Multi-Symbol Volatility Tracker with Range DetectionMulti-Symbol Volatility Tracker with Range Detection
🎯 Main Purpose:
This indicator is specifically designed for scalpers to quickly identify symbols with high volatility that are currently in ranging conditions . It helps you spot the perfect opportunities for buying at lows and selling at highs repeatedly within the same trading session.
📊 Table Data Explanation:
The indicator displays a comprehensive table with 5 columns for 4 major symbols (GOLD, SILVER, NASDAQ, SP500):
SYMBOL: The trading instrument being analyzed
VOLATILITY: Color-coded volatility levels (NORMAL/HIGH/EXTREME) based on ATR values
Last Candle %: The percentage range of the most recent 5-minute candle
Last 5 Candle Avg %: Average percentage range over the last 5 candles
RANGE: Shows "YES" (blue) or "NO" (gray) indicating if the symbol is currently ranging
🔍 How to Identify Trading Opportunities:
Look for symbols that combine these characteristics:
RANGE column shows "YES" (highlighted in blue) - This means the symbol is moving sideways, perfect for range trading
VOLATILITY shows "HIGH" or "EXTREME" - Ensures there's enough movement for profitable scalping
Higher candlestick percentages - Indicates larger candle ranges, meaning more profit potential per trade
⚡ Optimal Usage:
Best Timeframe: Works optimally on 5-minute charts where the ranging patterns are most reliable for scalping
Trading Strategy: When you find a symbol with "YES" in the RANGE column, switch to that symbol and look for opportunities to buy near the lows and sell near the highs of the ranging pattern
Risk Management: Higher volatility symbols offer more profit potential but require tighter risk management
⚙️ Settings:
ATR Length: Adjusts the Average True Range calculation period (default: 14)
Range Sensitivity: Fine-tune range detection sensitivity (0.1-2.0, lower = more sensitive)
💡 Pro Tips:
The indicator updates in real-time, so monitor for symbols switching from "NO" to "YES" in the RANGE column
Combine HIGH/EXTREME volatility with RANGE: YES for the most profitable scalping setups
Use the candlestick percentages to gauge potential profit per trade - higher percentages mean more movement
The algorithm uses advanced statistical analysis including standard deviation, linear regression slopes, and range efficiency to accurately detect ranging conditions
Perfect for day traders and scalpers who want to quickly identify which symbols offer the best ranging opportunities for consistent buy-low, sell-high strategies.
Indikator dan strategi
Opening Range IndicatorComplete Trading Guide: Opening Range Breakout Strategy
What Are Opening Ranges?
Opening ranges capture the high and low prices during the first few minutes of market open. These levels often act as key support and resistance throughout the trading day because:
Heavy volume occurs at market open as overnight orders execute
Institutional activity is concentrated during opening minutes
Price discovery happens as market participants react to overnight news
Psychological levels are established that traders watch all day
Understanding the Three Timeframes
OR5 (5-Minute Range: 9:30-9:35 AM)
Most sensitive - captures immediate market reaction
Quick signals but higher false breakout rate
Best for scalping and momentum trading
Use for early entry when conviction is high
OR15 (15-Minute Range: 9:30-9:45 AM)
Balanced approach - most popular among day traders
Moderate sensitivity with better reliability
Good for swing trades lasting several hours
Primary timeframe for most strategies
OR30 (30-Minute Range: 9:30-10:00 AM)
Most reliable but slower signals
Lower false breakout rate
Best for position trades and trend following
Use when looking for major moves
Core Trading Strategies
Strategy 1: Basic Breakout
Setup:
Wait for price to break above OR15 high or below OR15 low
Enter on the breakout candle close
Stop loss: Opposite side of the range
Target: 2-3x the range size
Example:
OR15 range: $100.00 - $102.00 (Range = $2.00)
Long entry: Break above $102.00
Stop loss: $99.50 (below OR15 low)
Target: $104.00+ (2x range size)
Strategy 2: Multiple Confirmation
Setup:
Wait for OR5 break first (early signal)
Confirm with OR15 break in same direction
Enter on OR15 confirmation
Stop: Below OR30 if available, or OR15 opposite level
Why it works:
Multiple timeframe confirmation reduces false signals and increases probability of sustained moves.
