ×)** (float, default: 1.5, min: 0.5): Minimum impulse strength ((high-low) > ATR * this value). Ensures significant movement before OB.
- **Bars to watch for Retest** (int, default: 15, min: 1): Number of bars to monitor for retest. OB is confirmed only if price retests the OB zone within N bars after a breakout.
### Display Settings
- **Show Bullish OBs** (bool, default: true): Show bullish OBs (demand zone, rebounds after retest).
- **Show Bearish OBs** (bool, default: true): Show bearish OBs (supply zone, reverses after retest).
Colors are fixed: green (bullish, 80% transparency), red (bearish, 80% transparency).
## Calculations and Display
### Break of Structure (BOS) Detection
- **ATR Calculation**: ta.atr(14) used for strength verification.
- **Swing High/Low**: ta.highest(high, lookback) / ta.lowest(low, lookback) to identify structure. ...
## Calculation and Display
### Structure Breakout (BOS) Detection
- **ATR Calculation**: `ta.atr(14)` used for strength verification.
- **Swing High/Low**: `ta.highest(high, lookback)` / `ta.lowest(low, lookback)` identify structure.
- **BOS Trigger**:
- **bullBOS**: close > hh (breaks previous high).
- **bearBOS**: close < ll (breaks previous low).
### Order Block Identification
- **getLastOppositeCandle(isBullish)**:
- Search for the most recent "opposite" candle within the lookback period (bullBOS: bearish candle close < open; bearBOS: bullish candle close > open).
- Returns the index (idx); if none, then na.
- **OB Logic** (only when showBullish/Bearish=true):
- **Bullish OB (bullBOS)**:
- Find previous bearish candle (idx), check momentum: (high-low) > ATR * atrMult.
- Calculate obLow = low , obHigh = high .
- Backtest check: within 15 candles low inside → inRetest = true.
- If confirmed: draw green box (from bar_index - idx to current, obLow to obHigh); label "🟩 Bullish OB (Valid)" (top-left, green, 80% transparency, white text).
- Push into bullOBs array.
- **Bearish OB (bearBOS)**: symmetric, red box, label "🟥 Bearish OB (Valid)" (bottom-left).
- **Array Management**: var box bullOBs/bearOBs store all OBs; no automatic cleanup (expandable).
### Display Elements
- **Boxes**: dynamically from idx to current candle, visually showing OB area.
- **Labels**: displayed when confirmed, positioned based on obHigh/obLow.
- No lines/fills; pure boxes + labels.
## Alert Functionality
The indicator has no built-in alerts but can be extended via TradingView alerts, for example:
- **New OB**: bullBOS and inRetest or bearBOS and inRetest.
- **Backtest**: price enters OB range.
It is recommended to add `alertcondition()` for custom alerts. ...
It is recommended to add a custom alertcondition(), such as 'Bullish OB Confirmed'.
## Usage Tips
- **Optimization**: lookback=10 balances sensitivity; atrMult=1.5 filters weak impulses; retestBars=15 is suitable for intraday.
- **Customization**: turn off showBullish/Bearish to hide types; add volume filtering to the fork for better accuracy.
- **Explanation**:
- **BOS + Backtesting**: ensure OB is 'real' (not a false breakout); only draw after backtesting to avoid noise.
- **Strength**: (high-low)>ATR*1.5 indicates strong impulses, making OB more reliable.
- **Application**: Bullish OB = buy zone (support); Bearish OB = sell zone (resistance).
- **Limitations**: fixed backtesting period may miss late retracements; no volume/time filtering; few OBs in low-volatility markets.
- **Extensions**: add OB counts or Fibonacci extensions.
ICT订单块交易指标，用于识别“订单块”（Order Blocks, OB），基于结构突破（Break of Structure, BOS）与回测（Retest）机制。它通过检测摆动高/低点后的相反方向烛台，形成潜在供给/需求区域，仅在价格回测时确认并绘制有效OB。指标强调“真实”OB：需强冲动（> ATR * 乘数）与回测验证。
- **核心功能**：检测BOS（结构突破）；查找前冲动相反烛台；验证强度与回测；绘制OB盒子与标签。
- **适用场景**：适合ICT策略、供给需求交易或反转识别。帮助过滤假突破，仅显示高概率区域。
- **显示模式**：叠加在主图上，使用盒子（boxes）显示OB，支持最大500个盒子。
- **限制**：回测期固定15柱；基于简单烛台（无成交量过滤）；无自动清理旧OB（手动管理）。
指标无内置警报，但可扩展。数据使用ATR动态验证强度。
## 输入参数
输入参数简洁，分为核心设置与显示组。以下说明每个参数的默认值、类型和作用。
### 核心设置
- **Structure Lookback** (int, 默认: 10, 最小: 3)：结构检测回溯期（ta.highest/lowest的长度）。较高值检测更强结构。
- **Minimum Impulse Strength (ATR ×)** (float, 默认: 1.5, 最小: 0.5)：最小冲动强度（(high-low) > ATR * 此值）。确保OB前有显著移动。
- **Bars to watch for Retest** (int, 默认: 15, 最小: 1)：回测监控柱数。突破后N柱内价格回测OB区域才确认。
### 显示设置
- **Show Bullish OBs** (bool, 默认: true)：显示看涨OB（需求区，回测后反弹）。
- **Show Bearish OBs** (bool, 默认: true)：显示看跌OB（供给区，回测后反转）。
颜色固定：绿（看涨，80%透明）、红（看跌，80%透明）。
## 计算与显示
### 结构突破（BOS）检测
- **ATR计算**：ta.atr(14) 用于强度验证。
- **摆动高/低**：ta.highest(high, lookback) / ta.lowest(low, lookback) 识别结构。
- **BOS触发**：
- **bullBOS**：close > hh （上破前高）。
- **bearBOS**：close < ll （下破前低）。
### 订单块识别
- **getLastOppositeCandle(isBullish)**：
- 查找最近lookback柱内“相反”烛台（bullBOS: 熊烛 close < open；bearBOS: 牛烛 close > open）。
- 返回索引（idx）；若无则na。
- **OB逻辑**（仅当showBullish/Bearish=true）：
- **看涨OB (bullBOS)**：
- 查找前熊烛（idx），检查冲动：(high-low) > ATR * atrMult。
- 计算obLow=low ，obHigh=high 。
- 回测检查：15柱内low 在 内 → inRetest=true。
- 若确认：绘制绿盒（bar_index-idx 到当前，obLow到obHigh）；标签“🟩 Bullish OB (Valid)”（左上，绿，80%透明，白文本）。
- 推入bullOBs数组。
- **看跌OB (bearBOS)**：对称，红盒，标签“🟥 Bearish OB (Valid)”（左下）。
- **数组管理**：var box bullOBs/bearOBs 存储所有OB；无自动清理（可扩展）。
### 显示元素
- **盒子**：动态从idx到当前柱，延伸显示OB区域。
- **标签**：确认时显示，位置基于obHigh/obLow。
- 无线条/填充；纯盒子+标签。
## 警报功能
指标无内置警报，但可通过TradingView警报扩展，例如：
- **新OB**：bullBOS and inRetest 或 bearBOS and inRetest。
- **回测**：价格进入OB范围。
建议添加alertcondition()自定义，如“Bullish OB Confirmed”。
## 使用提示
- **优化**：lookback=10平衡敏感；atrMult=1.5过滤弱冲动；retestBars=15适合日内。
- **自定义**：关闭showBullish/Bearish隐藏类型；fork添加成交量过滤提升准确。
- **解释**：
- **BOS+回测**：确保OB“真实”（非假突破）；仅回测后绘制，避免噪音。
- **强度**：(high-low)>ATR*1.5表示强冲动，OB更可靠。
- **应用**：看涨OB=买入区（支撑）；看跌OB=卖出区（阻力）。
- **局限**：回测期固定，可能错过晚回测；无成交量/时间过滤；低波动市场少OB。
- **扩展**：添加OB计数或斐波那契扩展。
Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
Quantum Market Harmonics [QMH]# Quantum Market Harmonics - TradingView Script Description
## 📊 OVERVIEW
Quantum Market Harmonics (QMH) is a comprehensive multi-dimensional trading indicator that combines four independent analytical frameworks to generate high-probability trading signals with quantifiable confidence scores. Unlike simple indicator combinations that display multiple tools side-by-side, QMH synthesizes temporal analysis, inter-market correlations, behavioral psychology, and statistical probabilities into a unified confidence scoring system that requires agreement across all dimensions before generating a confirmed signal.
---
## 🎯 WHAT MAKES THIS SCRIPT ORIGINAL
### The Core Innovation: Weighted Confidence Scoring
Most indicators provide binary signals (buy/sell) or display multiple indicators separately, leaving traders to interpret conflicting information. QMH's originality lies in its weighted confidence scoring system that:
1. **Combines Four Independent Methods** - Each framework (described below) operates independently and contributes points to an overall confidence score
2. **Requires Multi-Dimensional Agreement** - Signals only fire when multiple frameworks align, dramatically reducing false positives
3. **Quantifies Signal Strength** - Every signal includes a numerical confidence rating (0-100%), allowing traders to filter by quality
4. **Adapts to Market Conditions** - Different market regimes activate different component combinations
### Why This Combination is Useful
Traditional approaches suffer from:
- **Single-dimension bias**: RSI shows oversold, but trend is still down
- **Conflicting signals**: MACD says buy, but volume is weak
- **No prioritization**: All signals treated equally regardless of strength
QMH solves these problems by requiring multiple independent confirmations and weighting each component's contribution to the final signal. This multi-dimensional approach mirrors how professional traders analyze markets - not relying on one indicator, but waiting for multiple pieces of evidence to align.
---
## 🔬 THE FOUR ANALYTICAL FRAMEWORKS
### 1. Temporal Fractal Resonance (TFR)
**What It Does:**
Analyzes trend alignment across four different timeframes simultaneously (15-minute, 1-hour, 4-hour, and daily) to identify periods of multi-timeframe synchronization.
**How It Works:**
- Uses `request.security()` with `lookahead=barmerge.lookahead_off` to retrieve confirmed price data from each timeframe
- Calculates "fractal strength" for each timeframe using this formula:
```
Fractal Strength = (Rate of Change / Standard Deviation) × 100
```
This creates a momentum-to-volatility ratio that measures trend strength relative to noise
- Computes a Resonance Index when all four timeframes show the same directional bias
- The index averages the absolute strength values when all timeframes align
**Why This Method:**
Fractal Market Hypothesis suggests that price patterns repeat across different time scales. When trends align from short-term (15m) to long-term (Daily), the probability of trend continuation increases substantially. The momentum/volatility ratio filters out low-conviction moves where volatility dominates direction.
