MACDouble + RSI (rec. 15min-2hr intrv) Uses two sets of MACD plus an RSI to either long or short. All three indicators trigger buy/sell as one (ie it's not 'IF MACD1 OR MACD2 OR RSI > 1 = buy", its more like "IF 1 AND 2 AND RSI=buy", all 3 match required for trigger)
The MACD inputs should be tweaked depending on timeframe and what you are trading. If you are doing 1, 3, 5 min or real frequent trading then 21/44/20 and 32/66/29 or other high value MACDs should be considered. If you are doing longer intervals like 2, 3, 4hr then consider 9/19/9 and 21/44/20 for MACDs (experiment! I picked these example #s randomly).
Ideal usage for the MACD sets is to have MACD2 inputs at around 1.5x, 2x, or 3x MACD1's inputs.
Other settings to consider: try having fastlength1=macdlength1 and then (fastlength2 = macdlength2 - 2). Like 10/26/10 and 23/48/20. This seems to increase net profit since it is more likely to trigger before major price moves, but may decrease profitable trade %. Conversely, consider FL1=MCDL1 and FL2 = MCDL2 + (FL2 * 0.5). Example: 10/26/10 and 22/48/30 this can increase profitable trade %, though may cost some net profit.
Feel free to message me with suggestions or questions.
Cari skrip untuk "a股近10年第二天溢价的股票"
Kay_BBandsV3This is the 3rd version of Kay_BBands.
When +DI (Directional Index ) is above -DI , then Upper band will be visible and vice-versa.
This is when the ADX is above the threshold. 28 is the default in this version. I found its more appealing in 5M time frame.
BLUE - ADX under 10
GREEN - Uptrend, ADX over 10
RED - Downtrend, ADX over 10
Use it with another band with setting 20, 0.6 deviation. Prices keeping above or below the 2nd bands upper or lower bounds shows trending conditions.
I didn't know how to update the old script so published it again.
Changes - :
1) Updated default settings for the indicator
2) ADX setting are now DI (28), ADX (10), adx level to check is 10.
3) IMPORTANT one - When DI is up/down, lower/upper band will also have color (more visible that way.)
Play around the settings.. It really eliminates extra indicator checking visually... Please like if you think idea is good.
CM Renko Overlay BarsCM_Renko Overlay Bars V1
Overlays Renko Bars on Regular Price Bars.
Default Renko plot is based on Average True Range. Look Back period adjustable in Inputs Tab.
If you Choose to use "Traditional" Renko bars and pick the Size of the Renko Bars the please read below.
Value in Input Tab is multiplied by .001 (To work on Forex)
1 = 10 pips on EURUSD - 1 X .001 = .001 or 10 Pips
10 = .01 or 100 Pips
1000 = 1 point to the left of decimal. 1 Point in Stocks etc.
10000 = 10 Points on Stocks etc.
***V2 will fix this issue.
Custom Indicator - No Trade Zone Warning Back Ground Highlights!Years ago I did an analysis of my trades. Every period of the day was profitable except for two. From 10:00-1030, and 1:00 to 1:30. (I was actively Day Trading Futures) Imagine a vertical graph broken down in to 30 minute time segments. I had nice Green bars in every time slot (Showing Net Profits), and HUGE Red Bars from 10 to 10:30 and 1 to 1:30. After analysis I found I made consistent profits at session open, but then I would enter in to bad setups around 10 to make more money. I also found after I took lunch when I came back at 1:00 I would force trades instead of patiently waiting for a great trade setup. I created an indicator that plotted a red background around those times telling me I was not allowed to enter a trade. Profits went up!!! Details on How to adjust times are in 1st Post. You can adjust times and colors to meet your own trading needs.
Dual FUT/Spot price with next monthly expiryThis Pine Script dashboard indicator is specifically designed for pair trading strategies in Indian futures markets (NSE). Let me break down how it facilitates pair trading:
Core Pair Trading Concept
The script monitors two correlated stocks simultaneously (Symbol A and Symbol B), comparing their:
Spot prices vs Futures prices
Current month futures vs Next month futures
Premium/discount relationships
Key Pair Trading Features
1. Dual Symbol Monitoring
symbolA = "NSE:TCS" (Default)
symbolB = "NSE:INFY" (Default)
Allows traders to watch two stocks in the same sector (like TCS and Infosys in IT) to identify relative value opportunities.
2. Basis Analysis for Each Stock
The indicator calculates the basis (difference between futures and spot):
Price Difference: FUT - SPOT
Premium/Discount %: ((FUT - SPOT) / SPOT) × 100
This helps identify when one stock's futures are relatively more expensive than the other's.
3. Multi-Expiry View
Near Month Futures (1!): Current active contract
Next Month Futures (2!): Upcoming contract
This enables calendar spread analysis within each stock and helps anticipate rollover effects.
4. Comparative Table
The detailed table displays side-by-side:
Symbol Spot Price Near Future Near Diff (%)Next Monthly Next Diff (%)Lot SizeTCS₹3,500₹3,520+20 (+0.57%)₹3,535+35 (+1.00%)125INFY₹1,450₹1,455+5 (+0.34%)₹1,460+10 (+0.69%)600
5. Lot Size Integration
Critical for position sizing in pair trades - the indicator fetches actual contract lot sizes, enabling proper hedge ratio calculations.
Pair Trading Strategies Enabled
Strategy 1: Basis Divergence Trading
When TCS futures trade at +0.8% premium and INFY at +0.2%
Trade: Short TCS futures, Long INFY futures (betting on convergence)
The indicator highlights these differences with color-coded cells
Strategy 2: Calendar Spread Arbitrage
Compare near month vs next month premium for each stock
If TCS shows wider calendar spread than INFY, potential arbitrage exists
Trade the relative calendar spread difference
Strategy 3: Premium/Discount Reversal
Monitor which stock moves from premium to discount (or vice versa)
Color indicators (green/red) make this immediately visible
Enter pairs when relative premium relationships normalize
Strategy 4: Lot-Adjusted Pair Trading
Use lot size data to create market-neutral positions
Example: If TCS lot = 125 and INFY lot = 600
Ratio = 600/125 = 4.8:1 for rupee-neutral positioning
Visual Trading Cues
Green cells: Futures at premium (contango)
Red cells: Futures at discount (backwardation)
Purple values: Next month contracts
Yellow highlights: Spot prices
Practical Pair Trading Example
Scenario: Both stocks in same sector, historically correlated
Normal state: Both show +0.5% premium
Divergence: TCS jumps to +1.2%, INFY stays at +0.5%
Trade Signal:
Short TCS futures (expensive)
Long INFY futures (relatively cheap)
Exit: When premiums converge back to similar levels
Hedge ratio: Use lot sizes to maintain proper exposure balance
Advantages for Pair Traders
✓ Single-screen monitoring of both legs
✓ Real-time basis calculations eliminate manual math
✓ Multi-timeframe view (near + next month)
✓ Automatic lot size fetching for position sizing
✓ Visual alerts through color coding
✓ Percentage normalization for easy comparison
This indicator essentially transforms raw price data into actionable pair trading intelligence by highlighting relative value discrepancies between correlated assets in the futures market.
Enjoy!!
Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide
Introduction to Correlation Analysis
What is Correlation?
Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor.
Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed
Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions
Zero Correlation (0): The dancers move completely independently of each other
In financial markets, correlation helps us understand relationships between different assets, which is crucial for:
Portfolio diversification
Risk management
Pairs trading strategies
Hedging positions
Market analysis
Why This Script is Special
This script goes beyond simple correlation calculations by providing:
Two different correlation methods (Pearson and Spearman)
Statistical significance testing to ensure results are meaningful
Rolling correlation analysis to track how relationships change over time
Visual representation for easy interpretation
Comprehensive statistics table with detailed metrics
Deep Dive into the Script's Components
1. Input Parameters Explained-
Symbol Selection:
This allows you to select the second asset to compare with the chart's primary asset
Default is Apple (NASDAQ:AAPL), but you can change this to any symbol
Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated
Correlation Window (60): This is the number of periods used to calculate the main correlation
Larger values (e.g., 100-500) provide more stable, long-term correlation measures
Smaller values (e.g., 10-50) are more responsive to recent price movements
60 is a good balance for most daily charts (about 3 months of trading days)
Rolling Correlation Window (20): A shorter window to detect recent changes in correlation
This helps identify when the relationship between assets is strengthening or weakening
Default of 20 is roughly one month of trading days
Return Type: This determines how price changes are calculated
Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price
Easy to understand: "The asset went up 2% today"
Log Returns: Natural logarithm of (Today's Price / Yesterday's Price)
More mathematically elegant for statistical analysis
Better for time-additive properties (returns over multiple periods)
Less sensitive to extreme values.
Confidence Level (95%): This determines how certain we want to be about our results
95% confidence means we accept a 5% chance of being wrong (false positive)
Higher confidence (e.g., 99%) makes the test more strict
Lower confidence (e.g., 90%) makes the test more lenient
95% is the standard in most scientific research
Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance.
Display options control what you see on the chart:
Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off
Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues)
Show Statistical Tests: Enables the detailed statistics table
Table Text Size: Adjusts the size of text in the statistics table
2.Functions explained-
calcReturns():
This function calculates price returns based on your selected method:
Log Returns:
Formula: ln(Price_t / Price_t-1)
Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995%
Benefits: More symmetric, time-additive, and better for statistical modeling
Simple Returns:
Formula: (Price_t - Price_t-1) / Price_t-1
Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1%
Benefits: More intuitive and easier to understand
rankArray():
This function calculates the rank of each value in an array, which is used for Spearman correlation:
How ranking works:
The smallest value gets rank 1
The second smallest gets rank 2, and so on
For ties (equal values), they get the average of their ranks
Example: For values
Sorted:
Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5)
Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships.
pearsonCorr():
This function calculates the Pearson correlation coefficient:
Mathematical Formula:
r = (nΣxy - ΣxΣy) / √
Where x and y are the two variables, and n is the sample size
What it measures:
The strength and direction of the linear relationship between two variables
Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship)
0 indicates no linear relationship
Example:
If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship
When one stock goes up, the other tends to go up in a fairly consistent proportion
spearmanCorr():
This function calculates the Spearman rank correlation:
How it works:
Convert each value in both datasets to its rank
Calculate the Pearson correlation on the ranks instead of the original values
What it measures:
The strength and direction of the monotonic relationship between two variables
A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases
It doesn't require the relationship to be linear
When to use it instead of Pearson:
When the relationship is monotonic but not linear
When there are significant outliers in the data
When the data is ordinal (ranked) rather than interval/ratio
Example:
If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship
When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship
tStatistic():
This function calculates the t-statistic for correlation:
Mathematical Formula: t = r × √((n-2)/(1-r²))
Where r is the correlation coefficient and n is the sample size
What it measures:
How many standard errors the correlation is away from zero
Used to test the null hypothesis that the true correlation is zero
Interpretation:
Larger absolute t-values indicate stronger evidence against the null hypothesis
Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level
criticalT() and pValue():
These functions provide approximations for statistical significance testing:
criticalT():
Returns the critical t-value for a given degrees of freedom (df) and significance level
The critical value is the threshold that the t-statistic must exceed to be considered statistically significant
Uses approximations since Pine Script doesn't have built-in statistical distribution functions
pValue():
Estimates the p-value for a given t-statistic and degrees of freedom
The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero
Smaller p-values indicate stronger evidence against the null hypothesis
Standard interpretation:
p < 0.01: Very strong evidence (marked with **)
p < 0.05: Strong evidence (marked with *)
p ≥ 0.05: Weak evidence, not statistically significant
stdev():
This function calculates the standard deviation of a dataset:
Mathematical Formula: σ = √(Σ(x-μ)²/(n-1))
Where x is each value, μ is the mean, and n is the sample size
What it measures:
The amount of variation or dispersion in a set of values
A low standard deviation indicates that the values tend to be close to the mean
A high standard deviation indicates that the values are spread out over a wider range
Why it matters for correlation:
Standard deviation is used in calculating the correlation coefficient
It also provides information about the volatility of each asset's returns
Comparing standard deviations helps understand the relative riskiness of the two assets.