Strategy 3: Failed Breakout Reversal
Setup:
Price breaks OR15 level but fails to hold
Wait for re-entry into the range
Enter reversal trade toward opposite OR level
Stop: Recent breakout high/low
Target: Opposite side of range + extension
Key insight: Failed breakouts often lead to strong moves in the opposite direction.
Advanced Techniques
Range Quality Assessment
High-Quality Ranges (Trade these):
Range size: 0.5% - 2% of stock price
Clean boundaries (not choppy)
Volume spike during range formation
Clear rejection at range levels
Low-Quality Ranges (Avoid these):
Very narrow ranges (<0.3% of stock price)
Extremely wide ranges (>3% of stock price)
Choppy, overlapping candles
Low volume during formation
Volume Confirmation
For Breakouts:
Look for volume spike (2x+ average) on breakout
Declining volume often signals false breakout
Rising volume during range formation shows interest
Market Context Filters
Best Conditions:
Trending market days (SPY/QQQ with clear direction)
Earnings reactions or news-driven moves
High-volume stocks with good liquidity
Volatility above average (VIX considerations)
Avoid Trading When:
Extremely low volume days
Major economic announcements pending
Holidays or half-days
Choppy, sideways market conditions
Risk Management Rules
Position Sizing
Conservative: Risk 0.5% of account per trade
Moderate: Risk 1% of account per trade
Aggressive: Risk 2% maximum per trade
Stop Loss Placement
Inside the range: Quick exit but higher stop-out rate
Outside opposite level: More room but larger risk
ATR-based: 1.5-2x Average True Range below entry
Profit Taking
Target 1: 1x range size (take 50% off)
Target 2: 2x range size (take 25% off)
Runner: Trail remaining 25% with moving stops
Specific Entry Techniques
Breakout Entry Methods
Method 1: Immediate Entry
Enter as soon as price closes above/below range
Fastest entry but highest false signal rate
Best for strong momentum situations
Method 2: Pullback Entry
Wait for breakout, then pullback to range level
Enter when price bounces off former resistance/support
Better risk/reward but may miss some moves
Method 3: Volume Confirmation
Wait for breakout + volume spike
Enter after volume confirmation candle
Reduces false signals significantly
Multiple Timeframe Entries
Aggressive: OR5 break → immediate entry
Conservative: OR5 + OR15 + OR30 all align → enter
Balanced: OR15 break with OR30 support → enter
Common Mistakes to Avoid
1. Trading Poor-Quality Ranges
❌ Don't trade ranges that are too narrow or too wide
✅ Focus on clean, well-defined ranges with good volume
2. Ignoring Volume
❌ Don't chase breakouts without volume confirmation
✅ Always check for volume spike on breakouts
3. Over-Trading
❌ Don't force trades when ranges are unclear
✅ Wait for high-probability setups only
4. Poor Risk Management
❌ Don't risk more than planned or use tight stops in volatile conditions
✅ Stick to predetermined risk levels
5. Fighting the Trend
❌ Don't fade breakouts in strongly trending markets
✅ Align trades with overall market direction
Daily Trading Routine
Pre-Market (8:00-9:30 AM)
Check overnight news and earnings
Review major indices (SPY, QQQ, IWM)
Identify potential opening range candidates
Set alerts for range breakouts
Market Open (9:30-10:00 AM)
Watch opening range formation
Note volume and price action quality
Mark key levels on charts
Prepare for breakout signals
Trading Session (10:00 AM - 4:00 PM)
Execute breakout strategies
Manage existing positions
Trail stops as profits develop
Look for additional setups
Post-Market Review
Analyze winning and losing trades
Review range quality vs. outcomes
Identify improvement areas
Prepare for next session
Best Stocks/ETFs for Opening Range Trading
Large Cap Stocks (Best for beginners):
AAPL, MSFT, GOOGL, AMZN, TSLA
High liquidity, predictable behavior
Good range formation most days
ETFs (Consistent patterns):
SPY, QQQ, IWM, XLF, XLE
Excellent liquidity
Clear range boundaries
Mid-Cap Growth (Advanced traders):
Stocks with good volume (1M+ shares daily)
Recent news catalysts
Clean technical patterns
Performance Optimization
Track These Metrics:
Win rate by range type (OR5 vs OR15 vs OR30)
Average R/R (risk vs reward ratio)
Best performing market conditions
Time of day performance
Continuous Improvement:
Keep detailed trade journal
Review failed breakouts for patterns
Adjust position sizing based on win rate
Refine entry timing based on backtesting
Final Tips for Success
Start small - Paper trade or use tiny positions initially
Focus on quality - Better to miss trades than take bad ones
Stay disciplined - Stick to your rules even during losing streaks
Adapt to conditions - What works in trending markets may fail in choppy conditions
Keep learning - Markets evolve, so should your approach
The opening range strategy is powerful because it captures natural market behavior, but like all strategies, it requires practice, discipline, and proper risk management to be profitable long-term.