**Contribution to Confidence Score:**
- TFR Bullish = +25 points
- TFR Bearish = +25 points (to bearish confidence)
- No alignment = 0 points
---
### 2. Cross-Asset Quantum Entanglement (CAQE)
**What It Does:**
Analyzes correlation patterns between the current asset and three reference markets (Bitcoin, US Dollar Index, and Volatility Index) to identify both normal correlation behavior and anomalous breakdowns that often precede significant moves.
**How It Works:**
- Retrieves price data from BTC (BINANCE:BTCUSDT), DXY (TVC:DXY), and VIX (TVC:VIX) using confirmed bars
- Calculates Pearson correlation coefficient between the main asset and each reference:
```
Correlation = Covariance(X,Y) / (StdDev(X) × StdDev(Y))
```
- Computes an Intermarket Pressure Index by weighting each reference asset's momentum by its correlation strength:
```
Pressure = (Corr₁ × ROC₁ + Corr₂ × ROC₂ + Corr₃ × ROC₃) / 3
```
- Detects "correlation breakdowns" when average correlation drops below 0.3
**Why This Method:**
Markets don't operate in isolation. Inter-market analysis (developed by John Murphy) recognizes that:
- Crypto assets often correlate with Bitcoin
- Risk assets inversely correlate with VIX (fear gauge)
- Dollar strength affects commodity and crypto prices
When these normal correlations break down, it signals potential regime changes. The term "quantum" reflects the interconnected nature of these relationships - like quantum entanglement where distant particles influence each other.
**Contribution to Confidence Score:**
- CAQE Bullish (positive pressure, stable correlations) = +25 points
- CAQE Bearish (negative pressure, stable correlations) = +25 points (to bearish)
- Correlation breakdown = Warning marker (potential reversal zone)
---
### 3. Adaptive Market Psychology Matrix (AMPM)
**What It Does:**
Classifies the current market emotional state into six distinct categories by analyzing the interaction between momentum (RSI), volume behavior, and volatility acceleration (ATR change).
**How It Works:**
The system evaluates three metrics:
1. **RSI (14-period)**: Measures overbought/oversold conditions
2. **Volume Analysis**: Compares current volume to 20-period average
3. **ATR Rate of Change**: Detects volatility acceleration
Based on these inputs, the market is classified into:
- **Euphoria**: RSI > 80, volume spike present, volatility rising (extreme bullish emotion)
- **Greed**: RSI > 70, normal volume (moderate bullish emotion)
- **Neutral**: RSI 40-60, declining volatility (balanced state)
- **Fear**: RSI 40-60, low volatility (uncertainty without panic)
- **Panic**: RSI < 30, volume spike present, volatility rising (extreme bearish emotion)
- **Despair**: RSI < 20, normal volume (capitulation phase)
**Why This Method:**
Behavioral finance principles (Kahneman, Tversky) show that markets follow predictable emotional cycles. Extreme psychological states often mark reversal points because:
- At Euphoria/Greed peaks, everyone bullish has already bought (no buyers left)
- At Panic/Despair bottoms, everyone bearish has already sold (no sellers left)
AMPM provides contrarian signals at these extremes while respecting trends during Fear and Greed intermediate states.
**Contribution to Confidence Score:**
- Psychology Bullish (Panic/Despair + RSI < 35) = +15 points
- Psychology Bearish (Euphoria/Greed + RSI > 65) = +15 points
- Neutral states = 0 points
---
### 4. Time-Decay Probability Zones (TDPZ)
**What It Does:**
Creates dynamic support and resistance zones based on statistical probability distributions that adapt to changing market volatility, similar to Bollinger Bands but with enhancements for trend environments.
**How It Works:**
- Calculates a 20-period Simple Moving Average as the basis line
- Computes standard deviation of price over the same period
- Creates four probability zones:
- **Extreme Upper**: Basis + 2.5 standard deviations (≈99% probability boundary)
- **Upper Zone**: Basis + 1.5 standard deviations
- **Lower Zone**: Basis - 1.5 standard deviations
- **Extreme Lower**: Basis - 2.5 standard deviations (≈99% probability boundary)
- Dynamically adjusts zone width based on ATR (Average True Range):
```
Adjusted Upper = Upper Zone + (ATR × adjustment_factor)
Adjusted Lower = Lower Zone - (ATR × adjustment_factor)
```
- The adjustment factor increases during high volatility, widening the zones
**Why This Method:**
Traditional support/resistance levels are static and don't account for volatility regimes. TDPZ zones are probability-based and mean-reverting:
- Price has ≈99% probability of staying within extreme zones in normal conditions
- Touches to extreme zones represent statistical outliers (high-probability reversal opportunities)
- Zone expansion/contraction reflects volatility regime changes
- ATR adjustment prevents false signals during unusual volatility
The "time-decay" concept refers to mean reversion - the further price moves from the basis, the higher the probability of eventual return.
**Contribution to Confidence Score:**
- Price in Lower Extreme Zone = +15 points (bullish reversal probability)
- Price in Upper Extreme Zone = +15 points (bearish reversal probability)
- Price near basis = 0 points
---
## 🎯 HOW THE CONFIDENCE SCORING SYSTEM WORKS
### Signal Generation Formula
QMH calculates separate Bullish and Bearish confidence scores each bar:
**Bullish Confidence (0-100%):**
```
Base Score: 20 points
+ TFR Bullish: 25 points (if all 4 timeframes aligned bullish)
+ CAQE Bullish: 25 points (if intermarket pressure positive)
+ AMPM Bullish: 15 points (if Panic/Despair contrarian signal)
+ TDPZ Bullish: 15 points (if price in lower probability zones)
─────────
Maximum Possible: 100 points
```
**Bearish Confidence (0-100%):**
```
Base Score: 20 points
+ TFR Bearish: 25 points (if all 4 timeframes aligned bearish)
+ CAQE Bearish: 25 points (if intermarket pressure negative)
+ AMPM Bearish: 15 points (if Euphoria/Greed contrarian signal)
+ TDPZ Bearish: 15 points (if price in upper probability zones)
─────────
Maximum Possible: 100 points
```
### Confirmed Signal Requirements
A **QBUY** (Quantum Buy) signal generates when:
1. Bullish Confidence ≥ User-defined threshold (default 60%)
2. Bullish Confidence > Bearish Confidence
3. No active sell signal present
A **QSELL** (Quantum Sell) signal generates when:
1. Bearish Confidence ≥ User-defined threshold (default 60%)
2. Bearish Confidence > Bullish Confidence
3. No active buy signal present
### Why This Approach Is Different
**Example Comparison:**
Traditional RSI Strategy:
- RSI < 30 → Buy signal
- Result: May buy into falling knife if trend remains bearish
QMH Approach:
- RSI < 30 → Psychology shows Panic (+15 points)
- But requires additional confirmation:
- Are all timeframes also showing bullish reversal? (+25 points)
- Is intermarket pressure turning positive? (+25 points)
- Is price at a statistical extreme? (+15 points)
- Only when total ≥ 60 points does a QBUY signal fire
This multi-layer confirmation dramatically reduces false signals while maintaining sensitivity to genuine opportunities.
---
## 🚫 NO REPAINT GUARANTEE
**QMH is designed to be 100% repaint-free**, which is critical for honest backtesting and reliable live trading.
### Technical Implementation:
1. **All Multi-Timeframe Data Uses Confirmed Bars**
```pinescript
tf1_close = request.security(syminfo.tickerid, "15", close , lookahead=barmerge.lookahead_off)
```
Using `close ` instead of `close ` ensures we only reference the previous confirmed bar, not the current forming bar.
2. **Lookahead Prevention**
```pinescript
lookahead=barmerge.lookahead_off
```
This parameter prevents the function from accessing future data that wouldn't be available in real-time.
3. **Signal Timing**
Signals appear on the bar AFTER all conditions are met, not retroactively on the bar where conditions first appeared.
### What This Means for Users:
- **Backtest Accuracy**: Historical signals match exactly what you would have seen in real-time
- **No Disappearing Signals**: Once a signal appears, it stays (though price may move against it)
- **Honest Performance**: Results reflect true predictive power, not hindsight optimization
- **Live Trading Reliability**: Alerts fire at the same time signals appear on the chart
The dashboard displays "✓ NO REPAINT" to confirm this guarantee.