3.Getting Price Data-
price1: The closing price of the primary asset (the chart you're viewing)
price2: The closing price of the secondary asset (the one you selected in the input parameters)
Returns are used instead of raw prices because:
Returns are typically stationary (mean and variance stay constant over time)
Returns normalize for price levels, allowing comparison between assets of different values
Returns represent what investors actually care about: percentage changes in value
4.Information Table-
Creates a table to display statistics
Only shows on the last bar to avoid performance issues
Positioned in the top right of the chart
Has 2 columns and 15 rows
Populating the Table
The script then populates the table with various statistics:
Header Row: "Metric" and "Value"
Sample Information: Sample size and return type
Pearson Correlation: Value, t-statistic, p-value, and significance
Spearman Correlation: Value, t-statistic, p-value, and significance
Rolling Correlation: Current value
Standard Deviations: For both assets
Interpretation: Text description of the correlation strength
The table uses color coding to highlight important information:
Green for significant positive results
Red for significant negative results
Yellow for borderline significance
Color-coded headers for each section
=> Practical Applications and Interpretation
How to Interpret the Results
Correlation Strength
0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation
The assets move mostly independently of each other
Good for diversification purposes
0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation
The assets show some tendency to move together (or in opposite directions)
May be useful for certain trading strategies but not extremely reliable
0.7 to 1.0 (or -0.7 to -1.0): Strong correlation
The assets show a strong tendency to move together (or in opposite directions)
Can be useful for pairs trading, hedging, or as a market indicator
Statistical Significance
p < 0.01: Very strong evidence that the correlation is real
Marked with ** in the table
Very unlikely to be due to random chance
p < 0.05: Strong evidence that the correlation is real
Marked with * in the table
Unlikely to be due to random chance
p ≥ 0.05: Weak evidence that the correlation is real
Not marked in the table
Could easily be due to random chance
Rolling Correlation
The rolling correlation shows how the relationship between assets changes over time
If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing
This can indicate:
A shift in market regime
Changing fundamentals of one or both assets
Temporary market dislocations that might present trading opportunities
Trading Applications
1. Portfolio Diversification
Goal: Reduce overall portfolio risk by combining assets that don't move together
Strategy: Look for assets with low or negative correlations
Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech
2. Pairs Trading
Goal: Profit from the relative price movements of two correlated assets
Strategy:
Find two assets with strong historical correlation
When their prices diverge (one goes up while the other goes down)
Buy the underperforming asset and short the outperforming asset
Close the positions when they converge back to their normal relationship
Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi
3. Hedging
Goal: Reduce risk by taking an offsetting position in a negatively correlated asset
Strategy: Find assets that tend to move in opposite directions
Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall
4. Market Analysis
Goal: Understand market dynamics and interrelationships
Strategy: Analyze correlations between different sectors or asset classes
Example:
If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other
If the correlation between stocks and bonds changes, it might signal a shift in market expectations
5. Risk Management
Goal: Understand and manage portfolio risk
Strategy: Monitor correlations to identify when diversification benefits might be breaking down
Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits
Advanced Interpretation and Caveats
Correlation vs. Causation
Important Note: Correlation does not imply causation
Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other
Implication: Just because two assets move together doesn't mean one causes the other to move
Solution: Look for fundamental economic reasons why assets might be correlated
Non-Stationary Correlations
Problem: Correlations between assets can change over time
Causes:
Changing market conditions
Shifts in monetary policy
Structural changes in the economy
Changes in the underlying businesses
Solution: Use rolling correlations to monitor how relationships change over time
Outliers and Extreme Events
Problem: Extreme market events can distort correlation measurements
Example: During a market crash, many assets may move in the same direction regardless of their normal relationship
Solution:
Use Spearman correlation, which is less sensitive to outliers
Be cautious when interpreting correlations during extreme market conditions
Sample Size Considerations
Problem: Small sample sizes can produce unreliable correlation estimates
Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results
Solution:
Use the default correlation length of 60 or higher
Be skeptical of correlations calculated with small samples
Timeframe Considerations
Problem: Correlations can vary across different timeframes
Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis
Solution:
Test correlations on multiple timeframes
Use the timeframe that matches your trading horizon
Look-Ahead Bias
Problem: Using information that wouldn't have been available at the time of trading
Example: Calculating correlation using future data
Solution: This script avoids look-ahead bias by using only historical data
Best Practices for Using This Script
1. Appropriate Parameter Selection
Correlation Window:
For short-term trading: 20-50 periods
For medium-term analysis: 50-100 periods
For long-term analysis: 100-500 periods
Rolling Window:
Should be shorter than the main correlation window
Typically 1/3 to 1/2 of the main window
Return Type:
For most applications: Log Returns (better statistical properties)
For simplicity: Simple Returns (easier to interpret)
2. Validation and Testing
Out-of-Sample Testing:
Calculate correlations on one time period
Test if they hold in a different time period
Multiple Timeframes:
Check if correlations are consistent across different timeframes
Economic Rationale:
Ensure there's a logical reason why assets should be correlated
3. Monitoring and Maintenance
Regular Review:
Correlations can change, so review them regularly
Alerts:
Set up alerts for significant correlation changes
Documentation:
Keep notes on why certain assets are correlated and what might change that relationship
4. Integration with Other Analysis
Fundamental Analysis:
Combine correlation analysis with fundamental factors
Technical Analysis:
Use correlation analysis alongside technical indicators
Market Context:
Consider how market conditions might affect correlations
Conclusion
This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights.
For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications.
Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
💻 RSI Dual-Band Reversal Strategy (Hacker Mode)This 💻 RSI Dual-Band Reversal Strategy (Hacker Mode) is a mean-reversion trading strategy built on the Relative Strength Index (RSI) indicator.
It identifies potential trend reversals when price momentum reaches extreme overbought or oversold levels — then enters trades expecting the price to revert.
⚙️ Strategy Concept
The RSI measures market momentum on a scale of 0–100.
When RSI is too low, it signals an oversold market → potential buy.
When RSI is too high, it signals an overbought market → potential sell.
This strategy sets two reversal zones using dual RSI bands:
Zone RSI Range Meaning Action
Upper Band 80–90 Overbought Prepare to Sell
Lower Band 10–20 Oversold Prepare to Buy
🧩 Code Breakdown
1. Input Parameters
rsiLength = input.int(14)
upperBandHigh = input.float(90.0)
upperBandLow = input.float(80.0)
lowerBandLow = input.float(10.0)
lowerBandHigh = input.float(20.0)
You can adjust:
RSI Length (default 14) → sensitivity of the RSI.
Upper/Lower Bands → control when buy/sell triggers occur.
2. RSI Calculation
rsi = ta.rsi(close, rsiLength)
Calculates the RSI of the closing price over 14 periods.
3. Signal Logic
buySignal = ta.crossover(rsi, lowerBandHigh)
sellSignal = ta.crossunder(rsi, upperBandLow)
Buy Signal: RSI crosses up through 20 → market rebounding from oversold.
Sell Signal: RSI crosses down through 80 → market turning from overbought.
4. Plotting
RSI line (lime green)
Bands:
🔴 80–90 (Sell Zone)
🟢 10–20 (Buy Zone)
Gray midline at 50 for reference.
Triangle markers for signals:
🟢 “BUY” below chart
🔴 “SELL” above chart
5. Trading Logic
if (buySignal)
strategy.entry("Buy", strategy.long)
if (sellSignal)
strategy.entry("Sell", CRYPTO:BTCUSD strategy.short OANDA:XAUUSD )
Opens a long position on a buy signal.
Opens a short position on a sell signal.
No explicit stop loss or take profit — positions reverse when an opposite signal appears.
🧠 How It Works (Step-by-Step Example)
RSI drops below 20 → oversold → buy signal triggers.
RSI rises toward 80 → overbought → sell signal triggers.
Strategy flips position, always staying in the market (either long or short).
📈 Visual Summary
Imagine the RSI line oscillating between 0 and 100:
100 ────────────────────────────────
90 ───── Upper Band High (Sell Limit)
80 ───── Upper Band Low (Sell Trigger)
50 ───── Midline
20 ───── Lower Band High (Buy Trigger)
10 ───── Lower Band Low (Buy Limit)
0 ────────────────────────────────
When RSI moves above 80 → SELL
When RSI moves below 20 → BUY
⚡ Strategy Profile
Category Description
Type Mean Reversion
Entry Rule RSI crosses up 20 → Buy
Exit/Reverse Rule RSI crosses down 80 → Sell
Strengths Simple, effective in sideways/range markets, minimal lag
Weaknesses Weak in strong trends, no stop-loss or take-profit logic
💡 Suggested Improvements
You can enhance this script by adding:
Stop loss & take profit levels (e.g., % or ATR-based).
Trend filter (e.g., trade only in direction of 200 EMA).
RSI smoothing to reduce noise.
Lot Size Calculator - Gold🥇 Lot Size Calculator for Gold (XAU/USD)
Description:
A professional and accurate lot size calculator specifically designed for Gold (XAU/USD) trading. This indicator helps traders calculate the optimal position size based on account balance, risk percentage, and stop loss distance, ensuring proper risk management for every trade.
Key Features:
Accurate Gold Calculations - Properly accounts for Gold pip values ($10 per pip for standard 100oz lots)
Multi-Currency Support - Works with USD, EUR, and GBP account currencies
Flexible Contract Sizes - Supports Standard (100 oz), Mini (10 oz), and Micro (1 oz) lots
Customizable Decimal Places - Display lot sizes with 2-8 decimal precision (no rounding)
Clean Visual Design - Modern, professional info panel with gold-themed styling
Adjustable Display - Position panel anywhere on chart with customizable colors and sizes
Real-Time Calculations - Instantly updates as you adjust your risk parameters
How It Works:
The calculator uses the standard forex position sizing formula optimized for Gold:
Lot Size = Risk Amount / (Stop Loss in Pips × Pip Value Per Lot)
For Gold (XAU/USD):
Standard Lot (100 oz): 1 pip = $10
Mini Lot (10 oz): 1 pip = $1
Micro Lot (1 oz): 1 pip = $0.10
Settings:
Account Settings:
Account Balance: Your trading capital
Account Currency: USD, EUR, or GBP
Risk Percentage: How much to risk per trade (default: 2%)
Contract Size: 100 oz (Standard), 10 oz (Mini), or 1 oz (Micro)
Display Currency: Choose how to display risk amounts
Trade Settings:
Stop Loss: Your SL distance in pips
Display Settings:
Label Position: Top/Bottom, Left/Right, Middle Right
Label Size: Tiny to Huge
Decimal Places: 2-8 decimals
Custom Colors: Background, text, and accent colors
Perfect For:
Gold (XAU/USD) day traders and swing traders
Position sizing and risk management
Traders using fixed percentage risk models
Anyone trading Gold CFDs or spot markets
Scalpers to long-term Gold investors
What Makes This Different:
Unlike generic lot size calculators, this tool correctly calculates Gold's pip values based on contract size. Many calculators get this wrong, leading to incorrect position sizing. This indicator ensures you're always trading the right lot size for your risk tolerance.
Example Usage:
Account Balance: $10,000
Risk: 1% = $100
Stop Loss: 60 pips
Contract Size: 100 oz (Standard)
Result: 0.1667 lots (exact, no rounding)
Perfect for maintaining consistent risk management in your Gold trading strategy!
ProScalper📊 ProScalper - Professional 1-Minute Scalping System
🎯 Overview
ProScalper is a sophisticated, multi-confluence scalping indicator designed specifically for 1-minute chart trading. Combining advanced technical analysis with intelligent signal filtering, it provides high-probability trade setups with clear entry, stop loss, and take profit levels.