Foresight Cone (HoltxF1xVWAP) [KedArc Quant]Description:
This is a time-series forecasting indicator that estimates the next bar (F1) and projects a path a few bars ahead. It also draws a confidence cone based on how accurate the recent forecasts have been. You can optionally color the projection only when price agrees with VWAP.
Why it’s different
* One clear model: Everything comes from Holt’s trend-aware forecasting method—no mix of unrelated indicators.
* Transparent visuals: You see the next-bar estimate (F1), the forward projection, and a cone that widens or narrows based on recent forecast error.
* Context, not signals: The VWAP option only changes colors. It doesn’t add trade rules.
* No look-ahead: Accuracy is measured using the forecast made on the previous bar versus the current bar.
Inputs (what they mean)
* Source: Price series to forecast (default: Close).
* Preset: Quick profiles for fast, smooth, or momentum markets (see below).
* Alpha (Level): How fast the model reacts to new prices. Higher = faster, twitchier.
* Beta (Trend): How fast the model updates the slope. Higher = faster pivots, more flips in chop.
* Horizon: How many bars ahead to project. Bigger = wider cone.
* Residual Window: How many bars to judge recent accuracy. Bigger = steadier cone.
* Confidence Z: How wide the cone should be (typical setting ≈ “95% style” width).
* Show Bands / Draw Forward Path: Turn the cone and forward lines on/off.
* Color only when aligned with VWAP: Highlights projections only when price agrees with the trend side of VWAP.
* Colors / Show Panel: Styling plus a small panel with RMSE, MAPE, and trend slope.
Presets (when to pick which)
* Scalp / Fast (1-min): Very responsive; best for quick moves. More twitch in chop.
* Smooth Intraday (1–5 min): Calmer and steadier; a good default most days.
* Momentum / Breakout: Quicker slope tracking during strong pushes; may over-react in ranges.
* Custom: Set your own values if you know exactly what you want.
What is F1 here?
F1 is the model’s next-bar fair value. Crosses of price versus F1 can hint at short-term momentum shifts or mean-reversion, especially when viewed with VWAP or the cone.
How this helps
* Gives a baseline path of where price may drift and a cone that shows normal wiggle room.
* Helps you tell routine noise (inside cone) from information (edges or breaks outside the cone).
* Keeps you aware of short-term bias via the trend slope and F1.
How to use (step by step)
1. Add to chart → choose a Preset (start with Smooth Intraday).
2. Set Horizon around 8–15 bars for intraday.
3. (Optional) Turn on VWAP alignment to color only when price agrees with the trend side of VWAP.
4. Watch where price sits relative to the cone and F1:
* Inside = normal noise.
* At edges = stretched.
* Outside = possible regime change.
5. Check the panel: if RMSE/MAPE spike, expect a wider cone; consider a smoother preset or a higher timeframe.
6. Tweak Alpha/Beta only if needed: faster for momentum, slower for chop.
7. Combine with your own plan for entries, exits, and risk.
Accuracy Panel — what it tells you
Preset & Horizon: Shows which preset you’re using and how many bars ahead the projection goes. Longer horizons mean more uncertainty.
RMSE (error in price units): A “typical miss” measured in the chart’s currency (e.g., ₹).
Lower = tighter fit and a usually narrower cone. Rising = conditions getting noisier; the cone will widen.
MAPE (error in %): The same idea as RMSE but in percent.
Good for comparing different symbols or timeframes. Sudden spikes often hint at a regime change.
Slope T: The model’s short-term trend reading.
Positive = gentle up-bias; negative = gentle down-bias; near zero = mostly flat/drifty.
How to read it at a glance
Calm & directional: RMSE/MAPE steady or falling + Slope T positive (or negative) → trends tend to respect the cone’s mid/upper (or mid/lower) area.