---
## 📖 HOW TO USE THIS INDICATOR
### Basic Trading Strategy
**For Trend Followers:**
1. **Wait for Signal Confirmation**
- QBUY label appears below a bar = Confirmed bullish entry opportunity
- QSELL label appears above a bar = Confirmed bearish entry opportunity
2. **Check Confidence Score**
- 60-70%: Moderate confidence (consider smaller position size)
- 70-85%: High confidence (standard position size)
- 85-100%: Very high confidence (consider larger position size)
3. **Enter Trade**
- Long entry: Market or limit order near signal bar
- Short entry: Market or limit order near signal bar
4. **Set Targets Using Probability Zones**
- Long trades: Target the adjusted upper zone (lime line)
- Short trades: Target the adjusted lower zone (red line)
- Alternatively, target the basis line (yellow) for conservative exits
5. **Set Stop Loss**
- Long trades: Below recent swing low minus 1 ATR
- Short trades: Above recent swing high plus 1 ATR
**For Mean Reversion Traders:**
1. **Wait for Extreme Zones**
- Price touches extreme lower zone (dotted red line below)
- Price touches extreme upper zone (dotted lime line above)
2. **Confirm with Psychology**
- At lower extreme: Look for Panic or Despair state
- At upper extreme: Look for Euphoria or Greed state
3. **Wait for Confidence Build**
- Monitor dashboard until confidence exceeds threshold
- Requires patience - extreme touches don't always reverse immediately
4. **Enter Reversal**
- Target: Return to basis line (yellow SMA 20)
- Stop: Beyond the extreme zone
**For Position Traders (Longer Timeframes):**
1. **Use Daily Timeframe**
- Set chart to daily for longer-term signals
- Signals will be less frequent but higher quality
2. **Require High Confidence**
- Filter setting: Min Confidence Score 80%+
- Only take the strongest multi-dimensional setups
3. **Confirm with Resonance Background**
- Green tinted background = All timeframes bullish aligned
- Red tinted background = All timeframes bearish aligned
- Only enter when background tint matches signal direction
4. **Hold for Major Targets**
- Long trades: Hold until extreme upper zone or opposite signal
- Short trades: Hold until extreme lower zone or opposite signal
---
## 📊 DASHBOARD INTERPRETATION
The QMH Dashboard (top-right corner) provides real-time market analysis across all four dimensions:
### Dashboard Elements:
1. **✓ NO REPAINT**
- Green confirmation that signals don't repaint
- Always visible to remind users of signal integrity
2. **SIGNAL: BULL/BEAR XX%**
- Shows dominant direction (whichever confidence is higher)
- Displays current confidence percentage
- Background color intensity reflects confidence level
3. **Psychology: **
- Current market emotional state
- Color coded:
- Orange = Euphoria (extreme bullish emotion)
- Yellow = Greed (moderate bullish emotion)
- Gray = Neutral (balanced state)
- Purple = Fear (uncertainty)
- Red = Panic (extreme bearish emotion)
- Dark red = Despair (capitulation)
4. **Resonance: **
- Multi-timeframe alignment strength
- Positive = All timeframes bullish aligned
- Negative = All timeframes bearish aligned
- Near zero = Timeframes not synchronized
- Emoji indicator: 🔥 (bullish resonance) ❄️ (bearish resonance)
5. **Intermarket: **
- Cross-asset pressure measurement
- Positive = BTC/DXY/VIX correlations supporting upside
- Negative = Correlations supporting downside
- Warning ⚠️ if correlation breakdown detected
6. **RSI: **
- Current RSI(14) reading
- Background colors: Red (>70 overbought), Green (<30 oversold)
- Status: OB (overbought), OS (oversold), or • (neutral)
7. **Status: READY BUY / READY SELL / WAIT**
- Quick trade readiness indicator
- READY BUY: Confidence ≥ threshold, bias bullish
- READY SELL: Confidence ≥ threshold, bias bearish
- WAIT: Confidence below threshold
### How to Use Dashboard:
**Before Entering a Trade:**
- Verify Status shows READY (not WAIT)
- Check that Resonance matches signal direction
- Confirm Psychology isn't contradicting (e.g., buying during Euphoria)
- Note Intermarket value - breakdowns (⚠️) suggest caution
**During a Trade:**
- Monitor Psychology shifts (e.g., from Fear to Greed in a long)
- Watch for Resonance changes that could signal exit
- Check for Intermarket breakdown warnings
---
## ⚙️ CUSTOMIZATION SETTINGS
### TFR Settings (Temporal Fractal Resonance)
- **Enable/Disable**: Turn TFR analysis on/off
- **Fractal Sensitivity** (5-50, default 14):
- Lower values = More responsive to short-term changes
- Higher values = More stable, slower to react
- Recommendation: 14 for balanced, 7 for scalping, 21 for position trading
### CAQE Settings (Cross-Asset Quantum Entanglement)
- **Enable/Disable**: Turn CAQE analysis on/off
- **Asset 1** (default BTC): Reference asset for correlation analysis
- **Asset 2** (default DXY): Second reference asset
- **Asset 3** (default VIX): Third reference asset
- **Correlation Length** (10-100, default 20):
- Lower values = More sensitive to recent correlation changes
- Higher values = More stable correlation measurements
- Recommendation: 20 for most assets, 50 for less volatile markets
### Psychology Settings (Adaptive Market Psychology Matrix)
- **Enable/Disable**: Turn AMPM analysis on/off
- **Volume Spike Threshold** (1.0-5.0x, default 2.0):
- Lower values = Detect smaller volume increases as spikes
- Higher values = Only flag major volume surges
- Recommendation: 2.0 for stocks, 1.5 for crypto
### Probability Settings (Time-Decay Probability Zones)
- **Enable/Disable**: Turn TDPZ visualization on/off
- **Probability Lookback** (20-200, default 50):
- Lower values = Zones adapt faster to recent price action
- Higher values = Zones based on longer statistical history
- Recommendation: 50 for most uses, 100 for position trading
### Filter Settings
- **Min Confidence Score** (40-95%, default 60%):
- Lower threshold = More signals, more false positives
- Higher threshold = Fewer signals, higher quality
- Recommendation: 60% for active trading, 75% for selective trading
### Visual Settings
- **Show Entry Signals**: Toggle QBUY/QSELL labels on chart
- **Show Probability Zones**: Toggle zone visualization
- **Show Psychology State**: Toggle dashboard display
---
## 🔔 ALERT CONFIGURATION
QMH includes four alert conditions that can be configured via TradingView's alert system:
### Available Alerts:
1. **Quantum Buy Signal**
- Fires when: Confirmed QBUY signal generates
- Message includes: Confidence percentage
- Use for: Entry notifications
2. **Quantum Sell Signal**
- Fires when: Confirmed QSELL signal generates
- Message includes: Confidence percentage
- Use for: Entry notifications or exit warnings
3. **Market Panic**
- Fires when: Psychology state reaches Panic
- Use for: Contrarian opportunity alerts
4. **Market Euphoria**
- Fires when: Psychology state reaches Euphoria
- Use for: Reversal warning alerts
### How to Set Alerts:
1. Right-click on chart → "Add Alert"
2. Condition: Select "Quantum Market Harmonics"
3. Choose alert type from dropdown
4. Configure expiration, frequency, and notification method
5. Create alert
**Recommendation**: Set alerts for Quantum Buy/Sell signals with "Once Per Bar Close" frequency to avoid intra-bar false triggers.
---
## 💡 BEST PRACTICES
### For All Users:
1. **Backtest First**
- Test on your specific market and timeframe before live trading
- Different assets may perform better with different confidence thresholds
- Verify that the No Repaint guarantee works as described
2. **Paper Trade**
- Practice with signals on a demo account first
- Understand typical signal frequency for your timeframe
- Get comfortable with the dashboard interpretation
3. **Risk Management**
- Never risk more than 1-2% of capital per trade
- Use proper stop losses (not just mental stops)
- Position size based on confidence score (larger size at higher confidence)
4. **Consider Context**
- QMH signals work best in clear trends or at extremes
- During tight consolidation, false signals increase
- Major news events can invalidate technical signals
### Optimal Use Cases:
**QMH Works Best When:**
- ✅ Markets are trending (up or down)
- ✅ Volatility is normal to elevated
- ✅ Price reaches probability zone extremes
- ✅ Multiple timeframes align
- ✅ Clear inter-market relationships exist
**QMH Is Less Effective When:**
- ❌ Extremely low volatility (zones contract too much)
- ❌ Sideways choppy markets (conflicting timeframes)
- ❌ Flash crashes or news events (correlations break down)
- ❌ Very illiquid assets (irregular price action)
### Session Considerations:
- **24/7 Markets (Crypto)**: Works on all sessions, but signals may be more reliable during high-volume periods (US/European trading hours)
- **Forex**: Best during London/New York overlap when volume is highest
- **Stocks**: Most reliable during regular trading hours (not pre-market/after-hours)
---
## ⚠️ LIMITATIONS AND RISKS
### This Indicator Cannot:
- **Predict Black Swan Events**: Sudden unexpected events invalidate technical analysis
- **Guarantee Profits**: No indicator is 100% accurate; losses will occur
- **Replace Risk Management**: Always use stop losses and proper position sizing
- **Account for Fundamental Changes**: Company news, economic data, etc. can override technical signals
- **Work in All Market Conditions**: Less effective during extreme low volatility or major news events
### Known Limitations:
1. **Multi-Timeframe Lag**: Uses confirmed bars (`close `), so signals appear one bar after conditions met
2. **Correlation Dependency**: CAQE requires sufficient history; may be less reliable on newly listed assets
3. **Computational Load**: Multiple `request.security()` calls may cause slower performance on older devices
4. **Repaint of Dashboard**: Dashboard updates every bar (by design), but signals themselves don't repaint
### Risk Warnings:
- Past performance doesn't guarantee future results
- Backtesting results may not reflect actual trading results due to slippage, commissions, and execution delays
- Different markets and timeframes may produce different results
- The indicator should be used as a tool, not as a standalone trading system
- Always combine with your own analysis, risk management, and trading plan
---
## 🎓 EDUCATIONAL CONCEPTS
This indicator synthesizes several established financial theories and technical analysis concepts:
### Academic Foundations:
1. **Fractal Market Hypothesis** (Edgar Peters)
- Markets exhibit self-similar patterns across time scales
- Implemented via multi-timeframe resonance analysis
2. **Behavioral Finance** (Kahneman & Tversky)
- Investor psychology drives market inefficiencies
- Implemented via market psychology state classification
3. **Intermarket Analysis** (John Murphy)
- Asset classes correlate and influence each other predictably
- Implemented via cross-asset correlation monitoring
4. **Mean Reversion** (Statistical Arbitrage)
- Prices tend to revert to statistical norms
- Implemented via probability zones and standard deviation bands
5. **Multi-Timeframe Analysis** (Technical Analysis Standard)
- Higher timeframe trends dominate lower timeframe noise
- Implemented via fractal resonance scoring
### Learning Resources:
To better understand the concepts behind QMH:
- Read "Intermarket Analysis" by John Murphy (for CAQE concepts)
- Study "Thinking, Fast and Slow" by Daniel Kahneman (for psychology concepts)
- Review "Fractal Market Analysis" by Edgar Peters (for TFR concepts)
- Learn about Bollinger Bands (for TDPZ foundation)
---
## 🔄 VERSION HISTORY AND UPDATES
**Current Version: 1.0**
This is the initial public release. Future updates will be published using TradingView's Update feature (not as separate publications). Planned improvements may include:
- Additional reference assets for CAQE
- Optional machine learning-based weight optimization
- Customizable psychology state definitions
- Alternative probability zone calculations
- Performance metrics tracking
Check the "Updates" tab on the script page for version history.
---
## 📞 SUPPORT AND FEEDBACK
### How to Get Help:
1. **Read This Description First**: Most questions are answered in the detailed sections above
2. **Check Comments**: Other users may have asked similar questions
3. **Post Comments**: For general questions visible to the community
4. **Use TradingView Messaging**: For private inquiries (if available)
### Providing Useful Feedback:
When reporting issues or suggesting improvements:
- Specify your asset, timeframe, and settings
- Include a screenshot if relevant
- Describe expected vs. actual behavior
- Check if issue persists with default settings
### Continuous Improvement:
This indicator will evolve based on user feedback and market testing. Constructive suggestions for improvements are always welcome.
---
## ⚖️ DISCLAIMER
This indicator is provided for **educational and informational purposes only**. It does **not constitute financial advice, investment advice, trading advice, or any other type of advice**.