✨ Key Features
🔺 Smart Signal Detection
Range Filter Technology: Fast-responding trend detection (25-period) optimized for 1-minute timeframe
Medium-sized triangles appear above/below candles for clear buy/sell signals
Only most recent signal shown - no chart clutter
Automatically deletes old signals when new ones appear
📋 Real-Time Signal Table
Top-center display shows complete trade breakdown
Grade system: A+, A, B+, B, C+ ratings for every setup
All confluence reasons listed with checkmarks
Score and R:R displayed for instant trade quality assessment
Color-coded: Green for LONG, Red for SHORT
📐 Multi-Confluence Analysis
ProScalper combines 10+ technical factors:
✅ EMA Trend: 4 EMAs (200, 48, 13, 8) for multi-timeframe alignment
✅ VWAP: Dynamic support/resistance
✅ Fibonacci Retracement: Golden ratio (61.8%), 50%, 38.2%, 78.6%
✅ Range Filter: Adaptive trend confirmation
✅ Pivot Points: Smart reversal detection
✅ Volume Analysis: Spike detection and volume profile
✅ Higher Timeframe: 5-minute trend confirmation
✅ HTF Support/Resistance: Key levels from higher timeframes
✅ Liquidity Sweeps: Smart money detection
✅ Opening Range Breakout: First 15-minute range
💰 Complete Trade Management
Entry Lines: Dashed green (LONG) or red (SHORT) showing exact entry
Stop Loss: Red dashed line with price label
Take Profit: Blue dashed line with price label and R:R
Partial Exits: 1R level marked with orange dashed line
All lines extend 10 bars for clean alignment with Fibonacci levels
📊 Dynamic Risk/Reward
Adaptive R:R calculation based on market volatility
Targets adjusted for pivot distances
Minimum 1.2:1 to maximum 3.5:1 for scalping
Position sizing based on account risk percentage
🎨 Professional Visualization
Clean chart layout - no clutter, only essential information
Custom EMA colors: Red (200), Aqua (48), Green (13), White (8)
Gold VWAP line for key support/resistance
Color-coded Fibonacci: Bright yellow (61.8%), white (50%), orange (38.2%), fuchsia (78.6%)
No shaded zones - pure price action focus
📈 Performance Tracking
Real-time statistics table (optional)
Win rate, total trades, P&L tracking
Average R:R and win/loss ratios
Setup-specific performance metrics
⚙️ Settings & Customization
Risk Management
Adjustable account risk per trade (default: 0.5%)
ATR-based stop loss multiplier (default: 0.8 for tight scalping)
Dynamic position sizing
Signal Sensitivity
Confluence Score Threshold: 40-100 (default: 55 for balanced signals)
Range Filter Period: 25 bars (fast signals for 1-min)
Range Filter Multiplier: 2.2 (tighter bands for more signals)
Visual Controls
Toggle signal table on/off
Show/hide Fibonacci levels
Control EMA visibility
Adjust table text size
Partial Exits
1R: 50% (default)
2R: 30% (default)
3R: 20% (default)
Fully customizable percentages
Trailing Stops
ATR-Based (best for scalping)
Pivot-Based
EMA-Based
Breakeven trigger at 0.8R
🎯 Best Use Cases
Ideal For:
✅ 1-minute scalping on liquid instruments
✅ Day traders looking for quick 2-8 minute trades
✅ High-frequency trading with 8-15 signals per session
✅ Trending markets where Range Filter excels
✅ Crypto, Forex, Futures - works on all liquid assets
Trading Style:
Timeframe: 1-minute (can work on 3-5 min with adjusted settings)
Hold Time: 3-8 minutes average
Target: 1.2-3R per trade
Frequency: 8-15 signals per day
Win Rate: 45-55% (with proper risk management)
📋 How to Use
Step 1: Wait for Signal
Watch for green triangle (BUY) or red triangle (SELL)
Signal table appears at top center automatically
Step 2: Review Confluence
Check grade (prefer A+, A, B+ for best quality)
Review all reasons listed in table
Confirm score is above your threshold (55+ recommended)
Note the R:R ratio
Step 3: Enter Trade
Enter at current market price
Set stop loss at red dashed line
Set take profit at blue dashed line
Mark 1R level (orange line) for partial exit
Step 4: Manage Trade
Exit 50% at 1R (orange line)
Move to breakeven after 0.8R
Trail remaining position using your chosen method
Exit fully at TP or opposite signal
🎨 Chart Setup Recommendations
Optimal Display:
Timeframe: 1-minute
Chart Type: Candles or Heikin Ashi
Background: Dark theme for best color visibility
Volume: Enable volume bars below chart
Complementary Indicators (optional):
Order flow/Delta for institutional confirmation
Market profile for key levels
Economic calendar for news avoidance
⚠️ Important Notes
Risk Disclaimer:
Not financial advice - for educational purposes only
Always use proper risk management (0.5-1% per trade max)
Past performance doesn't guarantee future results
Test on demo account before live trading
Best Practices:
✅ Trade during high liquidity hours (9:30-11 AM, 2-4 PM EST)
✅ Avoid news events and market open/close (first/last 2 minutes)
✅ Use tight stops (0.8-1.0 ATR) for 1-minute scalping
✅ Take partial profits quickly (1R = 50% off)
✅ Respect max daily loss limits (3% recommended)
✅ Focus on A and B grade setups for consistency
What Makes This Different:
🎯 Complete system - not just signals, but full trade management
📊 Multi-confluence - 10+ factors analyzed per trade
🎨 Professional visualization - clean, focused chart design
⚡ Optimized for 1-min - settings specifically tuned for fast scalping
📋 Transparent reasoning - see exactly why each trade was taken
🏆 Grade system - instantly know trade quality
🔧 Technical Details
Pine Script Version: 5
Overlay: Yes (plots on price chart)
Max Lines: 500
Max Labels: 100
Non-repainting: All signals confirmed on bar close
Alerts: Compatible with TradingView alerts
📞 Support & Updates
This indicator is actively maintained and optimized for 1-minute scalping. Settings can be adjusted for different timeframes and trading styles, but default configuration is specifically tuned for high-frequency 1-minute scalping.
🚀 Get Started
Add ProScalper to your 1-minute chart
Adjust settings to your risk tolerance
Wait for signals (green/red triangles)
Follow the signal table guidance
Manage trades using provided levels
Track performance with stats table
Happy Scalping! 📊⚡💰
FVG MagicFVG Magic — Fair Value Gaps with Smart Mitigation, Inversion & Auto-Clean-up
FVG Magic finds every tradable Fair Value Gap (FVG), shows who powered it, and then manages each gap intelligently as price interacts with it—so your chart stays actionable and clean.
Attribution
This tool is inspired by the idea popularized in “Volumatic Fair Value Gaps ” by BigBeluga (licensed CC BY-NC-SA 4.0). Credit to BigBeluga for advancing FVG visualization in the community.
Important: This is a from-scratch implementation—no code was copied from the original. I expanded the concept substantially with a different detection stack, a gap state machine (ACTIVE → 50% SQ → MITIGATED → INVERSED), auto-clean up rules, lookback/nearest-per-side pruning, zoom-proof volume meters, and timeframe auto-tuning for 15m/H1/H4.
What makes this version more accurate
Full-coverage detection (no “missed” gaps)
Default ICT-minimal rule (Bullish: low > high , Bearish: high < low ) catches all valid 3-candle FVGs.
Optional Strict filter (stricter structure checks) for traders who prefer only “clean” gaps.
Optional size percentile filter—off by default so nothing is hidden unless you choose to filter.
Correct handling of confirmations (wick vs close)
Mitigation Source is user-selectable: high/low (wick-based) or close (strict).
This avoids false “misses” when you expect wick confirmations (50% or full fill) but your logic required closes.
State-aware labelling to prevent misleading data
The Bull%/Bear% meter is shown only while a gap is ACTIVE.
As soon as a gap is 50% SQ, MITIGATED, or INVERSED, the meter is hidden and replaced with a clear tag—so you never read stale participation stats.
Robust zoom behaviour
The meter uses a fixed bar-width (not pixels), so it stays proportional and readable at any zoom level.
Deterministic lifecycle (no stale boxes)
Remove on 50% SQ (instant or delayed).
Inversion window after first entry: if price enters but doesn’t invert within N bars, the box auto-removes once fully filled.
Inversion clean up: after a confirmed flip, keep for N bars (context) then delete (or 0 = immediate).
Result: charts auto-maintain themselves and never “lie” about relevance.
Clarity near current price
Nearest-per-side (keep N closest bullish & bearish gaps by distance to the midpoint) focuses attention where it matters without altering detection accuracy.
Lookback (bars) ensures reproducible behaviour across accounts with different data history.
Timeframe-aware defaults
Sensible auto-tuning for 15m / H1 / H4 (right-extension length, meter width, inversion windows, clean up bars) to reduce setup friction and improve consistency.
What it does (under the hood)
Detects FVGs using ICT-minimal (default) or a stricter rule.
Samples volume from a 10× lower timeframe to split participation into Bull % / Bear % (sum = 100%).
Manages each gap through a state machine:
ACTIVE → 50% SQ (midline) → MITIGATED (full) → INVERSED (SR flip after fill).
Auto-clean up keeps only relevant levels, per your rules.
Dashboard (top-right) displays counts by side and the active state tags.
How to use it
First run (show everything)
Use Strict FVG Filter: OFF
Enable Size Filter (percentile): OFF
Mitigation Source: high/low (wick-based) or close (stricter), as you prefer.
Remove on 50% SQ: ON, Delay: 0
Read the context
While ACTIVE, use the Bull%/Bear% meter to gauge demand/supply behind the impulse that created the gap.
Confluence with your HTF structure, sessions, VWAP, OB/FVG, RSI/MACD, etc.
Trade interactions
50% SQ: often the highest-quality interaction; if removal is ON, the box clears = “job done.”
Full mitigation then rejection through the other side → tag changes to INVERSED (acts like SR). Keep for N bars, then auto-remove.
Keep the chart tidy (optional)
If too busy, enable Size Filter or set Nearest per side to 2–4.
Use Lookback (bars) to make behaviour consistent across symbols and histories.
Inputs (key ones)
Use Strict FVG Filter: OFF(default)/ON
Enable Size Filter (percentile): OFF(default)/ON + threshold
Mitigation Source: high/low or close
Remove on 50% SQ + Delay
Inversion window after entry (bars)
Remove inversed after (bars)
Lookback (bars), Nearest per side (N)
Right Extension Bars, Max FVGs, Meter width (bars)
Colours: Bullish, Bearish, Inversed fill
Suggested defaults (per TF)
15m: Extension 50, Max 12, Inversion window 8, Clean up 8, Meter width 20
H1: Extension 25, Max 10, Inversion window 6, Clean up 6, Meter width 15
H4: Extension 15, Max 8, Inversion window 5, Clean up 5, Meter width 10
Notes & edge cases
If a wick hits 50% or the far edge but state doesn’t change, you’re likely on close mode—switch to high/low for wick-based behaviour.
If a gap disappears, it likely met a clean up condition (50% removal, inversion window, inversion clean up, nearest-per-side, lookback, or max-cap).
Meters are hidden after ACTIVE to avoid stale percentages.
Ultimate Oscillator (ULTOSC)The Ultimate Oscillator (ULTOSC) is a technical momentum indicator developed by Larry Williams that combines three different time periods to reduce the volatility and false signals common in single-period oscillators. By using a weighted average of three Stochastic-like calculations across short, medium, and long-term periods, the Ultimate Oscillator provides a more comprehensive view of market momentum while maintaining sensitivity to price changes.
The indicator addresses the common problem of oscillators being either too sensitive (generating many false signals) or too slow (missing opportunities). By incorporating multiple timeframes with decreasing weights for longer periods, ULTOSC attempts to capture both short-term momentum shifts and longer-term trend strength, making it particularly valuable for identifying divergences and potential reversal points.
## Core Concepts
* **Multi-timeframe analysis:** Combines three different periods (typically 7, 14, 28) to capture various momentum cycles
* **Weighted averaging:** Assigns higher weights to shorter periods for responsiveness while including longer periods for stability
* **Buying pressure focus:** Measures the relationship between closing price and the true range rather than just high-low range
* **Divergence detection:** Particularly effective at identifying momentum divergences that precede price reversals
* **Normalized scale:** Oscillates between 0 and 100, with clear overbought/oversold levels
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Fast Period | 7 | Short-term momentum calculation | Lower (5-6) for more sensitivity, higher (9-12) for smoother signals |
| Medium Period | 14 | Medium-term momentum calculation | Adjust based on typical swing duration in the market |
| Slow Period | 28 | Long-term momentum calculation | Higher values (35-42) for longer-term position trading |
| Fast Weight | 4.0 | Weight applied to fast period | Higher weight increases short-term sensitivity |
| Medium Weight | 2.0 | Weight applied to medium period | Adjust to balance medium-term influence |
| Slow Weight | 1.0 | Weight applied to slow period | Usually kept at 1.0 as the baseline weight |
**Pro Tip:** The classic 7/14/28 periods with 4/2/1 weights work well for most markets, but consider using 5/10/20 with adjusted weights for faster markets or 14/28/56 for longer-term analysis.
## Calculation and Mathematical Foundation
**Simplified explanation:**
The Ultimate Oscillator calculates three separate "buying pressure" ratios using different time periods, then combines them using weighted averaging. Buying pressure is defined as the close minus the true low, divided by the true range.
**Technical formula:**
```
BP = Close - Min(Low, Previous Close)
TR = Max(High, Previous Close) - Min(Low, Previous Close)
BP_Sum_Fast = Sum(BP, Fast Period)
TR_Sum_Fast = Sum(TR, Fast Period)
Raw_Fast = 100 × (BP_Sum_Fast / TR_Sum_Fast)
BP_Sum_Medium = Sum(BP, Medium Period)
TR_Sum_Medium = Sum(TR, Medium Period)
Raw_Medium = 100 × (BP_Sum_Medium / TR_Sum_Medium)
BP_Sum_Slow = Sum(BP, Slow Period)
TR_Sum_Slow = Sum(TR, Slow Period)
Raw_Slow = 100 × (BP_Sum_Slow / TR_Sum_Slow)
ULTOSC = 100 × / (Fast_Weight + Medium_Weight + Slow_Weight)
```
Where:
- BP = Buying Pressure
- TR = True Range
- Fast Period = 7, Medium Period = 14, Slow Period = 28 (defaults)
- Fast Weight = 4, Medium Weight = 2, Slow Weight = 1 (defaults)
> 🔍 **Technical Note:** The implementation uses efficient circular buffers for all three period calculations, maintaining O(1) time complexity per bar. The algorithm properly handles true range calculations including gaps and ensures accurate buying pressure measurements across all timeframes.