Choppy/uncertain: RMSE/MAPE climbing or jumping → expect more whipsaw; rely more on the cone edges and higher-TF context.
Flat tape: Slope T near zero → mean-revert behavior is common; treat cone edges as stretch zones rather than breakout zones.
Warm-up & tweaks
Warm-up: Right after adding the indicator, the panel may be blank for a short time while it gathers enough bars.
Too twitchy? Switch to Smooth Intraday or increase the Residual Window.
Too slow? Use Scalp/Fast or Momentum/Breakout to react quicker.
Timeframe tips
* 1–3 min: Scalp/Fast or Momentum/Breakout; horizon \~8–12.
* 5–15 min: Smooth Intraday; horizon \~12–15.
* 30–60 min+: Consider a larger residual window for a steadier cone.
FAQ
Q: Is this a strategy or an indicator?
A: It’s an indicator only. It does not place orders, TP/SL, or run backtests.
Q: Does it repaint?
A: The next-bar estimate (F1) and the cone are calculated using only information available at that time. The forward path is a projection drawn on the last bar and will naturally update as new bars arrive. Historical bars aren’t revised with future data.
Q: What is F1?
A: F1 is the indicator’s best guess for the next bar.
Price crossing above/below F1 can hint at short-term momentum shifts or mean-reversion.
Q: What do “Alpha” and “Beta” do?
A: Alpha controls how fast the indicator reacts to new prices
(higher = faster, twitchier). Beta controls how fast the slope updates (higher = quicker pivots, more flips in chop).
Q: Why does the cone width change?
A: It reflects recent forecast accuracy. When the market gets noisy, the cone widens. When the tape is calm, it narrows.
Q: What does the Accuracy Panel tell me?
A:
* Preset & Horizon you’re using.
* RMSE: typical forecast miss in price units.
* MAPE: typical forecast miss in percent.
* Slope T: short-term trend reading (up, down, or flat).
If RMSE/MAPE rise, expect a wider cone and more whipsaw.
Q: The panel shows “…” or looks empty. Why?
A: It needs a short warm-up to gather enough bars. This is normal after you add the indicator or change settings/timeframes.
Q: Which timeframe is best?
A:
* 1–3 min: Scalp/Fast or Momentum/Breakout, horizon \~8–12.
* 5–15 min: Smooth Intraday, horizon \~12–15.
Higher timeframes work too; consider a larger residual window for steadier cones.
Q: Which preset should I start with?
A: Start with Smooth Intraday. If the market is trending hard, try Momentum/Breakout.
For very quick tapes, use Scalp/Fast. Switch back if things get choppy.
Q: What does the VWAP option do?
A: It only changes colors (highlights when price agrees with the trend side of VWAP).
It does not add or remove signals.
Q: Are there alerts?
A: Yes—alerts for price crossing F1 (up/down). Use “Once per bar close” to reduce noise on fast charts.
Q: Can I use this on stocks, futures, crypto, or FX?
A: Yes. It works on any symbol/timeframe. You may want to adjust Horizon and the Residual Window based on volatility.
Q: Can I use it with Heikin Ashi or other non-standard bars?
A: You can, but remember you’re forecasting the synthetic series of those bars. For pure price behavior, use regular candles.
Q: The cone feels too wide/too narrow. What do I change?
A:
* Too wide: lower Alpha/Beta a bit or increase the Residual Window.
* Too narrow (misses moves): raise Alpha/Beta slightly or try Momentum/Breakout.
Q: Why do results change when I switch timeframe or symbol?
A: Different noise levels and trends. The accuracy stats reset per chart, so the cone adapts to each context.
Q: Any limits or gotchas?
A: Extremely large Horizon may hit TradingView’s line-object limits; reduce Horizon or turn
off extra visuals if needed. Big gaps or news spikes will widen errors—expect the cone to react.
Q: Can this predict exact future prices?
A: No. It provides a baseline path and context. Always combine with your own rules and risk management.
Glossary
* TS (Time Series): Data over time (prices).
* Holt’s Method: A forecasting approach that tracks a current level and a trend to predict the next bars.
* F1: The indicator’s best guess for the next bar.
* F(h): The projected value h bars ahead.
* VWAP: Volume-Weighted Average Price—used here for optional color alignment.
* RMSE: Typical forecast miss in price units (how far off, on average).
* MAPE: Typical forecast miss in percent (scale-free, easy to compare).