**Important Disclaimers:**
- You should **not** rely solely on this indicator to make trading decisions
- Always conduct your own research and due diligence
- Past performance is not indicative of future results
- Trading and investing involve substantial risk of loss
- Only trade with capital you can afford to lose
- Consider consulting with a licensed financial advisor before trading
- The author is not responsible for any trading losses incurred using this indicator
**By using this indicator, you acknowledge:**
- You understand the risks of trading
- You take full responsibility for your trading decisions
- You will use proper risk management techniques
- You will not hold the author liable for any losses
---
## 🙏 ACKNOWLEDGMENTS
This indicator builds upon the collective knowledge of the technical analysis and trading community. While the specific implementation and combination are original, the underlying concepts draw from:
- The Pine Script community on TradingView
- Academic research in behavioral finance and market microstructure
- Classical technical analysis methods developed over decades
- Open-source indicators that demonstrate best practices in Pine Script coding
Special thanks to TradingView for providing the platform and Pine Script language that make indicators like this possible.
---
## 📚 ADDITIONAL RESOURCES
**Pine Script Documentation:**
- Official Pine Script Manual: www.tradingview.com
**Related Concepts to Study:**
- Multi-timeframe analysis techniques
- Correlation analysis in financial markets
- Behavioral finance principles
- Mean reversion strategies
- Bollinger Bands methodology
**Recommended TradingView Tools:**
- Strategy Tester: To backtest signal performance
- Bar Replay: To see how signals develop in real-time
- Alert System: To receive notifications of new signals
---
**Thank you for using Quantum Market Harmonics. Trade safely and responsibly.**
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
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What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
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Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
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Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
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TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
________________________________________
Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
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Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
MadTrend [InvestorUnknown]The MadTrend indicator is an experimental tool that combines the Median and Median Absolute Deviation (MAD) to generate signals, much like the popular Supertrend indicator. In addition to identifying Long and Short positions, MadTrend introduces RISK-ON and RISK-OFF states for each trade direction, providing traders with nuanced insights into market conditions.
Core Concepts
Median and Median Absolute Deviation (MAD)
Median: The middle value in a sorted list of numbers, offering a robust measure of central tendency less affected by outliers.
Median Absolute Deviation (MAD): Measures the average distance between each data point and the median, providing a robust estimation of volatility.
Supertrend-like Functionality
MadTrend utilizes the median and MAD in a manner similar to how Supertrend uses averages and volatility measures to determine trend direction and potential reversal points.
RISK-ON and RISK-OFF States
RISK-ON: Indicates favorable conditions for entering or holding a position in the current trend direction.
RISK-OFF: Suggests caution, signaling RISK-ON end and potential trend weakening or reversal.
Calculating MAD
The mad function calculates the median of the absolute deviations from the median, providing a robust measure of volatility.
// Function to calculate the Median Absolute Deviation (MAD)
mad(series float src, simple int length) =>
med = ta.median(src, length) // Calculate median
abs_deviations = math.abs(src - med) // Calculate absolute deviations from median
ta.median(abs_deviations, length) // Return the median of the absolute deviations
MADTrend Function
The MADTrend function calculates the median and MAD-based upper (med_p) and lower (med_m) bands. It determines the trend direction based on price crossing these bands.
MADTrend(series float src, simple int length, simple float mad_mult) =>
// Calculate MAD (volatility measure)
mad_value = mad(close, length)
// Calculate the MAD-based moving average by scaling the price data with MAD
median = ta.median(close, length)
med_p = median + (mad_value * mad_mult)
med_m = median - (mad_value * mad_mult)
var direction = 0
if ta.crossover(src, med_p)
direction := 1
else if ta.crossunder(src, med_m)
direction := -1
Trend Direction and Signals
Long Position (direction = 1): When the price crosses above the upper MAD band (med_p).
Short Position (direction = -1): When the price crosses below the lower MAD band (med_m).
RISK-ON: When the price moves further in the direction of the trend (beyond median +- MAD) after the initial signal.
RISK-OFF: When the price retraces towards the median, signaling potential weakening of the trend.
RISK-ON and RISK-OFF States
RISK-ON LONG: Price moves above the upper band after a Long signal, indicating strengthening bullish momentum.
RISK-OFF LONG: Price falls back below the upper band, suggesting potential weakness in the bullish trend.
RISK-ON SHORT: Price moves below the lower band after a Short signal, indicating strengthening bearish momentum.
RISK-OFF SHORT: Price rises back above the lower band, suggesting potential weakness in the bearish trend.
Picture below show example RISK-ON periods which can be identified by “cloud”
Note: Highlighted areas on the chart indicating RISK-ON and RISK-OFF periods for both Long and Short positions.
Implementation Details
Inputs and Parameters:
Source (input_src): The price data used for calculations (e.g., close, open, high, low).
Median Length (length): The number of periods over which the median and MAD are calculated.
MAD Multiplier (mad_mult): Determines the distance of the upper and lower bands from the median.
Calculations:
Median and MAD are recalculated each period based on the specified length.
Upper (med_p) and Lower (med_m) Bands are computed by adding and subtracting the scaled MAD from the median.
Visual representation of the indicator on a price chart:
Backtesting and Performance Metrics
The MadTrend indicator includes a Backtesting Mode with a performance metrics table to evaluate its effectiveness compared to a simple buy-and-hold strategy.
Equity Calculation:
Calculates the equity curve based on the signals generated by the indicator.
Performance Metrics:
Metrics such as Mean Returns, Standard Deviation, Sharpe Ratio, Sortino Ratio, and Omega Ratio are computed.
The metrics are displayed in a table for both the strategy and the buy-and-hold approach.
Note: Due to the use of labels and plot shapes, automatic chart scaling may not function ideally in Backtest Mode.
Alerts and Notifications
MadTrend provides alert conditions to notify traders of significant events:
Trend Change Alerts
RISK-ON and RISK-OFF Alerts - Provides real-time notifications about the RISK-ON and RISK-OFF states for proactive trade management.
Customization and Calibration
Default Settings: The provided default settings are experimental and not optimized. They serve as a starting point for users.
Parameter Adjustment: Traders are encouraged to calibrate the indicator's parameters (e.g., length, mad_mult) to suit their specific trading style and the characteristics of the asset being analyzed.
Source Input: The indicator allows for different price inputs (open, high, low, close, etc.), offering flexibility in how the median and MAD are calculated.
Important Notes
Market Conditions: The effectiveness of the MadTrend indicator can vary across different market conditions. Regular calibration is recommended.
Backtest Limitations: Backtesting results are historical and do not guarantee future performance.
Risk Management: Always apply sound risk management practices when using any trading indicator.
TrigWave Suite [InvestorUnknown]The TrigWave Suite combines Sine-weighted, Cosine-weighted, and Hyperbolic Tangent moving averages (HTMA) with a Directional Movement System (DMS) and a Relative Strength System (RSS).
Hyperbolic Tangent Moving Average (HTMA)
The HTMA smooths the price by applying a hyperbolic tangent transformation to the difference between the price and a simple moving average. It also adjusts this value by multiplying it by a standard deviation to create a more stable signal.
// Function to calculate Hyperbolic Tangent
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
// Function to calculate Hyperbolic Tangent Moving Average
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Sine-Weighted Moving Average (SWMA)
The SWMA applies sine-based weights to historical prices. This gives more weight to the central data points, making it responsive yet less prone to noise.
// Function to calculate the Sine-Weighted Moving Average
f_Sine_Weighted_MA(series float src, simple int length) =>
var float sine_weights = array.new_float(0)
array.clear(sine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights, weight)
// Normalize the weights
sum_weights = array.sum(sine_weights)
for i = 0 to length - 1
norm_weight = array.get(sine_weights, i) / sum_weights
array.set(sine_weights, i, norm_weight)
// Calculate Sine-Weighted Moving Average
swma = 0.0
if bar_index >= length
for i = 0 to length - 1
swma := swma + array.get(sine_weights, i) * src
swma
Cosine-Weighted Moving Average (CWMA)
The CWMA uses cosine-based weights for data points, which produces a more stable trend-following behavior, especially in low-volatility markets.
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * src
cwma
Directional Movement System (DMS)
DMS is used to identify trend direction and strength based on directional movement. It uses ADX to gauge trend strength and combines +DI and -DI for directional bias.
// Function to calculate Directional Movement System
f_DMS(simple int dmi_len, simple int adx_len) =>
up = ta.change(high)
down = -ta.change(low)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
trur = ta.rma(ta.tr, dmi_len)
plus = fixnan(100 * ta.rma(plusDM, dmi_len) / trur)
minus = fixnan(100 * ta.rma(minusDM, dmi_len) / trur)
sum = plus + minus
adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adx_len)
dms_up = plus > minus and adx > minus
dms_down = plus < minus and adx > plus
dms_neutral = not (dms_up or dms_down)
signal = dms_up ? 1 : dms_down ? -1 : 0
Relative Strength System (RSS)
RSS employs RSI and an adjustable moving average type (SMA, EMA, or HMA) to evaluate whether the market is in a bullish or bearish state.
// Function to calculate Relative Strength System
f_RSS(rsi_src, rsi_len, ma_type, ma_len) =>
rsi = ta.rsi(rsi_src, rsi_len)
ma = switch ma_type
"SMA" => ta.sma(rsi, ma_len)
"EMA" => ta.ema(rsi, ma_len)
"HMA" => ta.hma(rsi, ma_len)
signal = (rsi > ma and rsi > 50) ? 1 : (rsi < ma and rsi < 50) ? -1 : 0
ATR Adjustments
To minimize false signals, the HTMA, SWMA, and CWMA signals are adjusted with an Average True Range (ATR) filter:
// Calculate ATR adjusted components for HTMA, CWMA and SWMA
float atr = ta.atr(atr_len)
float htma_up = htma + (atr * atr_mult)
float htma_dn = htma - (atr * atr_mult)
float swma_up = swma + (atr * atr_mult)
float swma_dn = swma - (atr * atr_mult)
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
This adjustment allows for better adaptation to varying market volatility, making the signal more reliable.
Signals and Trend Calculation
The indicator generates a Trend Signal by aggregating the output from each component. Each component provides a directional signal that is combined to form a unified trend reading. The trend value is then converted into a long (1), short (-1), or neutral (0) state.
Backtesting Mode and Performance Metrics
The Backtesting Mode includes a performance metrics table that compares the Buy and Hold strategy with the TrigWave Suite strategy. Key statistics like Sharpe Ratio, Sortino Ratio, and Omega Ratio are displayed to help users assess performance. Note that due to labels and plotchar use, automatic scaling may not function ideally in backtest mode.