## Interpretation Details
ULTOSC provides several analytical perspectives:
* **Overbought/Oversold conditions:** Values above 70 suggest overbought conditions, below 30 suggest oversold conditions
* **Momentum direction:** Rising ULTOSC indicates increasing buying pressure, falling indicates increasing selling pressure
* **Divergence analysis:** Divergences between ULTOSC and price often precede significant reversals
* **Trend confirmation:** ULTOSC direction can confirm or question the prevailing price trend
* **Signal quality:** Extreme readings (>80 or <20) indicate strong momentum that may be unsustainable
* **Multiple timeframe consensus:** When all three underlying periods agree, signals are typically more reliable
## Trading Applications
**Primary Uses:**
- **Divergence trading:** Identify when momentum diverges from price for reversal signals
- **Overbought/oversold identification:** Find potential entry/exit points at extreme levels
- **Trend confirmation:** Validate breakouts and trend continuations
- **Momentum analysis:** Assess the strength of current price movements
**Advanced Strategies:**
- **Multi-divergence confirmation:** Look for divergences across multiple timeframes
- **Momentum breakouts:** Trade when ULTOSC breaks above/below key levels with volume
- **Swing trading entries:** Use oversold/overbought levels for swing position entries
- **Trend strength assessment:** Evaluate trend quality using momentum consistency
## Signal Combinations
**Strong Bullish Signals:**
- ULTOSC rises from oversold territory (<30) with positive price divergence
- ULTOSC breaks above 50 after forming a base near 30
- All three underlying periods show increasing buying pressure
**Strong Bearish Signals:**
- ULTOSC falls from overbought territory (>70) with negative price divergence
- ULTOSC breaks below 50 after forming a top near 70
- All three underlying periods show decreasing buying pressure
**Divergence Signals:**
- **Bullish divergence:** Price makes lower lows while ULTOSC makes higher lows
- **Bearish divergence:** Price makes higher highs while ULTOSC makes lower highs
- **Hidden bullish divergence:** Price makes higher lows while ULTOSC makes lower lows (trend continuation)
- **Hidden bearish divergence:** Price makes lower highs while ULTOSC makes higher highs (trend continuation)
## Comparison with Related Oscillators
| Indicator | Periods | Focus | Best Use Case |
|-----------|---------|-------|---------------|
| **Ultimate Oscillator** | 3 periods | Buying pressure | Divergence detection |
| **Stochastic** | 1-2 periods | Price position | Overbought/oversold |
| **RSI** | 1 period | Price momentum | Momentum analysis |
| **Williams %R** | 1 period | Price position | Short-term signals |
## Advanced Configurations
**Fast Trading Setup:**
- Fast: 5, Medium: 10, Slow: 20
- Weights: 4/2/1, Thresholds: 75/25
**Standard Setup:**
- Fast: 7, Medium: 14, Slow: 28
- Weights: 4/2/1, Thresholds: 70/30
**Conservative Setup:**
- Fast: 14, Medium: 28, Slow: 56
- Weights: 3/2/1, Thresholds: 65/35
**Divergence Focused:**
- Fast: 7, Medium: 14, Slow: 28
- Weights: 2/2/2, Thresholds: 70/30
## Market-Specific Adjustments
**Volatile Markets:**
- Use longer periods (10/20/40) to reduce noise
- Consider higher threshold levels (75/25)
- Focus on extreme readings for signal quality
**Trending Markets:**
- Emphasize divergence analysis over absolute levels
- Look for momentum confirmation rather than reversal signals
- Use hidden divergences for trend continuation
**Range-Bound Markets:**
- Standard overbought/oversold levels work well
- Trade reversals from extreme levels
- Combine with support/resistance analysis
## Limitations and Considerations
* **Lagging component:** Contains inherent lag due to multiple moving average calculations
* **Complex calculation:** More computationally intensive than single-period oscillators
* **Parameter sensitivity:** Performance varies significantly with different period/weight combinations
* **Market dependency:** Most effective in trending markets with clear momentum patterns
* **False divergences:** Not all divergences lead to significant price reversals
* **Whipsaw potential:** Can generate conflicting signals in choppy markets
## Best Practices
**Effective Usage:**
- Focus on divergences rather than absolute overbought/oversold levels
- Combine with trend analysis for context
- Use multiple timeframe analysis for confirmation
- Pay attention to the speed of momentum changes
**Common Mistakes:**
- Over-relying on overbought/oversold levels in strong trends
- Ignoring the underlying trend direction
- Using inappropriate period settings for the market being analyzed
- Trading every divergence without additional confirmation
**Signal Enhancement:**
- Combine with volume analysis for confirmation
- Use price action context (support/resistance levels)
- Consider market volatility when setting thresholds
- Look for convergence across multiple momentum indicators
## Historical Context and Development
The Ultimate Oscillator was developed by Larry Williams and introduced in his 1985 article "The Ultimate Oscillator" in Technical Analysis of Stocks and Commodities magazine. Williams designed it to address the limitations of single-period oscillators by:
- Reducing false signals through multi-timeframe analysis
- Maintaining sensitivity to short-term momentum changes
- Providing more reliable divergence signals
- Creating a more robust momentum measurement tool
The indicator has become a standard tool in technical analysis, particularly valued for its divergence detection capabilities and its balanced approach to momentum measurement.
## References
* Williams, L. R. (1985). The Ultimate Oscillator. Technical Analysis of Stocks and Commodities, 3(4).
* Williams, L. R. (1999). Long-Term Secrets to Short-Term Trading. Wiley Trading.
Double Weighted Moving Average (DWMA)# DWMA: Double Weighted Moving Average
## Overview and Purpose
The Double Weighted Moving Average (DWMA) is a technical indicator that applies weighted averaging twice in sequence to create a smoother signal with enhanced noise reduction. Developed in the late 1990s as an evolution of traditional weighted moving averages, the DWMA was created by quantitative analysts seeking enhanced smoothing without the excessive lag typically associated with longer period averages. By applying a weighted moving average calculation to the results of an initial weighted moving average, DWMA achieves more effective filtering while preserving important trend characteristics.
## Core Concepts
* **Cascaded filtering:** DWMA applies weighted averaging twice in sequence for enhanced smoothing and superior noise reduction
* **Linear weighting:** Uses progressively increasing weights for more recent data in both calculation passes
* **Market application:** Particularly effective for trend following strategies where noise reduction is prioritized over rapid signal response
* **Timeframe flexibility:** Works across multiple timeframes but particularly valuable on daily and weekly charts for identifying significant trends
The core innovation of DWMA is its two-stage approach that creates more effective noise filtering while minimizing the additional lag typically associated with longer-period or higher-order filters. This sequential processing creates a more refined output that balances noise reduction and signal preservation better than simply increasing the length of a standard weighted moving average.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Length | 14 | Controls the lookback period for both WMA calculations | Increase for smoother signals in volatile markets, decrease for more responsiveness |
| Source | close | Price data used for calculation | Consider using hlc3 for a more balanced price representation |
**Pro Tip:** For trend following, use a length of 10-14 with DWMA instead of a single WMA with double the period - this provides better smoothing with less lag than simply increasing the period of a standard WMA.
## Calculation and Mathematical Foundation
**Simplified explanation:**
DWMA first calculates a weighted moving average where recent prices have more importance than older prices. Then, it applies the same weighted calculation again to the results of the first calculation, creating a smoother line that reduces market noise more effectively.
**Technical formula:**
```
DWMA is calculated by applying WMA twice:
1. First WMA calculation:
WMA₁ = (P₁ × w₁ + P₂ × w₂ + ... + Pₙ × wₙ) / (w₁ + w₂ + ... + wₙ)
2. Second WMA calculation applied to WMA₁:
DWMA = (WMA₁₁ × w₁ + WMA₁₂ × w₂ + ... + WMA₁ₙ × wₙ) / (w₁ + w₂ + ... + wₙ)
```
Where:
- Linear weights: most recent value has weight = n, second most recent has weight = n-1, etc.
- n is the period length
- Sum of weights = n(n+1)/2
**O(1) Optimization - Inline Dual WMA Architecture:**
This implementation uses an advanced O(1) algorithm with two complete inline WMA calculations. Each WMA uses the dual running sums technique:
1. **First WMA (source → wma1)**:
- Maintains buffer1, sum1, weighted_sum1
- Recurrence: `W₁_new = W₁_old - S₁_old + (n × P_new)`
- Cached denominator norm1 after warmup
2. **Second WMA (wma1 → dwma)**:
- Maintains buffer2, sum2, weighted_sum2
- Recurrence: `W₂_new = W₂_old - S₂_old + (n × WMA₁_new)`
- Cached denominator norm2 after warmup
**Implementation details:**
- Both WMAs fully integrated inline (no helper functions)
- Each maintains independent state: buffers, sums, counters, norms
- Both warm up independently from bar 1
- Performance: ~16 operations per bar regardless of period (vs ~10,000 for naive O(n²) implementation)
**Why inline architecture:**
Unlike helper functions, the inline approach makes all state variables and calculations visible in a single scope, eliminating function call overhead and making the dual-pass nature explicit. This is ideal for educational purposes and when debugging complex cascaded filters.
> 🔍 **Technical Note:** The dual-pass O(1) approach creates a filter that effectively increases smoothing without the quadratic increase in computational cost. Original O(n²) implementations required ~10,000 operations for period=100; this optimized version requires only ~16 operations, achieving a 625x speedup while maintaining exact mathematical equivalence.
## Interpretation Details
DWMA can be used in various trading strategies:
* **Trend identification:** The direction of DWMA indicates the prevailing trend
* **Signal generation:** Crossovers between price and DWMA generate trade signals, though they occur later than with single WMA
* **Support/resistance levels:** DWMA can act as dynamic support during uptrends and resistance during downtrends
* **Trend strength assessment:** Distance between price and DWMA can indicate trend strength
* **Noise filtering:** Using DWMA to filter noisy price data before applying other indicators
## Limitations and Considerations
* **Market conditions:** Less effective in choppy, sideways markets where its lag becomes a disadvantage
* **Lag factor:** More lag than single WMA due to double calculation process
* **Initialization requirement:** Requires more data points for full calculation, showing more NA values at chart start
* **Short-term trading:** May miss short-term trading opportunities due to increased smoothing
* **Complementary tools:** Best used with momentum oscillators or volume indicators for confirmation
## References
* Jurik, M. "Double Weighted Moving Averages: Theory and Applications in Algorithmic Trading Systems", Jurik Research Papers, 2004
* Ehlers, J.F. "Cycle Analytics for Traders," Wiley, 2013
CCI [Hash Adaptive]Adaptive CCI Pro: Professional Technical Analysis Indicator
The Commodity Channel Index is a momentum oscillator developed by Donald Lambert in 1980. CCI measures the relationship between an asset's price and its statistical average, identifying cyclical turns and overbought/oversold conditions. The indicator oscillates around zero, with values above +100 indicating overbought conditions and values below -100 suggesting oversold conditions.
Standard CCI Formula: (Typical Price - Moving Average) / (0.015 × Mean Deviation)
This indicator transforms the traditional CCI into a sophisticated visual analysis tool through several key enhancements:
Implements dual exponential moving average smoothing to eliminate market noise
Preserves signal integrity while reducing false signals
Adaptive smoothing responds to market volatility conditions
Dynamic Color Visualization System
Continuous gradient transitions from red (bearish momentum) to green (bullish momentum)
Real-time color intensity reflects momentum strength
Eliminates discrete color jumps for fluid visual interpretation
Adaptive Intelligence Features
Dynamic overbought/oversold thresholds adapt to market conditions
Reduces false signals during high volatility periods
Maintains sensitivity during low volatility environments
Momentum Vector Analysis
Incorporates velocity calculations for early trend identification
Crossover detection with momentum confirmation
Advanced signal filtering reduces market noise
Extreme Level Analysis
Values above +100: Strong overbought conditions, potential reversal zones
Values below -100: Strong oversold conditions, potential buying opportunities
Zero-line crossovers: Momentum shift confirmation
Optimization Parameters
CCI Period (Default: 14)
Shorter periods (10-12): Increased sensitivity, more signals
Standard periods (14-20): Balanced responsiveness and reliability
Longer periods (21-30): Reduced noise, stronger signal confirmation
Smoothing Factor (Default: 5)
Lower values (1-3): Maximum responsiveness, suitable for scalping
Medium values (4-6): Balanced approach for swing trading
Higher values (7-10): Institutional-grade smoothness for position trading
Signal Sensitivity (Default: 6)
Conservative (7-10): High-probability signals, reduced frequency
Balanced (5-6): Optimal risk-reward ratio
Aggressive (1-4): Maximum signal generation, requires additional confirmation
Strategic Implementation
Oversold reversals in red zones with momentum confirmation
Zero-line breaks with sustained color transitions
Extreme readings followed by momentum divergence
Risk Management
Use extreme levels (+100/-100) for position sizing decisions
Monitor color intensity for momentum strength assessment
Combine with price action analysis for comprehensive market view
Market Context Application
Trending markets: Focus on momentum direction and extreme readings
Range-bound markets: Utilize overbought/oversold levels for mean reversion
Volatile markets: Increase smoothing parameters and signal sensitivity
Professional Advantages
Instantaneous momentum assessment through color visualization
Reduced cognitive load compared to traditional oscillators
Professional presentation suitable for client reporting
Adaptive Technology
Self-adjusting parameters reduce manual optimization requirements
Consistent performance across varying market conditions
Advanced mathematics eliminate common CCI limitations
The Adaptive CCI Pro represents the evolution of momentum analysis, combining Lambert's foundational CCI concept with modern computational techniques to deliver institutional-grade market intelligence through an intuitive visual interface.
iFVG Strategie by Futures.RobbyiFVG Strategy Checklist by Futures.Robby
Updated: October 27, 2025
Description
This script is a manual checklist designed to help traders evaluate their setups based on the iFVG (Fair Value Gap) strategy. It serves solely as a visual aid and does not perform automatic analysis, signal generation, or trade execution.
How It Works
The script creates an interactive checklist directly on the chart. Traders manually select which criteria are met, and the script calculates a percentage score, displaying it with color coding:
Green (≥ 60%): Good fulfillment of criteria
Orange (40–59%): Partial fulfillment
Red (< 40%): Poor fulfillment
Checklist Criteria
The checklist is divided into two main sections:
1. Trade Criteria (8 Points)
Eight manually selectable criteria to assess setup quality:
Trade im Bias → Trade in Bias: Trade follows the higher timeframe trend (H1/H4/Daily).
BE Level → BE Level: Swing point between entry and target.
Sweep → Sweep: Price hits a key swing before reversing.
Displacement → Displacement: iFVG broken by strong candles.
Leg FVG geschlossen → Leg FVG Closed: No open m1 to m5 FVGs to target.
FVG Reaktion → FVG Reaction: Reaction at FVG during sweep (HTF).
FVG Größe → FVG Size: 6 to 10 points.
Anzahl Kerzen → Number of Candles: Maximum of 6 candles.
2. Goals (1 Point)
Six optional goal conditions, counted together as 1 point:
Equal H / L → Equal High/Low
Session H / L → Session High/Low
News H / L → News High/Low
HTF Swing Point → HTF Swing Point
HTF OB → HTF Order Block
HTF FVG → HTF FVG
Settings and Customization
The script’s settings are translated as follows:
Group: Trade Criteria
Trade im Bias → Trade in Bias
Tooltip: Trendrichtung folgt HTF (H1/H4/Täglich) – Trend follows HTF direction
BE Level → BE Level
Tooltip: Swingpunkt zwischen Einstieg und Ziel – Swing point between entry and target
Sweep → Sweep
Tooltip: Kurs erreicht markanten Swing – Price hits key swing before inverse
Displacement → Displacement
Tooltip: iFVG durch starke Kerzen gebrochen – iFVG broken by strong candles
Leg FVG geschlossen → Leg FVG Closed
Tooltip: Keine offenen m1 bis m5 FVGs bis Ziel – No open m1 to m5 FVGs to target
FVG Reaktion → FVG Reaction
Tooltip: Reaktion an FVG beim Sweep (HTF) – Reaction at FVG during sweep (HTF)
FVG Größe → FVG Size
Tooltip: 6 bis 10 Punkte – 6 to 10 points
Anzahl Kerzen → Number of Candles
Tooltip: Maximal 6 Kerzen – Maximum of 6 candles
Group: Goals
Equal H / L → Equal High/Low
Session H / L → Session High/Low
News H / L → News High/Low
HTF Swing Point → HTF Swing Point
HTF OB → HTF Order Block
HTF FVG → HTF FVG
ℹ️ Ziele zählen gemeinsam als 1 Punkt → ℹ️ Goals count together as 1 point
Window Position & Size
Fensterposition → Window Position
oben rechts → top right
oben links → top left
unten rechts → bottom right
unten links → bottom left
Tabellengröße → Table Size
normal → normal
small → small
tiny → tiny
Translation of Chart Table Contents
The table headers and entries on the chart are translated as follows:
Table Headers:
Trade Checkliste → Trade Checklist
Ziele → Goals
Status Symbols:
✅ → ✅ (Fulfilled)
❌ → ❌ (Not fulfilled)
Individual Criteria (Trade Criteria):
Trade im Bias → Trade in Bias
BE Level → BE Level
Sweep → Sweep
Displacement → Displacement
Leg FVG geschlossen → Leg FVG Closed
FVG Reaktion → FVG Reaction
FVG Größe → FVG Size
Anzahl Kerzen → Number of Candles
Individual Criteria (Goals):
Equal H / L → Equal High/Low
Session H / L → Session High/Low
News H / L → News High/Low
HTF Swing Point → HTF Swing Point
HTF OB → HTF Order Block
HTF FVG → HTF FVG
Note Line:
Ziele zählen gemeinsam als 1 Punkt → Goals count together as 1 point
Important Note
This tool is not an automated indicator, but a visual decision aid for traders who want to apply their strategy in a structured and conscious way.
Relative Performance Tracker [QuantAlgo]🟢 Overview
The Relative Performance Tracker is a multi-asset comparison tool designed to monitor and rank up to 30 different tickers simultaneously based on their relative price performance. This indicator enables traders and investors to quickly identify market leaders and laggards across their watchlist, facilitating rotation strategies, strength-based trading decisions, and cross-asset momentum analysis.
🟢 Key Features
1. Multi-Asset Monitoring
Track up to 30 tickers across any market (stocks, crypto, forex, commodities, indices)
Individual enable/disable toggles for each ticker to customize your watchlist
Universal compatibility with any TradingView symbol format (EXCHANGE:TICKER)
2. Ranking Tables (Up to 3 Tables)
Each ticker's percentage change over your chosen lookback period, calculated as:
(Current Price - Past Price) / Past Price × 100
Automatic sorting from strongest to weakest performers
Rank: Position from 1-30 (1 = strongest performer)
Ticker: Symbol name with color-coded background (green for gains, red for losses)
% Change: Exact percentage with color intensity matching magnitude
For example, Rank #1 has the highest gain among all enabled tickers, Rank #30 has the lowest (or most negative) return.
3. Histogram Visualization
Adjustable bar count: Display anywhere from 1 to 30 top-ranked tickers (user customizable)
Bar height = magnitude of percentage change.
Bars extend upward for gains, downward for losses. Taller bars = larger moves.
Green bars for positive returns, red for negative returns.
4. Customizable Color Schemes
Classic: Traditional green/red for intuitive interpretation
Aqua: Blue/orange combination for reduced eye strain
Cosmic: Vibrant aqua/purple optimized for dark mode
Custom: Full personalization of positive and negative colors
5. Built-In Ranking Alerts
Six alert conditions detect when rankings change:
Top 1 Changed: New #1 leader emerges
Top 3/5/10/15/20 Changed: Shifts within those tiers
🟢 Practical Applications
→ Momentum Trading: Focus on top-ranked assets (Rank 1-10) that show strongest relative strength for trend-following strategies
→ Market Breadth Analysis: Monitor how many tickers are above vs. below zero on the histogram to gauge overall market health
→ Divergence Spotting: Identify when previously leading assets lose momentum (drop out of top ranks) as potential trend reversal signals
→ Multi-Timeframe Analysis: Use different lookback periods on different charts to align short-term and long-term relative strength
→ Customized Focus: Adjust histogram bars to show only top 5-10 strongest movers for concentrated analysis, or expand to 20-30 for comprehensive overview
4h 相对超跌筛选器 · Webhook v2.0## 指标用途
用于你的「框架第2步」：在**美股 RTH**里，按**4h 收盘**（06:30–10:30 PT 为首根）筛出相对大盘/行业**显著超跌**且结构健康的候选标的，并可**通过 Webhook 自动推送**`symbol + ts`给下游 AI 执行新闻甄别（第3步）与进出场评估（第4步）。
## 工作原理（核心逻辑）
* **结构健康**：最近 80 根 4h 中，收盘 > 4h_SMA50 的占比 ≥ 阈值（默认 55%）。
* **跌深条件**：4h 跌幅 ≤ −4%，且近两根累计（≈8h）≤ −6%。
* **相对劣化**：相对大盘（SPY/QQQ）与相对行业（XLK/XLF/… 或 KWEB/CQQQ）各 ≤ −3%。
* **流动性与价格**：ADV20_USD ≥ 2000 万；价格 ≥ 3 美元。
* **只在 4h 收盘刻评估与触发**，历史点位全部保留，便于回放核验。
* **冷却**：同一标的信号间隔 ≥ N 天（默认 10）。
## 主要输入参数
* **bench / sector**：大盘与行业基准（例：SPY/QQQ，XLK/XLF/XLY；中概用 KWEB/CQQQ）。
* **advMinUSD / priceMin**：20 日美元成交额下限、最小价格。
* **pctAboveTh**：结构健康阈值（%）。
* **drop4hTh / drop8hTh**：4h/8h 跌幅阈值（%）。
* **relMktTh / relSecTh**：相对大盘/行业阈值（%）。
* **coolDays**：冷却天数。
* **fromDate**：仅显示此日期后的历史信号（图表拥挤时可用）。
* **showTable / tableRows**：是否显示右上角“最近信号表”及行数。
## 图表信号
* **S2 绿点**：当根 4h 收盘满足全部筛选条件。
* **右上角表格**：滚动列出最近 N 条命中（`SYMBOL @ yyyy-MM-dd HH:mm`，按图表本地时区）。
## Webhook 联动（生产用）
1. 添加指标 → 🔔 新建警报（Alert）：
* **Condition**：`Any alert() function call`
* **Options**：`Once per bar close`
* **Webhook URL**：填你的接收地址（可带 `?token=...`）
* **Message**：留空（脚本内部 `alert(payload)` 会发送 JSON）。
2. 典型 JSON 载荷（举例）：
```json
{
"event": "step2_signal",
"symbol": "LULU",
"symbol_id": "NASDAQ:LULU",
"venue": "NASDAQ",
"bench": "SPY",
"sector": "XLY",
"ts_bar_close_ms": 1754524200000,
"ts_bar_close_local": "2025-06-06 10:30",
"price_close": 318.42,
"ret_4h_pct": -5.30,
"ret_8h_pct": -7.45,
"rel_mkt_pct": -4.90,
"rel_sec_pct": -3.80
}
```
> 建议以 `symbol + ts_bar_close_ms` 做去重键；接收端先快速 `200 OK`，后续异步处理并交给第3步 AI。
## 使用建议
* **时间框架**：任意周期可用，指标内部统一拉取 240 分钟数据并仅在 4h 收盘刻触发。
* **行业映射**：尽量选与个股业务最贴近的 ETF；中国 ADR 可用 `PGJ/KWEB/CQQQ` 叠加细分行业对照。
* **回放验证**：Bar Replay **不发送真实 Webhook**；仅用于查看历史命中与表格。测试接收端请用 Alert 面板的 **Test**。
## 适配说明
* Pine Script **v5**。
* 不含成分筛查逻辑（请在你的 500–600 只候选池内使用）。
* 数字常量不使用下划线分隔；如需大数可用 `20000000` 或 `2e7`。
## 常见问题
* ⛔️ 报错 `tostring(...)`：Pine 无时间格式化重载，脚本已内置 `timeToStr()`。
* ⛔️ `syminfo.exchange` 不存在：已改用 `syminfo.prefix`（交易所前缀）。
* ⛔️ 多行字符串拼接报 `line continuation`：本脚本已用括号包裹或 `str.format` 规避。
## 免责声明
该指标仅供筛选与研究使用，不构成投资建议。请结合你的第3步新闻/基本面甄别与第4步执行规则共同决策。
Scalper Pro Pattern Recognition & Price ActionOVERVIEW
Scalper Pro is a comprehensive multi-timeframe trading indicator that combines Smart Money Concepts (SMC) with traditional technical analysis to provide scalpers and day traders with high-probability entry and exit signals. This indicator integrates multiple analytical frameworks into a unified visual system designed specifically for short-term trading strategies.
ORIGINALITY & PURPOSE
What Makes This Script Original
This script is not a simple mashup of existing indicators. Instead, it represents a carefully orchestrated integration of complementary analytical methods that work together to solve a specific problem: identifying high-probability scalping opportunities in volatile markets.