Alerts and Visualization
Trend Direction Alerts: Set up alerts for long and short signals
Color Bars and Gradient Option: Bars are colored based on the trend direction, with an optional gradient for smoother visual feedback.
Important Notes
Customization: Default settings are experimental and not intended for trading/investing purposes. Users are encouraged to adjust and calibrate the settings to optimize results according to their trading style.
Backtest Results Disclaimer: Please note that backtest results are not indicative of future performance, and no strategy guarantees success.
Z-Score Weighted Trend System I [InvestorUnknown]The Z-Score Weighted Trend System I is an advanced and experimental trading indicator designed to utilize a combination of slow and fast indicators for a comprehensive analysis of market trends. The system is designed to identify stable trends using slower indicators while capturing rapid market shifts through dynamically weighted fast indicators. The core of this indicator is the dynamic weighting mechanism that utilizes the Z-score of price , allowing the system to respond effectively to significant market movements.
Dynamic Z-Score-Based Weighting System
The Z-Score Weighted Trend System I utilizes the Z-score of price to assign weights dynamically to fast indicators. This mechanism is designed to capture rapid market shifts at potential turning points, providing timely entry and exit signals.
Traders can choose from two primary weighting mechanisms:
Threshold-Based Weighting: The fast indicators are given weight only when the absolute Z-score exceeds a user-defined threshold. Below this threshold, fast indicators have no impact on the final signal.
Continuous Weighting: By setting the threshold to zero, fast indicators always contribute to the final signal, regardless of Z-score levels. However, this increases the likelihood of false signals during ranging or low-volatility markets
// Calculate weight for Fast Indicators based on Z-Score (Slow Indicator weight is kept to 1 for simplicity)
f_zscore_weights(series float z, simple float weight_thre) =>
float fast_weight = na
float slow_weight = na
if weight_thre > 0
if math.abs(z) <= weight_thre
fast_weight := 0
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
Choice of Z-Score Normalization
Traders have the flexibility to select different Z-score processing methods to better suit their trading preferences:
Raw Z-Score or Moving Average: Traders can opt for either the raw Z-score or a moving average of the Z-score to smooth out fluctuations.
Normalized Z-Score (ranging from -1 to 1) or Z-Score Percentile: The normalized Z-score is simply the raw Z-score divided by 3, while the Z-score percentile utilizes a normal distribution for transformation.
f_zscore_perc(series float zscore_src, simple int zscore_len, simple string zscore_a, simple string zscore_b, simple string ma_type, simple int ma_len) =>
z = (zscore_src - ta.sma(zscore_src, zscore_len)) / ta.stdev(zscore_src, zscore_len)
zscore = switch zscore_a
"Z-Score" => z
"Z-Score MA" => ma_type == "EMA" ? (ta.ema(z, ma_len)) : (ta.sma(z, ma_len))
output = switch zscore_b
"Normalized Z-Score" => (zscore / 3) > 1 ? 1 : (zscore / 3) < -1 ? -1 : (zscore / 3)
"Z-Score Percentile" => (f_percentileFromZScore(zscore) - 0.5) * 2
output
Slow and Fast Indicators
The indicator uses a combination of slow and fast indicators:
Slow Indicators (constant weight) for stable trend identification: DMI (Directional Movement Index), CCI (Commodity Channel Index), Aroon
Fast Indicators (dynamic weight) to identify rapid trend shifts: ZLEMA (Zero-Lag Exponential Moving Average), IIRF (Infinite Impulse Response Filter)
Each indicator is calculated using for-loop methods to provide a smoothed and averaged view of price data over varying lengths, ensuring stability for slow indicators and responsiveness for fast indicators.
Signal Calculation
The final trading signal is determined by a weighted combination of both slow and fast indicators. The slow indicators provide a stable view of the trend, while the fast indicators offer agile responses to rapid market movements. The signal calculation takes into account the dynamic weighting of fast indicators based on the Z-score:
// Calculate Signal (as weighted average)
float sig = math.round(((DMI*slow_w) + (CCI*slow_w) + (Aroon*slow_w) + (ZLEMA*fast_w) + (IIRF*fast_w)) / (3*slow_w + 2*fast_w), 2)
Backtest Mode and Performance Metrics
The indicator features a detailed backtesting mode, allowing traders to compare the effectiveness of their selected settings against a traditional Buy & Hold strategy. The backtesting provides:
Equity calculation based on signals generated by the indicator.
Performance metrics comparing Buy & Hold metrics with the system’s signals, including: Mean, positive, and negative return percentages, Standard deviations, Sharpe, Sortino, and Omega Ratios
// Calculate Performance Metrics
f_PerformanceMetrics(series float base, int Lookback, simple float startDate, bool Annualize = true) =>
// Initialize variables for positive and negative returns
pos_sum = 0.0
neg_sum = 0.0
pos_count = 0
neg_count = 0
returns_sum = 0.0
returns_squared_sum = 0.0
pos_returns_squared_sum = 0.0
neg_returns_squared_sum = 0.0
// Loop through the past 'Lookback' bars to calculate sums and counts
if (time >= startDate)
for i = 0 to Lookback - 1
r = (base - base ) / base
returns_sum += r
returns_squared_sum += r * r
if r > 0
pos_sum += r
pos_count += 1
pos_returns_squared_sum += r * r
if r < 0
neg_sum += r
neg_count += 1
neg_returns_squared_sum += r * r
float export_array = array.new_float(12)
// Calculate means
mean_all = math.round((returns_sum / Lookback), 4)
mean_pos = math.round((pos_count != 0 ? pos_sum / pos_count : na), 4)
mean_neg = math.round((neg_count != 0 ? neg_sum / neg_count : na), 4)
// Calculate standard deviations
stddev_all = math.round((math.sqrt((returns_squared_sum - (returns_sum * returns_sum) / Lookback) / Lookback)) * 100, 2)
stddev_pos = math.round((pos_count != 0 ? math.sqrt((pos_returns_squared_sum - (pos_sum * pos_sum) / pos_count) / pos_count) : na) * 100, 2)
stddev_neg = math.round((neg_count != 0 ? math.sqrt((neg_returns_squared_sum - (neg_sum * neg_sum) / neg_count) / neg_count) : na) * 100, 2)
// Calculate probabilities
prob_pos = math.round((pos_count / Lookback) * 100, 2)
prob_neg = math.round((neg_count / Lookback) * 100, 2)
prob_neu = math.round(((Lookback - pos_count - neg_count) / Lookback) * 100, 2)
// Calculate ratios
sharpe_ratio = math.round((mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
sortino_ratio = math.round((mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
omega_ratio = math.round(pos_sum / math.abs(neg_sum), 2)
// Set values in the array
array.set(export_array, 0, mean_all), array.set(export_array, 1, mean_pos), array.set(export_array, 2, mean_neg),
array.set(export_array, 3, stddev_all), array.set(export_array, 4, stddev_pos), array.set(export_array, 5, stddev_neg),
array.set(export_array, 6, prob_pos), array.set(export_array, 7, prob_neu), array.set(export_array, 8, prob_neg),
array.set(export_array, 9, sharpe_ratio), array.set(export_array, 10, sortino_ratio), array.set(export_array, 11, omega_ratio)
// Export the array
export_array
//}
Calibration Mode
A Calibration Mode is included for traders to focus on individual indicators, helping them fine-tune their settings without the influence of other components. In Calibration Mode, the user can visualize each indicator separately, making it easier to adjust parameters.
Alerts
The indicator includes alerts for long and short signals when the indicator changes direction, allowing traders to set automated notifications for key market events.
// Alert Conditions
alertcondition(long_alert, "LONG (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬇Short⬇")
Important Note:
The default settings of this indicator are not optimized for any particular market condition. They are generic starting points for experimentation. Traders are encouraged to use the calibration tools and backtesting features to adjust the system to their specific trading needs.
The results generated from the backtest are purely historical and are not indicative of future results. Market conditions can change, and the performance of this system may differ under different circumstances. Traders and investors should exercise caution and conduct their own research before using this indicator for any trading decisions.
MACD_RSI_trend_followingINFO:
This indicator can be used to build-up a strategy for trading of assets which are currently in trending phase.
My preference is to use it on slowly moving assets like GOLD and on higher timeframes, but practice may show that we find more usefull cases.
This script uses two indicators - MACD and RSI, as the timeframe that those are extracted for is configurable (defaults with the Chart TF, but can be any other selected by the user).
The strategy has the following simple idea - buy if any if the conditions below is true:
The selected TF MACD line crosses above the signal line and the TF RSI is above the user selected trigger value
The selected TF MACD line is above the signal line and the TF RSI crosses above the user selected trigger value
Once we're in position we wait for the selected TF MACD line to cross below the signal line, and then we set a SL at the low of that bar
DETAILS and USAGE:
In the current implementation I find two possible use cases for the indicator:
as a stand-alone indicator on the chart which can also fire alerts that can help to determine if we want to manually enter/exit trades based on them
can be used to connect to the Signal input of the TTS (TempalteTradingStrategy) by jason5480 in order to backtest it, thus effectively turning it into a strategy (instructions below in TTS CONNECTIVITY section)
In the example below we see a position opened at the bar after the buy indicator from the script has been triggered, and then later after the SL indicator from the script has been triggered a SL has been set on the lower wick of the closing candle, and the position eventually got closed once the price hit that level. Note that most of the drawing on the example snapshot below are from the TTS indicator following the buy/sell/SL conditions themseves:
Trading period can be selected from the indicator itself to limit to more interesting periods.
Arrow indications are drawn on the chart to indicate the trading conditions met in the script - green arrow for a buy signal indication and orange for LTF crossunder to indicate setting of SL.
SETTINGS:
Leaving all of the settings as in vanilla use case, as both the MACD and RSI indicator's settings follow the default ones for the stand-alone indicators themselves.
The start-end date is a time filter that can be extermely usefull when backtesting different time periods.
Pesonal preference is using the script on a D/W timeframe, while the indicator is configured to use Monthly chart.
The default value of the RSI filter is left to 50, which can be changed. I.e. if the RSI is above 50 we have a regime filter based on the MACD criteria.
EXTERNAL LIBRARIES:
The script uses a couple of external libraries:
HeWhoMustNotBeNamed/enhanced_ta/14 - collection of TA indicators
jason5480/tts_convention/3 - more details about the Template Trading Strategy below
I would like to highly appreciate and credit the work of both HeWhoMustNotBeNamed and jason5480 for providing them to the community.
TTS SETTINGS (NEEDED IF USED TO BACKTEST WITH TTS):
The TempalteTradingStrategy is a strategy script developed in Pine by jason5480, which I recommend for quick turn-around of testing different ideas on a proven and tested framework
I cannot give enough credit to the developer for the efforts put in building of the infrastructure, so I advice everyone that wants to use it first to get familiar with the concept and by checking
by checking jason5480's profile www.tradingview.com
The TTS itself is extremely functional and have a lot of properties, so its functionality is beyond the scope of the current script -
Again, I strongly recommend to be thoroughly epxlored by everyone that plans on using it.
In the nutshell it is a script that can be feed with buy/sell signals from an external indicator script and based on many configuration options it can determine how to execute the trades.
The TTS has many settings that can be applied, so below I will cover only the ones that differ from the default ones, at least according to my testing - do your own research, you may find something even better :)
The current/latest version that I've been using as of writing and testing this script is TTSv48
Settings which differ from the default ones:
from - False (time filter is from the indicator script itself)
Deal Conditions Mode - External (take enter/exit conditions from an external script)
🔌Signal 🛈➡ - MACD_RSI_trend_following: 🔌Signal to TTSv48 (this is the output from the indicator script, according to the TTS convention)
Sat/Sun - true (for crypto, in order to trade 24/7)
Order Type - STOP (perform stop order)
Distance Method - HHLL (HigherHighLowerLow - in order to set the SL according to the strategy definition from above)
The next are just personal preferenes, you can feel free to experiment according to your trading style
Take Profit Targets - 0 (either 100% in or out, no incremental stepping in or out of positions)
Dist Mul|Len Long/Short- 10 (make sure that we don't close on profitable trades by any reason)
Quantity Method - EQUITY (personal backtesting preference is to consider each backtest as a separate portfolio, so determine the position size by 100% of the allocated equity size)
Equity % - 100 (note above)
Dual_MACD_trendingINFO:
This indicator is useful for trending assets, as my preference is for low-frequency trading, thus using BTCUSD on 1D/1W chart
In the current implementation I find two possible use cases for the indicator:
- as a stand-alone indicator on the chart which can also fire alerts that can help to determine if we want to manually enter/exit trades based on the signals from it (1D/1W is good for non-automated trading)
- can be used to connect to the Signal input of the TTS (TempalteTradingStrategy) by jason5480 in order to backtest it, thus effectively turning it into a strategy (instructions below in TTS CONNECTIVITY section)
Trading period can be selected from the indicator itself to limit to more interesting periods.
Arrow indications are drawn on the chart to indicate the trading conditions met in the script - light green for HTF crossover, dark green for LTF crossover and orange for LTF crossunder.
Note that the indicator performs best in trending assets and markets, and it is advisable to use additional indicators to filter the trading conditions when market/asset is expected to move sideways.
DETAILS:
It uses a couple of MACD indicators - one from the current timeframe and one from a higher timeframe, as the crossover/crossunder cases of the MACD line and the signal line indicate the potential entry/exit points.
The strategy has the following flow:
- If the weekly MACD is positive (MACD line is over the signal line) we have a trading window.
- If we have a trading window, we buy when the daily macd line crosses AND closes above the signal line.
- If we are in a position, we await the daily MACD to cross AND close under the signal line, and only then place a stop loss under the wick of that closing candle.
The user can select both the higher (HTF) and lower (LTF) timeframes. Preferably the lower timeframe should be the one that the Chart is on for better visualization.
If one to decide to use the indicator as a strategy, it implements the following buy and sell criterias, which are feed to the TTS, but can be also manually managed via adding alerts from this indicator.
Since usually the LTF is preceeding the crossover compared to the HTF, then my interpretation of the strategy and flow that it follows is allowing two different ways to enter a trade:
- crossover (and bar close) of the macd over the signal line in the HIGH TIMEFRAME (no need to look at the LOWER TIMEFRMAE)
- crossover (and bar close) of the macd over the signal line in the LOW TIMEFRAME, as in this case we need to check also that the macd line is over the signal line for the HIGH TIMEFRAME as well (like a regime filter)
The exit of the trade is based on the lower timeframe MACD only, as we create a stop loss equal to the lower wick of the bar, once the macd line crosses below the signal line on that timeframe
SETTINGS:
All of the indicator's settings are for the vanilla/general case.
User can set all of the MACD parameters for both the higher and lower (current) timeframes, currently left to default of the MACD stand-alone indicator itself.
The start-end date is a time filter that can be extermely usefull when backtesting different time periods.
TTS SETTINGS (NEEDED IF USED TO BACKTEST WITH TTS)
The TempalteTradingStrategy is a strategy script developed in Pine by jason5480, which I recommend for quick turn-around of testing different ideas on a proven and tested framework
I cannot give enough credit to the developer for the efforts put in building of the infrastructure, so I advice everyone that wants to use it first to get familiar with the concept and by checking
by checking jason5480's profile www.tradingview.com
The TTS itself is extremely functional and have a lot of properties, so its functionality is beyond the scope of the current script -
Again, I strongly recommend to be thoroughly epxlored by everyone that plans on using it.
In the nutshell it is a script that can be feed with buy/sell signals from an external indicator script and based on many configuration options it can determine how to execute the trades.
The TTS has many settings that can be applied, so below I will cover only the ones that differ from the default ones, at least according to my testing - do your own research, you may find something even better :)
The current/latest version that I've been using as of writing and testing this script is TTSv48
Settings which differ from the default ones:
- from - False (time filter is from the indicator script itself)
- Deal Conditions Mode - External (take enter/exit conditions from an external script)
- 🔌Signal 🛈➡ - Dual_MACD: 🔌Signal to TTSv48 (this is the output from the indicator script, according to the TTS convention)
- Sat/Sun - true (for crypto, in order to trade 24/7)
- Order Type - STOP (perform stop order)
- Distance Method - HHLL (HigherHighLowerLow - in order to set the SL according to the strategy definition from above)
The next are just personal preferenes, you can feel free to experiment according to your trading style
- Take Profit Targets - 0 (either 100% in or out, no incremental stepping in or out of positions)
- Dist Mul|Len Long/Short- 10 (make sure that we don't close on profitable trades by any reason)
- Quantity Method - EQUITY (personal backtesting preference is to consider each backtest as a separate portfolio, so determine the position size by 100% of the allocated equity size)
- Equity % - 100 (note above)
EXAMPLES:
If used as a stand-alone indicator, the green arrows on the bottom will represent:
- light green - MACD line crossover signal line in the HTF
- darker green - MACD line crossover signal line in the LTF
- orange - MACD line crossunder signal line in the LTF
I recommend enabling the alerts from the script to cover those cases.
If used as an input to the TTS, we'll get more decorations on the chart from the TTS itself.
In the example below we open a trade on the next day of LTF crossover, then a few days later a crossunder in the LTF occurs, so we set a SL at the low of the wick of this day. Few days later the price doesn't recover and hits that SL, so the position is closed.
Volatility Radar [upslidedown]💎 Overview
Volatility Radar visualizes extreme volatility conditions in a clean, intuitive oscillator format.
Unlike traditional momentum oscillators, it transforms average true range (ATR) behavior into a directional volatility structure, making it easier to spot moments when markets may be shifting into expansion, compression, or potential pivot zones.
💎 How to Use
The oscillator highlights moments when the internal volatility condition becomes active as well as when that condition breaks. These events may coincide with structural turning points, breakout conditions, or volatility expansions. While not a prediction tool, Volatility Radar helps traders identify moments worth paying closer attention to.
💎 Signal Markers
■ Square icons on top/bottom identify when the Volatility Radar condition is ACTIVE
▲▼ Triangle icons on top/bottom identify when the Volatility Radar condition BREAKS
📌 Chart Example:
💎 Oscillator Trends
One of the core features of Volatility Radar is its ability to highlight positive or negative volatility trends. The oscillator automatically colors its components to reflect uptrending vs. downtrending volatility structure, making trend context easier to interpret at a glance.
📌 Chart Example:
💎 Histogram Trends
For users who prefer a more compact or traditional visual style, Volatility Radar includes an optional histogram display mode. This mode provides a clean representation of the detected trend and can be helpful for validating price-action concepts within the broader volatility context.
📌 Chart Example:
💎 Volatility Moving Average
The yellow moving average line offers a volatility moving average that can aid in determining longer term trend strength.
Interpret the trend direction by observing whether the average is increasing/decreasing or above/below the zero line.
Reversals may be observed when values move into oversold territories.
Trend continuation may occur during periods when the average is near the zero line.
Evaluate opportunities when the moving average is "touched" or "pinged" by the radar line (setting available to highlight these crosses).
📌 Chart Example:
💎 Backtesting Support
Volatility Radar outputs external signals designed for use with automated backtesting on TradingView. It integrates with @jason5480’s open-source Template Trailing Strategy and its supporting signal libraries.
VIX Expected Daily Move [SPY/SPX] VIX Expected Daily Move Indicator
This indicator helps traders anticipate the expected daily trading range for the current chart's asset (e.g., SPY, ES, SPX) based on the CBOE Volatility Index (VIX), using the widely recognized "Rule of 16" method.
Key Features:
VIX-Based Range: Calculates the implied daily high and low targets by applying the formula:
$$\text{Expected Move} = \text{Open Price} \times \frac{\text{VIX}}{100} \times \frac{1}{\sqrt{252}}$$
(where $\sqrt{252} \approx 16$)
Anchor Time: The calculation is anchored to a user-defined time (default: market open at 09:30 Exchange Time) for reliable, non-repainting levels.
Persistent Levels: Levels are calculated once per day and plotted as lines and labels that persist and extend throughout the trading session.
Historical Backtesting: Includes an option to display the expected range for historical days, making it excellent for backtesting volatility strategies.
Customization: Easily adjust the VIX symbol, anchor time, and line colors/styles.
How to Use:
Set the VIX Symbol to your preferred volatility source (default: CBOE:VIX).
Set the Anchor Time to the market open or another time when you wish to lock in the day's expected volatility reading.
Use the plotted Expected High (red line) and Expected Low (green line) as potential support and resistance targets for intraday trading decisions.
Hammer Model [#]Hammer Model - HTF Candle Entry Model
Overview
The Hammer Model is a sophisticated technical indicator that identifies high-probability reversal setups based on Higher Timeframe (HTF) candlestick wick rejection patterns. Unlike traditional hammer pattern indicators that simply flag candle formations, this system provides a complete trading framework with precise entry zones, stop loss placement, and multiple take profit targets calculated using statistical projections.