The unique value proposition:
Adaptive Trend Filtering System - Combines a customized SuperTrend algorithm with dual-period range filters (Cirrus Cloud) and Hull Moving Average trend cloud to create a three-layer trend confirmation system
Smart Money Concepts Integration - Incorporates institutional trading concepts (Order Blocks, Fair Value Gaps, Break of Structure) with retail technical indicators for a complete market structure view
Dynamic Risk Management - Automatically calculates stop-loss and take-profit levels based on ATR volatility, providing objective position sizing
ADX-Based Market Regime Detection - Identifies ranging vs. trending markets through ADX analysis with visual bar coloring to prevent whipsaws during consolidation
Why Combine These Specific Components
Each component addresses a specific weakness in scalping:
SuperTrend provides the primary directional bias but can generate false signals in ranging markets
Range Filters smooth out noise and confirm trend direction, reducing SuperTrend false positives
ADX Analysis prevents trading during low-volatility consolidation when most indicators fail
SMC Elements identify institutional activity zones where price is likely to react strongly
ATR-Based Risk Management adapts position sizing to current volatility conditions
The synergy creates a system where signals are only generated when multiple confirmation layers align, significantly reducing false signals common in single-indicator approaches.
HOW IT WORKS
Core Calculation Methodology
1. SuperTrend Signal Generation
The script uses a modified SuperTrend algorithm with the following calculation:
ATR = Average True Range (default: 10 periods)
Factor = 7 (default sensitivity multiplier)
Upper Band = Source + (Factor × ATR)
Lower Band = Source - (Factor × ATR)
Directional Logic:
When price crosses above SuperTrend → Bullish signal
When price crosses below SuperTrend → Bearish signal
SuperTrend value is plotted as dynamic support/resistance
Key Modification: The sensitivity parameter (nsensitivity * 7) allows users to adjust the aggressiveness of trend detection without changing the core ATR calculation.
2. Range Filter System (Cirrus Cloud)
The Range Filter uses a smoothed range calculation to filter out market noise:
Smooth Range Calculation:
WPER = (Period × 2) - 1
AVRNG = EMA(|Price - Price |, Period)
Smooth Range = EMA(AVRNG, WPER) × Multiplier
Two-Layer System:
Layer 1: 22-period with 6x multiplier (broader trend)
Layer 2: 15-period with 5x multiplier (tighter price action)
Visual Output: The space between these two filters is colored:
Green fill = Bullish trend (Layer 1 > Layer 2)
Red fill = Bearish trend (Layer 1 < Layer 2)
This creates a "cloud" that expands during strong trends and contracts during consolidation.
3. ADX Market Regime Detection
Calculation:
+DM = Positive Directional Movement
-DM = Negative Directional Movement
True Range = RMA of True Range (15 periods)
+DI = 100 × RMA(+DM, 15) / True Range
-DI = 100 × RMA(-DM, 15) / True Range
ADX = 100 × RMA(|+DI - -DI| / (+DI + -DI), 15)
Threshold System:
ADX < Threshold (default 15) = Ranging market → Bar color changes to purple
ADX > Threshold = Trending market → Normal bar coloring applies
Purpose: This prevents taking trend-following signals during sideways markets where most indicators produce whipsaws.
4. Smart Money Concepts (SMC) Integration
Order Blocks (OB):
Identified using swing high/low detection with customizable pivot length
Bullish OB: Last down-close candle before bullish Break of Structure (BOS)
Bearish OB: Last up-close candle before bearish BOS
Extended forward until price breaks through them
Fair Value Gaps (FVG):
Detected when a three-candle gap exists:
Bullish FVG: Low > High
Bearish FVG: High < Low
Filtered by price delta percentage to ensure significant gaps
Displayed as boxes that delete when price fills the gap
Break of Structure (BOS) vs. Change of Character (CHoCH):
BOS = Price breaks the previous structural high/low in the current trend direction
CHoCH = Price breaks structure in the opposite direction (potential trend reversal)
Both internal (minor) and swing (major) structures are tracked
Equal Highs/Lows (EQH/EQL):
Detected when consecutive swing highs/lows are within ATR threshold
Often indicates liquidity pools that price may sweep before reversing
5. ATR-Based Risk Management
Calculation:
ATR Band = ATR(14) × Risk Multiplier (default 3%)
Stop Loss = Entry - ATR Band (for longs) or Entry + ATR Band (for shorts)
Take Profit Levels:
TP1 = Entry + (Entry - Stop Loss) × 1
TP2 = Entry + (Entry - Stop Loss) × 2
TP3 = Entry + (Entry - Stop Loss) × 3
Dynamic Labels: Stop loss and take profit levels are automatically calculated and displayed as labels on the chart when new signals trigger.
6. Hull Moving Average Trend Cloud
HMA = WMA(2 × WMA(Close, Period/2) - WMA(Close, Period), sqrt(Period))
Period = 600 bars (long-term trend)
The HMA provides a smoothed long-term trend reference that's more responsive than traditional moving averages while filtering out short-term noise.
HOW TO USE THE INDICATOR
Entry Signals
Primary Buy Signal:
SuperTrend changes to green (price crosses above)
ADX shows market is NOT ranging (bars are NOT purple)
Price is within or near a bullish Order Block OR bullish FVG
Cirrus Cloud shows green fill (Layer 1 > Layer 2)
Primary Sell Signal:
SuperTrend changes to red (price crosses below)
ADX shows market is NOT ranging
Price is within or near a bearish Order Block OR bearish FVG
Cirrus Cloud shows red fill (Layer 1 < Layer 2)
Confirmation Layers
Higher Probability Trades Include:
Bullish/Bearish BOS in the same direction as signal
Equal highs/lows being swept before entry
Price respecting premium/discount zones (above/below equilibrium)
Multiple timeframe alignment (use MTF settings)
Exit Strategy
The indicator provides three take-profit levels:
TP1: Conservative target (1:1 risk-reward)
TP2: Moderate target (2:1 risk-reward)
TP3: Aggressive target (3:1 risk-reward)
Suggested Exit Approach:
Close 1/3 position at TP1
Move stop to breakeven
Close 1/3 position at TP2
Trail remaining position or exit at TP3
Risk Management
Stop Loss:
Use the ATR-based stop loss level displayed on chart
Alternatively, use percentage-based stop (adjustable in settings)
Never risk more than 1-2% of account per trade
Position Sizing:
Position Size = (Account Risk $) / (Entry Price - Stop Loss Price)
CUSTOMIZABLE SETTINGS
Core Parameters
Buy/Sell Signals:
Toggle signals on/off
Adjust SuperTrend sensitivity (0.5 - 2.0)
Risk Management:
Show/hide TP/SL levels
ATR period (default: 14)
Risk percentage (default: 3%)
Number of decimal places for price labels
Trend Features:
Cirrus Cloud display toggle
Range filter periods (x1, x2, x3, x4)
Hull MA length for trend cloud
Smart Money Concepts:
Order Block settings (swing length, display count)
Fair Value Gap parameters (auto-threshold, extend length)
Structure detection (internal vs swing)
EQH/EQL threshold
ADX Settings:
ADX length (default: 15)
Sideways threshold (10-30, default: 15)
Bar color toggle
Display Options:
Previous day/week/month high/low levels
Premium/Discount/Equilibrium zones
Trend candle coloring (colored or monochrome)
BEST PRACTICES & TRADING TIPS
Optimal Use Cases
Scalping on lower timeframes (1m, 5m, 15m)
Rapid entry/exit with clear TP levels
ADX filter prevents choppy market entries
Day trading on medium timeframes (30m, 1H)
Stronger trend confirmation
Better risk-reward ratios
Swing trading entries on higher timeframes (4H, Daily)
Higher-probability structural setups
Larger ATR-based stops accommodate volatility
Market Conditions
Best Performance:
Trending markets with clear directional bias
Post-news volatility with defined structure
Markets respecting support/resistance levels
Avoid Trading When:
ADX indicator shows purple bars (ranging market)
Multiple conflicting signals across timeframes
Major news events without clear price structure
Low volume periods (market open/close)
Common Mistakes to Avoid
Ignoring the ADX filter - Taking signals during ranging markets leads to whipsaws
Not waiting for confirmation - Enter only when multiple layers align
Overtrading - Fewer high-quality setups outperform many mediocre ones
Ignoring risk management - Always use the calculated stop losses
Fighting the trend - Trade WITH the SuperTrend and Cirrus Cloud direction
TECHNICAL SPECIFICATIONS
Indicator Type: Overlay (plots on price chart)
Calculation Resources:
Max labels: 500
Max lines: 500
Max boxes: 500
Max bars back: 500
Pine Script Version: 5
Compatible Timeframes: All timeframes (optimized for 1m to 1D)
Compatible Instruments:
Forex pairs
Crypto assets
Stock indices
Individual stocks
Commodities
THEORETICAL FOUNDATION
Trend-Following Concepts
This indicator is based on the principle that markets trend more often than they range, and that trends tend to persist. The SuperTrend component captures this momentum while the range filters prevent premature entries during pullbacks.
Smart Money Theory
The SMC elements are based on the concept that institutional traders (banks, hedge funds) leave footprints in the form of:
Order Blocks: Areas where large orders were placed
Fair Value Gaps: Inefficient price movements that may be revisited
Liquidity Sweeps: Stop hunts before continuation (EQH/EQL)
Volatility-Based Position Sizing
Using ATR for stop-loss placement ensures that stop distances adapt to current market conditions:
Tight stops in low volatility (avoids excessive risk)
Wider stops in high volatility (avoids premature stop-outs)
PERFORMANCE EXPECTATIONS
Realistic Expectations
Win Rate:
Expected: 45-55% (trend-following systems rarely exceed 60%)
Higher win rates on trending days
Lower win rates during consolidation (even with ADX filter)
Risk-Reward Ratio:
Target: 1.5:1 minimum (TP2)
Achievable: 2:1 to 3:1 on strong trends
Drawdowns:
Normal: 10-15% of account during choppy periods
Maximum: Should not exceed 20% with proper risk management
Optimization Tips
Backtesting Recommendations:
Test on at least 1 year of historical data
Include different market conditions (trending, ranging, volatile)
Adjust SuperTrend sensitivity per instrument
Optimize ADX threshold for your specific market
Record trades to identify personal execution errors
FREQUENTLY ASKED QUESTIONS
Q: Can I use this for automated trading?
A: The indicator provides signals, but you'll need to code a strategy script separately for automation. The signals can trigger alerts that connect to trading bots.
Q: Why do I see conflicting signals?
A: This is normal during transition periods. Wait for all confirmation layers to align before entering.
Q: How often should I expect signals?
A: Depends on timeframe and market conditions. On 5m charts during trending markets: 3-7 quality setups per session.
Q: Can I use only some features?
A: Yes, all components can be toggled on/off. However, the system works best with all confirmations active.
Q: What's the difference between internal and swing structures?
A: Internal = minor price structures (smaller pivots). Swing = major price structures (larger pivots). Both provide different levels of confirmation.
DISCLAIMER
This indicator is a tool for technical analysis and should not be the sole basis for trading decisions. Past performance does not guarantee future results. Always:
Use proper risk management
Test on demo accounts first
Never risk more than you can afford to lose
Combine with fundamental analysis when applicable
Understand that no indicator is 100% accurate
License: Mozilla Public License 2.0
Author: DrFXGOD
VERSION HISTORY & UPDATES
Initial Release - Version 1.0
Integrated SuperTrend, Range Filters, ADX, SMC concepts
ATR-based risk management
Multi-timeframe support
Customizable visual elements
SUPPORT & DOCUMENTATION
For questions, suggestions, or bug reports, please comment on the script page or contact the author through TradingView.
Additional Resources:
Smart Money Concepts: Research ICT (Inner Circle Trader) materials
ATR and Volatility: Refer to Wilder's original ATR documentation
SuperTrend Indicator: Study original SuperTrend strategy papers
MACD-V Adaptive FluxProMACD-V Adaptive FluxPro
Type: Multi-Factor Volatility-Normalized Momentum & Regime Framework
Overlay: ✅ Yes (on price chart)
Purpose: Detect high-probability trend continuation or reversal zones through volatility-adjusted momentum, VWAP structure, and adaptive filters.
🧩 Concept Overview
MACD-V Adaptive FluxPro is a next-generation, multi-factor analytical framework that merges the principles of Linda Raschke’s 3-10-16 MACD with modern volatility normalization and adaptive filtering.
Instead of generating raw buy/sell signals, it builds a probability-driven environment model — showing when price action, volatility, and structure align for high-confidence trades.
The “V” in MACD-V stands for Volatility Normalization: every MACD component is divided by ATR to stabilize amplitude across fast or slow markets.
This enables the indicator to remain consistent across timeframes, instruments, and volatility regimes.
⚙️ Core Components
1️⃣ Volatility-Normalized MACD (MACD-V)
A traditional MACD built on Linda Raschke’s 3-10-16 structure, but adjusted by ATR to create a volatility-invariant momentum profile.