What Makes This Different
Proprietary Signal Filtering: This indicator uses a proprietary algorithm that analyzes multiple market structure conditions to filter out low-quality hammer patterns. Only the highest-probability setups are displayed, significantly reducing false signals compared to standard pattern recognition tools.
Dynamic Quadrant Mapping: Rather than basic support/resistance levels, the system divides each qualified hammer candle into three distinct zones (Upper Wick, Body, and Lower Wick), with precise .25, .5, and .75 subdivision levels for granular entry and exit planning.
Multi-Standard Deviation Projections: The indicator automatically calculates TP1 and TP2 targets based on the wick's range, along with optional 1-4 standard deviation extension levels for position scaling and profit maximization.
How It Works
Signal Generation @ Candle Close/New Candle Open
The indicator monitors your chart for HTF candles that meet specific criteria:
Bullish Hammer: Lower wick must be significantly larger than the body
Bearish Hammer: Upper wick must be significantly larger than the body
When both wicks qualify, the indicator selects the larger wick as the primary signal, depending on conditions set.
Visual Components
Bullish Setups:
SL: Stop loss level (below lower wick)
ENTRY: Entry zone (candle body range)
.25/.5/.25: Wick quadrant levels for scaling entries
TP1/TP2: First and second take profit targets
1-4STDV: Advanced/Long Range Targets
Bearish Setups:
SL: Stop loss level (above upper wick)
ENTRY: Entry zone (candle body range)
.25/.5/.25: Wick quadrant levels for scaling entries
TP1/TP2: First and second take profit targets
1-4STDV: Advanced/Long Range Targets
HTF Candle Overlay (Optional):
Displays the actual HTF candle that generated the signal
Shows Open, High, Low, and Close lines for context
Trading the Signals
For Bullish Hammers (Long):
Entry is @ HTF Candle Close / New HTF Candle Open (or wait for a .25-.5 wick retrace)
Place stop loss at or 1 tick below the SL level (lower wick low)
Target TP1 (1x wick range above) and TP2 (2x wick range above) and STDV
Use .25/.5/.25 levels to scale into positions or manage partial exits
For Bearish Hammers (Short):
Entry is @ HTF Candle Close / New HTF Candle Open (or wait for a .25-.5 wick retrace)
Place stop loss at or above the SL level (upper wick high)
Target TP1 (1x wick range below) and TP2 (2x wick range below) and STDV
Use .25/.5/.25 levels to scale into positions or manage partial exits
Key Settings
Hammer Model Conditions
Bullish/Bearish: Toggle which direction setups to display
1-2STDV / 3-4STDV: Show extended projection levels
HTF Liquidity Sweep: Filter for setups that swept previous HTF highs/lows (proprietary)
Wick Size: Require larger wick-to-body ratio (1.75x vs 1x)
Time Filters: Isolate setups during specific trading sessions (NY AM/PM, Asia, London)
Hourly Filters: Target setups that form during specific hour segments (useful for lower timeframes)
Display Options
Show Recent Hammer Models: Limit how many setups display on chart (default: 4)
Unlimited: Show all historical setups
Candle Quadrants: Toggle .25, .5, .25 subdivision lines
HTF Candle Overlay: Display the actual HTF candle that generated the signal
Timeframes
1min chart → 15min HTF (scalping)
5min chart → 1H HTF (day trading)
15min chart → 4H HTF (swing trading)
1H chart → Daily HTF (position trading)
The indicator automatically selects appropriate HTF pairs
Why Closed Source
This indicator is closed source to protect proprietary filtering algorithms that determine which hammer patterns qualify as valid signals. These filters analyze specific market structure conditions, liquidity dynamics, and statistical thresholds that have been developed through extensive backtesting, data logging over 1 years time, and represent the core intellectual property of this system. The filtering methodology is what separates this from basic pattern recognition tools and delivers higher-probability setups. To learn how to learn more about this system see Author Notes.
Best Practices
Confluence: Use this indicator alongside trend analysis, key support/resistance levels, or volume profiles
Risk Management: The SL levels provide clear invalidation points - always honor them
Scaling: Use the quadrant levels (.25/.5/.25) to scale into positions rather than entering full size at once
Session Filters: Enable time filters to focus on setups during high-liquidity sessions
Backtesting: Review historical signals on your preferred instruments to understand typical behavior and win rates
Notes
The indicator displays a table in the top-right showing the current chart timeframe and HTF being analyzed
Only charts with sufficient historical data will display all past signals
The "Unlimited" option may cause performance issues on very low timeframes with extensive history
Disclaimer: This indicator is a tool for technical analysis and risk management education and does not guarantee profitable trades. Always practice proper risk management and position sizing. Past performance does not indicate future results
Smart Money Concepts [XoRonX]# Smart Money Concepts (SMC) - Advanced Trading Indicator
## 📊 Deskripsi
**Smart Money Concepts ** adalah indicator trading komprehensif yang menggabungkan konsep Smart Money Trading dengan berbagai alat teknikal analisis modern. Indicator ini dirancang untuk membantu trader mengidentifikasi pergerakan institusional (smart money), struktur pasar, zona supply/demand, dan berbagai sinyal trading penting.
Indicator ini mengintegrasikan multiple timeframe analysis, order blocks detection, fair value gaps, fibonacci retracement, volume profile, RSI multi-timeframe, dan moving averages dalam satu platform yang powerful dan mudah digunakan.
---
## 🎯 Fitur Utama
### 1. **Smart Money Structure**
- **Internal Structure** - Struktur pasar jangka pendek untuk entry presisi
- **Swing Structure** - Struktur pasar jangka panjang untuk trend analysis
- **BOS (Break of Structure)** - Konfirmasi kelanjutan trend
- **CHoCH (Change of Character)** - Deteksi potensi reversal
### 2. **Order Blocks**
- **Internal Order Blocks** - Zona demand/supply jangka pendek
- **Swing Order Blocks** - Zona demand/supply jangka panjang
- Filter otomatis berdasarkan volatilitas (ATR/Range)
- Mitigation tracking (High/Low atau Close)
- Customizable display (jumlah order blocks yang ditampilkan)
### 3. **Equal Highs & Equal Lows (EQH/EQL)**
- Deteksi otomatis equal highs/lows
- Indikasi liquidity zones
- Threshold adjustment untuk sensitivitas
- Visual lines dan labels
### 4. **Fair Value Gaps (FVG)**
- Multi-timeframe FVG detection
- Auto threshold filtering
- Bullish & Bearish FVG boxes
- Extension control
- Color customization
### 5. **Premium & Discount Zones**
- Premium Zone (75-100% dari range)
- Equilibrium Zone (47.5-52.5% dari range)
- Discount Zone (0-25% dari range)
- Auto-update berdasarkan swing high/low
### 6. **Fibonacci Retracement**
- **Equilibrium to Discount** - Fib dari EQ ke discount zone
- **Equilibrium to Premium** - Fib dari EQ ke premium zone
- **Discount to Premium** - Fib full range
- Reverse option
- Show/hide lines
- Custom colors
### 7. **Volume Profile (VRVP)**
- Visible Range Volume Profile
- Point of Control (POC)
- Value Area (70% volume)
- Auto-adjust rows
- Placement options (Left/Right)
- Width customization
### 8. **RSI Multi-Timeframe**
- Monitor 3 timeframes sekaligus
- Overbought/Oversold signals
- Visual table display
- Color-coded signals (Red OB, Green OS)
- Customizable position & size
### 9. **Moving Averages**
- 3 Moving Average lines
- Pilihan tipe: EMA, SMA, WMA
- Automatic/Manual period mode
- Individual color & width settings
- Cross alerts (MA vs MA, Price vs MA)
### 10. **Multi-Timeframe Levels**
- Support up to 5 different timeframes
- Previous high/low levels
- Custom line styles
- Color customization
### 11. **Candle Color**
- Color candles berdasarkan trend
- Bullish = Green, Bearish = Red
- Optional toggle
---
## 🛠️ Cara Penggunaan
### **A. Setup Awal**
1. **Tambahkan Indicator ke Chart**
- Buka TradingView
- Klik "Indicators" → "My Scripts" atau paste code
- Pilih "Smart Money Concepts "
2. **Pilih Mode Display**
- **Historical**: Tampilkan semua struktur (untuk backtesting)
- **Present**: Hanya tampilkan struktur terbaru (clean chart)
3. **Pilih Style**
- **Colored**: Warna berbeda untuk bullish/bearish
- **Monochrome**: Tema warna abu-abu
---
### **B. Penggunaan Fitur**
#### **1. Smart Money Structure**
**Internal Structure (Real-time):**
- ✅ Aktifkan "Show Internal Structure"
- Pilih tampilan: All, BOS only, atau CHoCH only
- Gunakan untuk entry timing presisi
- Filter confluence untuk mengurangi noise
**Swing Structure:**
- ✅ Aktifkan "Show Swing Structure"
- Pilih tampilan struktur bullish/bearish
- Adjust "Swings Length" (default: 50)
- Gunakan untuk konfirmasi trend utama
**Tips:**
- BOS = Konfirmasi trend continuation
- CHoCH = Warning untuk possible reversal
- Tunggu price retest ke order block setelah BOS
---
#### **2. Order Blocks**
**Setup:**
- ✅ Aktifkan Internal/Swing Order Blocks
- Set jumlah blocks yang ditampil (1-20)
- Pilih filter: ATR atau Cumulative Mean Range
- Pilih mitigation: Close atau High/Low
**Cara Trading:**
1. Tunggu BOS/CHoCH terbentuk
2. Identifikasi order block terdekat
3. Wait for price pullback ke order block
4. Entry saat price respek order block (rejection)
5. Stop loss di bawah/atas order block
6. Target: swing high/low berikutnya
**Color Code:**
- 🔵 Light Blue = Internal Bullish OB
- 🔴 Light Red = Internal Bearish OB
- 🔵 Dark Blue = Swing Bullish OB
- 🔴 Dark Red = Swing Bearish OB
---
#### **3. Equal Highs/Lows (EQH/EQL)**
**Setup:**
- ✅ Aktifkan "Equal High/Low"
- Set "Bars Confirmation" (default: 3)
- Adjust threshold (0-0.5, default: 0.1)
**Interpretasi:**
- EQH = Liquidity di atas, kemungkinan sweep lalu dump
- EQL = Liquidity di bawah, kemungkinan sweep lalu pump
- Biasanya smart money akan grab liquidity sebelum move besar
**Trading Strategy:**
- Wait for EQH/EQL formation
- Anticipate liquidity grab
- Entry setelah sweep dengan konfirmasi (order block, FVG, CHoCH)
---
#### **4. Fair Value Gaps (FVG)**
**Setup:**
- ✅ Aktifkan "Fair Value Gaps"
- Pilih timeframe (default: chart timeframe)
- Enable/disable auto threshold
- Set extension bars
**Cara Trading:**
1. Bullish FVG = Support zone untuk buy
2. Bearish FVG = Resistance zone untuk sell
3. Price tends to fill FVG (retest)
4. Entry saat price kembali ke FVG
5. Partial fill = valid, full fill = invalidated
**Tips:**
- FVG + Order Block = High probability setup
- Multi-timeframe FVG lebih kuat
- Unfilled FVG = strong momentum
---
#### **5. Premium & Discount Zones**
**Setup:**
- ✅ Aktifkan "Premium/Discount Zones"
- Zones akan auto-update berdasarkan swing high/low
**Interpretasi:**
- 🟢 **Discount Zone** = Area BUY (price murah)
- ⚪ **Equilibrium** = Neutral (50%)
- 🔴 **Premium Zone** = Area SELL (price mahal)
**Trading Strategy:**
- BUY dari discount zone
- SELL dari premium zone
- Avoid trading di equilibrium
- Combine dengan structure confirmation
---
#### **6. Fibonacci Retracement**
**Setup:**
- Pilih Fib yang ingin ditampilkan:
- Equilibrium to Discount
- Equilibrium to Premium
- Discount to Premium
- Toggle show lines
- Enable reverse jika perlu
- Custom colors
**Key Levels:**
- 0.236 = Shallow retracement
- 0.382 = Common retracement
- 0.5 = 50% golden level
- 0.618 = Golden ratio (penting!)
- 0.786 = Deep retracement
**Cara Pakai:**
- 0.618-0.786 = Ideal entry zone dalam trend
- Combine dengan order blocks
- Wait for confirmation candle
---
#### **7. Volume Profile (VRVP)**
**Setup:**
- ✅ Aktifkan "Show Volume Profile"
- Set jumlah rows (10-100)
- Adjust width (5-50%)
- Pilih placement (Left/Right)
- Enable POC dan Value Area
**Interpretasi:**
- **POC (Point of Control)** = Harga dengan volume tertinggi = magnet
- **Value Area** = 70% volume = fair price range
- **Low Volume Nodes** = Weak support/resistance
- **High Volume Nodes** = Strong support/resistance
**Trading:**
- POC acts as support/resistance
- Price tends to return to POC
- Breakout dari Value Area = momentum
---
#### **8. RSI Multi-Timeframe**
**Setup:**
- ✅ Aktifkan "Show RSI Table"
- Set 3 timeframes (default: chart, 5m, 15m)
- Set RSI period (default: 14)
- Set Overbought level (default: 70)
- Set Oversold level (default: 30)
- Pilih posisi & ukuran table
**Interpretasi:**
- 🟢 **OS (Oversold)** = RSI ≤ 30 = Kondisi jenuh jual
- 🔴 **OB (Overbought)** = RSI ≥ 70 = Kondisi jenuh beli
- **-** = Neutral zone
**Trading Strategy:**
1. Multi-timeframe alignment = strong signal
2. OS + Bullish structure = BUY signal
3. OB + Bearish structure = SELL signal
4. Divergence RSI vs Price = reversal warning
**Contoh:**
- TF1: OS, TF2: OS, TF3: OS + Price di discount zone = STRONG BUY
---
#### **9. Moving Averages**
**Setup:**
- Pilih MA Type: EMA, SMA, atau WMA (berlaku untuk ketiga MA)
- Pilih Period Mode: Automatic atau Manual
- Set period untuk MA 1, 2, 3 (default: 20, 50, 100)
- Custom color & width per MA
- ✅ Enable Cross Alerts
**Interpretasi:**
- **Golden Cross** = MA fast cross above MA slow = Bullish
- **Death Cross** = MA fast cross below MA slow = Bearish
- Price above all MAs = Strong uptrend
- Price below all MAs = Strong downtrend
**Trading Strategy:**
1. MA1 (20) = Short-term trend
2. MA2 (50) = Medium-term trend
3. MA3 (100) = Long-term trend
**Entry Signals:**
- Price bounce dari MA dalam trend = continuation
- MA cross dengan konfirmasi structure = entry
- Multiple MA confluence = strong support/resistance
**Alerts Available:**
- MA1 cross MA2/MA3
- MA2 cross MA3
- Price cross any MA
---
#### **10. Multi-Timeframe Levels**
**Setup:**
- Enable HTF Level 1-5
- Set timeframes (contoh: 5m, 1H, 4H, D, W)
- Pilih line style (solid/dashed/dotted)
- Custom colors
**Cara Pakai:**
- Previous high/low dari HTF = strong S/R
- Breakout HTF level = significant move
- Multiple HTF levels confluence = major zone
---
### **C. Trading Setup Combination**
#### **Setup 1: High Probability Buy (Bullish)**
1. ✅ Swing structure: Bullish BOS
2. ✅ Price di Discount Zone
3. ✅ Pullback ke Bullish Order Block
4. ✅ Bullish FVG di bawah
5. ✅ RSI Multi-TF: Oversold
6. ✅ Price bounce dari MA
7. ✅ POC/Value Area support
8. ✅ Fibonacci 0.618-0.786 retracement
**Entry:** Saat price reject dari order block dengan confirmation candle
**Stop Loss:** Below order block
**Target:** Swing high atau premium zone
---
#### **Setup 2: High Probability Sell (Bearish)**
1. ✅ Swing structure: Bearish BOS
2. ✅ Price di Premium Zone
3. ✅ Pullback ke Bearish Order Block
4. ✅ Bearish FVG di atas
5. ✅ RSI Multi-TF: Overbought
6. ✅ Price reject dari MA
7. ✅ POC/Value Area resistance
8. ✅ Fibonacci 0.618-0.786 retracement
**Entry:** Saat price reject dari order block dengan confirmation candle
**Stop Loss:** Above order block
**Target:** Swing low atau discount zone
---
#### **Setup 3: Liquidity Grab (EQH/EQL)**
1. ✅ Identifikasi EQH atau EQL
2. ✅ Wait for liquidity sweep
3. ✅ Konfirmasi dengan CHoCH
4. ✅ Order block terbentuk setelah sweep
5. ✅ Entry saat retest order block
---
### **D. Tips & Best Practices**
**Risk Management:**
- Selalu gunakan stop loss
- Risk 1-2% per trade
- Risk:Reward minimum 1:2
- Jangan over-leverage
**Confluence adalah Kunci:**
- Minimal 3-4 konfirmasi sebelum entry
- Lebih banyak konfirmasi = higher probability
- Quality over quantity
**Timeframe Analysis:**
- HTF (Higher Timeframe) = Trend direction
- LTF (Lower Timeframe) = Entry timing
- Align dengan HTF trend
**Backtesting:**
- Gunakan mode "Historical"
- Test strategy di berbagai market condition
- Record dan analyze hasil
**Market Condition:**
- Trending market = Follow BOS, use order blocks
- Ranging market = Use premium/discount zones, EQH/EQL
- High volatility = Wider stops, wait for clear structure
**Avoid:**
- Trading di equilibrium zone
- Entry tanpa konfirmasi
- Fighting the trend
- Overleveraging
- Emotional trading
---
## 📈 Recommended Settings
### **For Scalping (1m - 5m):**
- Internal Structure: ON
- Swing Structure: OFF
- Order Blocks: Internal only
- RSI Timeframes: 1m, 5m, 15m
- MA Periods: 9, 21, 50
### **For Day Trading (15m - 1H):**
- Internal Structure: ON
- Swing Structure: ON
- Order Blocks: Both
- RSI Timeframes: 15m, 1H, 4H
- MA Periods: 20, 50, 100
### **For Swing Trading (4H - D):**
- Internal Structure: OFF
- Swing Structure: ON
- Order Blocks: Swing only
- RSI Timeframes: 4H, D, W
- MA Periods: 20, 50, 200
---
## ⚠️ Disclaimer
Indicator ini adalah alat bantu analisis teknikal. Tidak ada indicator yang 100% akurat. Selalu:
- Lakukan analisa fundamental
- Gunakan proper risk management
- Praktik di demo account terlebih dahulu
- Trading memiliki resiko, trade at your own risk
---
## 📝 Version Info
**Version:** 5.0
**Platform:** TradingView Pine Script v5
**Author:** XoRonX
**Max Labels:** 500
**Max Lines:** 500
**Max Boxes:** 500
---
## 🔄 Updates & Support
Untuk update, bug reports, atau pertanyaan:
- Check documentation regularly
- Test new features in replay mode
- Backup your settings before updates
---
## 🎓 Learning Resources
**Recommended Study:**
1. Smart Money Concepts (SMC) basics
2. Order blocks theory
3. Liquidity concepts
4. ICT (Inner Circle Trader) concepts
5. Volume profile analysis
6. Multi-timeframe analysis
**Practice:**
- Start with higher timeframes
- Master one concept at a time
- Keep a trading journal
- Review your trades weekly
---
**Happy Trading! 🚀📊**
_Remember: The best indicator is your own analysis and discipline._
Position Size & Drawdown ManagerThis tool is designed to help traders dynamically adjust their position size and drawdown expectations as their trading capital changes over time. It provides a simple and intuitive way to translate backtest results into real-world position sizing decisions.
Purpose and Functionality
The indicator uses your original backtest parameters — including base capital, base drawdown percentage, and base position size — and your current account balance to calculate how your risk profile changes. It presents two main scenarios:
Lock Drawdown %: Keeps your original drawdown percentage fixed and calculates the new position size required.
Lock Position Size: Keeps your position size unchanged and shows how your drawdown percentage will shift.
Why it’s useful
Many traders face the challenge of scaling their strategies as their account grows or shrinks. This tool makes it easy to visualize the relationship between position sizing, capital, and drawdown. It’s particularly valuable for risk management, portfolio rebalancing, and maintaining consistent exposure when transitioning from backtest conditions to live trading.
How it works
The calculations are displayed in a clean, color-coded table that updates dynamically. This allows you to instantly see how capital fluctuations impact your expected drawdown or position size. You can toggle between light and dark themes and highlight important cells for clarity.
Practical use case
Combine this tool with your TradingView strategy results to better interpret your backtests and adjust your real-world trade sizes accordingly. It bridges the gap between simulated performance and actual account management.
Chart example
The chart included focuses only on this indicator, showing the output table and visual layout clearly without additional scripts or overlays.