You can toggle to alternative presets (Scalp / Swing / Trend) for faster or slower environments.
2️⃣ Dynamic Regime Detection
A slope-based classifier that identifies whether the market is:
Trend Up 🟢
Trend Down 🔴
Compression / Squeeze 🟧
Transition / Neutral ⚫
The background color updates dynamically as momentum, volatility, and slope shift between these states.
3️⃣ VWAP Structure Bands
Adaptive VWAP with inner and outer ATR-scaled envelopes.
These act as short-term mean-reversion and breakout zones.
The indicator can optionally gate entries to occur only within defined VWAP proximity.
4️⃣ EMAs for Micro-Trend Confirmation
Includes 9-EMA and 21-EMA, color-configurable for visual crossovers and short-term momentum bias.
5️⃣ Multi-Timeframe Confirmation Tiles
Top-center dashboard tiles display directional bias from higher timeframes (e.g., 15m / 1h / 4h).
When all align, it confirms multi-frame trend coherence.
6️⃣ Adaptive Probability Engine
All subsystems — MACD-V, slope, compression, volume z-score, and VWAP distance — feed into a logistic scoring model that outputs a real-time AOI Probability (0-100%).
When conditions align, probabilities rise above 60% (long bias) or drop below 40% (short bias).
These are your high-probability “Areas of Interest.”
7️⃣ Dashboard HUD
The top-right status console provides a one-glance view of system state:
Field Meaning
AOI Prob Long Real-time probability of bullish bias
Regime Market state (Trend, Transition, Compression)
Risk Gate ATR-based volatility filter
News Mute Manual toggle for event-risk suppression
ATR (≈ risk) Real-time volatility readout
Status ✅ Trading OK / 🧱 Risk Gate / 🔇 News Mute / 🟧 Compression
🎯 Interpretation Guide
Visual Meaning
🟢 Green background Confirmed uptrend regime
🔴 Red background Confirmed downtrend regime
🟧 Orange background Volatility compression (squeeze forming)
⚫ Gray background Transitional / indecisive structure
Teal % (AOI Prob Long) Bullish probability > 60%
Arrows Optional: appear only when all gates align (rare, filtered signals)
🧮 Mathematical Notes
MACD-V = (EMA_fast(src) − EMA_slow(src)) / ATR(n)
Normalized score is smoothed, scaled 0–100 via logistic curve
Slope = Δ(EMA(src, n)) / ATR(n)
Probabilities gated by:
Minimum slope magnitude (minAbsSlope)
VWAP proximity (maxVWAPDistATR)
Multi-TF agreement
Cooldown interval (cooldownBars)
ATR-based risk gate
No repainting — all calculations use barstate.isconfirmed.
⚡ Use Cases
✅ Identify trend regime changes before major expansions
✅ Filter breakout vs. compression setups
✅ Quantify volatility conditions before entries
✅ Confirm multi-timeframe alignment
✅ Serve as a visual regime map for automated systems or discretionary traders
🧠 Recommended Presets
Market Type Setting Preset Behavior
Index Futures (ES/NQ) LBR 3-10-16 SMA (default) Classic swing/momentum balance
Scalping (1m–5m) Fast Adaptive Higher frequency, shorter cooldown
Swing Trading (1h–4h) Smooth ATR Broader, trend-only signals
Trend-Following Futures Wide ATR Bands Filters noise, favors strong continuation
⚠️ Notes
Non-repainting, bar-confirmed calculations
Signal arrows are optional and rare — intended for precision setups
ATR and slope thresholds should be tuned per instrument
Compatible with all TradingView markets and resolutions
🏁 Summary
“MACD-V Adaptive FluxPro” is not a simple MACD — it’s a volatility-normalized market state engine that adapts to changing conditions.
It fuses Linda Raschke’s timeless MACD logic with modern volatility, slope, and multi-timeframe analytics — giving you a live market dashboard that tells you when not to trade just as clearly as when you should.
Experimental Supertrend [CHE]Experimental Supertrend — Combines EMA crossovers for trend regime detection with an adaptive ATR-based hull that selects the narrowest band to contain recent highs and lows, minimizing false breaks in varying volatility.
Summary
This indicator overlays a dynamic supertrend boundary around a midline derived from dual EMAs, using EMA crossovers to switch between bullish and bearish regimes. The hull adapts by evaluating multiple ATR periods and selecting the tightest one that fully encloses price action over a specified window, which helps in creating more stable trend lines that hug price without excessive gaps or breaches. Fills between the midline and hull provide visual cues for trend strength, darkening temporarily after regime changes to highlight transitions. Alerts trigger on crossovers, and markers label entry points, making it suitable for trend-following setups where standard supertrends might whipsaw. Overall, it offers robustness through auto-adjustment, reducing sensitivity to noise while maintaining responsiveness to genuine shifts.
Motivation: Why this design?
Standard supertrend indicators often flip prematurely in choppy markets due to fixed multipliers that do not account for localized volatility patterns, leading to frequent false signals and eroded confidence in trends. This design addresses that by incorporating an EMA-based regime filter for directional bias and an auto-adaptive hull that dynamically tunes the band width based on recent price containment needs. By prioritizing the narrowest effective enclosure, it avoids over-wide bands in calm periods that cause lag or under-wide ones in volatility spikes that invite breaks, providing a more consistent trailing reference without manual tweaking.
What’s different vs. standard approaches?
- Reference baseline: Diverges from the classic ATR-multiplier supertrend, which uses a single fixed period and constant factor applied to close or high/low deviations.
- Architecture differences:
- Auto-selection from candidate ATR lengths to find the optimal period for current conditions.
- Dynamic multiplier clamped between floor and cap values, adjusted by padding to ensure reliable containment.
- Regime-gated rendering, where hull position flips based on EMA relative positioning.
- Post-transition visual fading to emphasize change points without altering core logic.
- Practical effect: Charts show tighter, more reactive bands that rarely breach during trends, reducing visual clutter from flips; the adaptive nature means less intervention across assets, as the hull self-adjusts to volatility clusters rather than applying a one-size-fits-all scale.
How it works (technical)
The indicator first computes two EMAs from close prices using lengths derived from a preset pair or manual inputs, establishing a midline as their average. This midline serves as the central reference for the hull. True range values are then smoothed into multiple ATR candidates using exponential weighting over the specified lengths. For each candidate, deviations of recent highs and lows from the midline are ratioed against the ATR to determine a required multiplier that would enclose all extremes in the containment window—the highest ratio plus padding sets the base, clamped to user-defined bounds. Among valid candidates (those with sufficient history), the one yielding the narrowest overall band width is selected. The hull boundaries are then offset from the midline by this multiplier times the chosen ATR, and further smoothed with a fixed EMA to reduce jitter. Regime direction from EMA comparison gates which boundary acts as support or resistance, with initialization seeding arrays on the first bar to handle state persistence. No higher timeframe data is used, so all logic runs on the chart's native bars without lookahead.
Parameter Guide
EMA Pair — Selects preset lengths for fast and slow EMAs, influencing regime sensitivity and midline stability. Default: "21/55". Trade-offs/Tips: Faster pairs like "9/21" increase cross frequency for scalping but raise false signals; slower like "50/200" smooths for swings, potentially missing early turns. Use Manual for fine control.
Manual Fast — Sets fast EMA length when Manual mode is active; shorter values make regime switches quicker. Default: 21. Trade-offs/Tips: Lower than 10 risks over-reactivity; pair with slow at least double for clear separation.
Manual Slow — Sets slow EMA length when Manual mode is active; longer values anchor the midline more firmly. Default: 55. Trade-offs/Tips: Above 100 adds lag in trends; balance with fast to avoid perpetual neutrality.
ATR Lengths (comma-separated) — Defines candidate periods for ATR smoothing; more options allow finer auto-selection. Default: "7,10,14,21,28,35". Trade-offs/Tips: Fewer candidates speed computation but may miss optimal fits; keep under 10 for efficiency.
Containment Window — Number of recent bars the hull must fully enclose highs/lows of; larger windows favor stability. Default: 50. Trade-offs/Tips: Shorter (under 20) adapts faster to breaks but increases breach risk; longer smooths but delays response.
Min Multiplier Floor — Lowest allowed multiplier for hull width; prevents overly tight bands in low volatility. Default: 0.5. Trade-offs/Tips: Raise to 0.75 for conservative enclosures; too low allows pinches that flip easily.
Max Multiplier Cap — Highest allowed multiplier; caps expansion in spikes to avoid wide, lagging bands. Default: 1.0. Trade-offs/Tips: Lower to 0.75 tightens overall; higher permits more room but risks detachment from price.
Padding (+) — Adds buffer to the auto-multiplier for safer containment without exact touches. Default: 0.05. Trade-offs/Tips: Increase to 0.10 in gappy markets; minimal values hug closer but may still breach on outliers.
Fill Between (Mid ↔ Supertrend) — Toggles shaded area between midline and active hull for trend visualization. Default: true. Trade-offs/Tips: Disable for cleaner charts; pairs well with transparency tweaks.
Base Fill Transparency (0..100) — Sets default opacity of fills; higher values make them subtler. Default: 80. Trade-offs/Tips: Under 50 overwhelms price action; adjust with darken boost for emphasis.
Darken on Trend Change — Enables temporary opacity increase after regime shifts to spotlight transitions. Default: true. Trade-offs/Tips: Off for steady visuals; on aids spotting reversals in real-time.
Darken Fade Bars — Duration in bars for the darken effect to ramp back to base; longer prolongs highlight. Default: 8. Trade-offs/Tips: Shorter (4-6) for fast-paced charts; longer holds attention on changes.
Darken Boost at Change (Δ transp) — Intensity of opacity reduction at crossover; higher values make shifts more prominent. Default: 50. Trade-offs/Tips: Cap at 70 to avoid blackout; tune down if fades obscure details.
Show Supertrend Line — Displays the active hull boundary as a line. Default: true. Trade-offs/Tips: Hide for fill-only views; linewidth fixed at 3 for visibility.
Show EMA Cross Markers — Places circles and labels at crossover points for entry cues. Default: true. Trade-offs/Tips: Disable in clutter; labels show "Buy"/"Sell" at absolute positions.
Alert: EMA Cross Up (Long) — Triggers notification on bullish crossover. Default: true. Trade-offs/Tips: Pair with filters; once-per-bar frequency.
Alert: EMA Cross Down (Short) — Triggers notification on bearish crossover. Default: true. Trade-offs/Tips: Use for exits; ensure broker integration.
Show Debug — Reveals internal diagnostics like selected ATR details (if implemented). Default: false. Trade-offs/Tips: Enable for troubleshooting selections; minimal overhead.
Reading & Interpretation
Bullish regime shows a green line below price as support, with upward fill from midline; bearish uses red line above as resistance, downward fill. Crossovers flip the active boundary, marked by tiny green/red circles and "Buy"/"Sell" labels at the hull level. Fills start at base transparency but darken sharply at changes, fading over the specified bars to signal fresh momentum. If the hull rarely breaches during trends, containment is effective; frequent touches without flips indicate tight adaptation. Debug mode (when enabled) overlays text or plots for selected length and multiplier, helping verify auto-choices.
Practical Workflows & Combinations
- Trend following: Enter long on green "Buy" label above prior low structure; confirm with higher high. Trail stops along the green hull line, tightening as fills stabilize post-fade.
- Exits/Stops: Conservative exit on opposite crossover or hull breach; aggressive hold until fade completes if volume supports. Use darken boost as a volatility cue—high delta suggests waiting for confirmation.
- Multi-asset/Multi-TF: Defaults suit forex/stocks on 15m-4h; for crypto, widen containment to 75 for gaps. Layer on volume oscillator for cross filters; avoid on low-liquidity assets where ATR candidates skew.
Behavior, Constraints & Performance
Closed-bar logic ensures signals confirm at bar end, with live bars updating hull adaptively but no repaints since no future data or security calls are used. Arrays persist ATR states across bars, initialized once with candidates parsed from string. Small fixed loops (over 6 lengths max, inner up to 50) run per bar, capped by max_bars_back=500 for history needs. Resources stay low with 500 labels/lines limits, but dense charts may hit on markers. Known limits include initial lag until containment history builds (50+ bars), potential wide bands on gaps, and suboptimal selections if candidates omit ideal lengths.
Sensible Defaults & Quick Tuning
Start with "21/55" pair, 50-window, 0.5-1.0 multipliers, and 80% transparency for balanced responsiveness on daily charts. For too many flips, raise min floor to 0.75 or add lengths like "42"; for sluggishness, shorten window to 30 or pick faster pair. In high-vol environments, boost padding to 0.10; for smoother visuals, extend fade bars to 12.
What this indicator is—and isn’t
This is a visualization and signal layer for trend regime and adaptive boundaries, aiding entry/exit timing in directional markets. It is not a standalone system—pair with price structure, risk sizing, and broader context. Not predictive of turns, just reactive to containment and crosses.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Happy trading
Chervolino
Smart Structure Pro - Market Structure & Smart Money Concepts═══════════════════════════════════════════════════════════════════════════════
SMART STRUCTURE PRO
═══════════════════════════════════════════════════════════════════════════════
A comprehensive market structure analysis tool that identifies institutional trading
patterns and smart money concepts for improved trade timing and decision-making.
═══════════════════════════════════════════════════════════════════════════════
📊 WHAT IT DOES
═══════════════════════════════════════════════════════════════════════════════
This indicator automatically detects and visualizes key market structure elements:
🔹 BOS (Break of Structure)
- Identifies trend continuation patterns
- Marks when price breaks above previous highs (bullish) or below previous lows (bearish)
- Confirms trend strength and momentum
🔹 CHoCH (Change of Character)
- Detects potential trend reversals
- Alerts when market structure shifts from bullish to bearish or vice versa
- Helps identify early reversal opportunities
🔹 Order Blocks
- Highlights institutional entry zones
- Identifies the last opposite candle before a structure break
- Shows areas where smart money likely entered positions
🔹 Fair Value Gaps (FVG)
- Detects price imbalances and inefficiencies
- Shows areas where price moved rapidly leaving gaps
- Often act as support/resistance when retested
🔹 Liquidity Zones
- Marks swing high and low levels
- Identifies areas where stop losses likely cluster
- Shows potential stop hunt and liquidity grab zones
═══════════════════════════════════════════════════════════════════════════════
🎯 HOW TO USE
═══════════════════════════════════════════════════════════════════════════════
BULLISH SETUP:
1. Wait for Bullish CHoCH (trend reversal signal) or BOS ↑ (continuation)
2. Look for price to pull back into an Order Block or Fair Value Gap
3. Enter long when price bounces from these zones
4. Place stop loss below the Order Block
5. Target the next liquidity zone or resistance level
BEARISH SETUP:
1. Wait for Bearish CHoCH (trend reversal signal) or BOS ↓ (continuation)
2. Look for price to retrace into an Order Block or Fair Value Gap
3. Enter short when price rejects from these zones
4. Place stop loss above the Order Block
5. Target the next liquidity zone or support level
DASHBOARD INTERPRETATION:
• Trend: Current market direction (Bullish/Bearish)
• Volume: Confirmation strength (High volume = stronger signals)
• Signal: Latest structure break detected
• Key High/Low: Critical levels for the current trend
• Position: Price location (Premium = expensive, Discount = cheap)
═══════════════════════════════════════════════════════════════════════════════
⚙️ SETTINGS GUIDE
═══════════════════════════════════════════════════════════════════════════════
STRUCTURE DETECTION:
• Pivot Length (Default: 10)
- Lower values = More signals but potentially weaker
- Higher values = Fewer signals but stronger/more reliable
- Recommended: 8-12 for intraday, 10-15 for higher timeframes
• Structure Line Extension
- Visual preference for how far lines extend
- Does not affect signal detection
SMART MONEY CONCEPTS:
• Order Block Extension: How long OB boxes remain visible
• FVG Extension: How long gap boxes remain visible
• Min FVG Size: Filter out small gaps (0 = show all)
- Set to 10-20% to reduce noise
- Set to 0 to see all gaps
VOLUME FILTER:
• Volume Confirmation (Recommended: ON)
- Filters weak signals without volume support
- Reduces false breakouts
• Volume Multiplier (Default: 1.5)
- Higher = Stricter filtering (fewer but stronger signals)
- Lower = More signals (but may include weak ones)
DISPLAY:
• Dashboard: Toggle information panel
• Trend Background: Subtle color tint showing current trend
• Dashboard Position: Choose corner placement
═══════════════════════════════════════════════════════════════════════════════
🔔 ALERTS
═══════════════════════════════════════════════════════════════════════════════
Available alert conditions:
✓ Bullish BOS - Uptrend continuation confirmed
✓ Bearish BOS - Downtrend continuation confirmed
✓ Bullish CHoCH - Reversal to uptrend detected
✓ Bearish CHoCH - Reversal to downtrend detected
✓ Structure Break - Any significant market structure change
To set up alerts:
1. Click the "⏰" alert icon
2. Select "Smart Structure Pro"
3. Choose your desired condition
4. Configure notification method
5. Click "Create"
═══════════════════════════════════════════════════════════════════════════════
⚠️ IMPORTANT DISCLOSURES
═══════════════════════════════════════════════════════════════════════════════
REPAINTING BEHAVIOR:
• Pivot points WILL repaint until confirmed (this is by design and unavoidable)
• Structure breaks (BOS/CHoCH) use CLOSED candles and do NOT repaint after confirmation
• Order Blocks and FVGs are drawn on confirmed signals and do NOT repaint
• All signals wait for candle close before triggering
BEST PRACTICES:
• Use on higher timeframes (15min+) for more reliable signals
• Combine with other analysis (support/resistance, volume profile, etc.)
• Wait for candle close confirmation before acting on signals
• Use proper risk management - this is not a standalone trading system
• Backtest on your preferred instrument and timeframe
PERFORMANCE:
• Limited to 100 boxes, 100 lines, 100 labels for optimal performance
• Older objects automatically removed as new ones appear
• Works on all markets (Forex, Crypto, Stocks, Indices, Commodities)
═══════════════════════════════════════════════════════════════════════════════
📚 CONCEPTS EXPLAINED
═══════════════════════════════════════════════════════════════════════════════
MARKET STRUCTURE:
Market structure refers to the pattern of price movements creating swing highs
and lows. Understanding structure helps identify trend direction and potential
reversal points.
SMART MONEY CONCEPTS:
These are trading techniques based on tracking institutional order flow and
understanding where large players (banks, funds, institutions) enter and exit
positions.
ORDER BLOCKS:
The last opposing candle before a strong directional move. Institutions often
leave unfilled orders in these zones, which can act as support/resistance when
price returns.
FAIR VALUE GAPS:
Areas where price moved so quickly that it left an imbalance. These gaps often
get "filled" as price returns to find equilibrium, creating trading opportunities.
═══════════════════════════════════════════════════════════════════════════════
🎓 EDUCATIONAL VALUE
═══════════════════════════════════════════════════════════════════════════════
This indicator helps traders:
✓ Understand market structure mechanics
✓ Identify institutional trading patterns
✓ Improve trade timing and entry precision
✓ Recognize trend continuation vs reversal
✓ Learn smart money concepts through visualization
═══════════════════════════════════════════════════════════════════════════════
📋 TECHNICAL DETAILS
═══════════════════════════════════════════════════════════════════════════════
• Version: 1.0.0
• Pine Script Version: 5
• Indicator Type: Overlay
• No Repainting: Structure breaks use confirmed candles
• Performance Optimized: Limited drawing objects
• Works On: All markets and timeframes
• Alerts: Yes, fully customizable
═══════════════════════════════════════════════════════════════════════════════
👤 AUTHOR
═══════════════════════════════════════════════════════════════════════════════
Created by: Zakaria Safri
Original Work: All code and concepts are original implementations
Based On: ICT (Inner Circle Trader) educational concepts
License: © 2024 Zakaria Safri - Personal Use Only
═══════════════════════════════════════════════════════════════════════════════
⚖️ DISCLAIMER
═══════════════════════════════════════════════════════════════════════════════
This indicator is for educational and informational purposes only. It does not
constitute financial advice. Trading involves substantial risk of loss. Past
performance does not guarantee future results. Always conduct your own research
and consult with a licensed financial advisor before making trading decisions.
The author is not responsible for any losses incurred from using this indicator.
═══════════════════════════════════════════════════════════════════════════════
If you find this indicator helpful, please:
👍 Like and favorite
⭐ Leave a review
📢 Share with other traders
💬 Comment with feedback or suggestions
Happy Trading! 📈
nadia
Gold ramon strategy based on 50 candles and atr of 12
You enter the maximum of 50 candles once the most bearish starts to rise, we expect 10 candles, if you don't go up in 10 candles, you don't enter, if you go up before 10 candles, you enter.
When is TP? Enough with 5 candles
The temporality is 1 hour. It can be adjusted to 1 minute temporality for scalping.
It is never lost, because it always exceeds the previous maximums.
Daily Levels: PD / PM / OR (RTH/Pre)# Daily Levels: PD / PM / OR (RTH/Pre)
## Overview
This indicator displays key intraday support and resistance levels for US equity markets, specifically designed for traders who use Previous Day, Pre-Market, and Opening Range levels in their trading strategy.
## Key Features
**Seven Critical Levels Displayed:**
- **PDH (Previous Day High)** - Blue line: The highest price from yesterday's regular trading hours (9:30 AM - 4:00 PM ET)
- **PDL (Previous Day Low)** - Blue line: The lowest price from yesterday's regular trading hours
- **PDC (Previous Day Close)** - Orange line: The closing price from yesterday's regular trading hours
- **PMH (Pre-Market High)** - Yellow line: The highest price during today's pre-market session (4:00 AM - 9:30 AM ET)
- **PML (Pre-Market Low)** - Yellow line: The lowest price during today's pre-market session
- **ORH (Opening Range High)** - Red line: The highest price during the first 30 minutes of trading (9:30 AM - 10:00 AM ET)
- **ORL (Opening Range Low)** - Red line: The lowest price during the first 30 minutes of trading
## How It Works
**At 9:30 AM ET (Market Open):**
- PDH, PDL, PDC levels appear (from previous day's RTH)
- PMH, PML levels appear (from today's pre-market session)
- All lines begin at the 9:30 AM bar and extend right
**At 10:00 AM ET (Opening Range Close):**
- ORH, ORL levels appear (from today's first 30 minutes)
- Lines begin at the 9:30 AM bar and extend right
**Level Persistence:**
- All levels remain visible until the next trading day at 9:30 AM ET
- Levels reset daily for the new trading session
## Use Cases
**Day Trading:**
- Identify key support and resistance zones before placing trades
- Use PDH/PDL as potential profit targets or stop loss areas
- Monitor price reaction at pre-market levels for early trading signals
- Trade breakouts or rejections at opening range levels
**Swing Trading:**
- Assess daily momentum by observing breaks above/below previous day levels
- Use multiple timeframes while maintaining consistent reference points
**Market Structure:**
- Quickly identify if the market is trading above or below key levels
- Recognize accumulation/distribution patterns around these zones
## Technical Details
- **Timezone:** All times referenced are US Eastern Time (America/New_York)
- **Session Windows:**
- Pre-Market: 4:00 AM - 9:30 AM ET
- Regular Trading Hours: 9:30 AM - 4:00 PM ET
- Opening Range: 9:30 AM - 10:00 AM ET
- **Timeframe Agnostic:** Works on any chart timeframe
- **Visual Clarity:** Color-coded lines and labels for easy identification
## Color Scheme
- **Blue:** Previous Day levels (PDH, PDL)
- **Orange:** Previous Day Close (PDC)
- **Yellow:** Pre-Market levels (PMH, PML)
- **Red:** Opening Range levels (ORH, ORL)
## Best Practices
1. Use on US equity indices (SPY, QQQ, ES, NQ) and liquid US stocks
2. Combine with volume analysis for confirmation
3. Pay attention to how price reacts at these levels (bounce vs. break)
4. Most effective during the first 2 hours of trading when volatility is highest
5. Consider the market context (trending vs. ranging) when interpreting these levels
## Note
This indicator is specifically designed for US market hours. Results may vary when applied to international markets or instruments with different trading sessions.
Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
• Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
• Timeframes. One minute to daily
• Default demo used in the publication. QQQ on one hour
• Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
• What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
• Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
• Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
• Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
• Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
• Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
• Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
• Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
• Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
• Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
• Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
• Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
• The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
• Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
• Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
• Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
• When polarity flips from plus to minus, the strategy closes any long and enters a short.
• When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
• White polarity plot around the zero line
• A dotted reference line at zero named Zen
• Green background tint for positive polarity and red background tint for negative polarity
• Strategy long and short markers placed by the TradingView engine at entry and at close conditions
• No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
• Price source. Default ohlc4. Stable for noisy symbols.
• Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
• Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
• Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
• Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
• Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
• Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
• Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
• Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
• Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
• Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
• Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
• Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
• Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
• Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
• Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
• This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
• Initial capital 25000
• Base currency Default
• Default order size method percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Honest limitations and failure modes
• Past results do not guarantee future outcomes
• Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
• Gap heavy symbols may benefit from the MAD Z normalization
• Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
• Session time is the exchange time of the chart
• If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
• None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
• Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
• Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
• Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
• Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
• Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
• Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
• Initial capital 25000
• Base currency Default
• Default order size percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Dataset and sample size
• Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
• Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
• Add alertcondition lines for long, short, and exit short
• Add optional table with component readouts
• Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