Notes & limitations
* The panel needs a short warm-up; stats may be blank at first.
* The cone reflects recent conditions; sudden volatility changes will widen it.
* This is a tool for context. It does not place trades and does not promise results.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
CNagda Anchor2EntryCNagda Anchor2Entry Pine Script v6 overlay indicator pulls higher-timeframe (HTF) signal events to define anchor high/low levels and then projects visual entry labels on the lower-timeframe (LTF). It also draws auto-oriented Fibonacci retracement/extension levels for context, but it does not execute orders, stops, or targets—only visual guidance.
Inputs
Key inputs include Lookback Length for HTF scanning and a Signal Timeframe used with request.security to import HTF events onto the active chart.
Entry behavior can be set to “Confirm only” or “Wait candle,” trade side can be restricted to Buy/Sell/Both, and individual strategies (Buy WAIT/S1; Sell REV/S1/S2/S3) can be toggled.
HTF logic
The script defines WAIT/BUY setup and confirmation, SELL reversal on breaking the WAIT BUY low, and several volume/candle-based patterns (Sell S1/S2/S3, Buy S1).
It captures the associated highs/lows at those events with ta.valuewhen and imports them via request.security to form anchors (anc_hi/anc_lo) and “new trigger” booleans that gate label creation on the LTF.
Flip entries
When enabled, “Flip entries” generate contrarian labels based on breaking or confirming HTF anchors: crossing above anc_hi can trigger a flip-to-sell label, and crossing below anc_lo can trigger a flip-to-buy label.
The flip mode supports Immediate (on cross) or Confirm (on sustained break) to control how strict the trigger is.
Fibonacci drawing
User-specified Fib levels are parsed from a string, safely converted to floats, and drawn as dotted horizontal lines only when they fall inside an approximate visible viewport. Orientation (up or down) is decided automatically from pending signal direction and a simple context score (candle bias, trend, and price vs. mid), with efficient redraw/clear guards to avoid clutter.
Dynamic anchors
If HTF anchors are missing or too far from current price (checked with an ATR-based threshold), the script falls back to local swing highs/lows to keep the reference range relevant. This dynamic switch helps Fib levels and labels remain close to current market structure without manual intervention.
Signal labels
Labels are created only on confirmed bars to avoid repainting noise, with one “latest” label kept by deleting the previous one. The script places BUY/SELL labels for WAIT/CONFIRM, direct HTF patterns (Buy S1, Sell S1/S2/S3), and contrarian flip events, offset slightly from highs/lows with clear coloring and configurable sizes.
Visual context
Bars are softly colored (lime tint for bullish, orange tint for bearish) for quick context, and everything renders as an overlay on the price chart. Fib labels include a Δ readout (distance from current close), and line extension length, label sizes, and viewport padding are adjustable.
How to use
Set the Signal Timeframe and Lookback Length to establish which HTF structures and ranges will drive the anchors and entry conditions. Choose entry flow (Wait vs Confirm), enable Flip if contrarian triggers are desired, select the trade side, toggle strategies, and customize Fibonacci levels plus dynamic-anchor fallback for practical on-chart guidance.
Notes
This is a visual decision-support tool; it does not place trades, stops, or targets and should be validated on charts before live use. It is written for Pine Script v6 and relies heavily on request.security for HTF-to-LTF transfer of signals and anchors.
Williams Accelerator Oscillator — ACWhat it is
The Accelerator Oscillator (AC) measures the acceleration/deceleration of momentum. It’s derived from the Awesome Oscillator (AO) and shows whether momentum is speeding up or slowing down. In this implementation, columns are green when AC rises vs. the previous bar and red when it falls.
How it’s calculated
Price source: Median Price (HL2) by default; Close can be used instead.
AO = SMA(HL2, fastLen) − SMA(HL2, slowLen) (defaults: 5 & 34).
AC = AO − SMA(AO, signalLen) (default: 5).
Coloring: Green if AC > AC , else Red.
Zero line (optional) helps contextualize acceleration around neutral.
How to read it (typical interpretation)
Above 0: Upside acceleration (bullish pressure increasing).
Below 0: Downside acceleration (bearish pressure increasing).
Color sequences: Consecutive green columns suggest increasing upside acceleration; consecutive red columns suggest increasing downside acceleration.
Note: AC reflects change in momentum, not trend direction by itself. Many traders confirm with trend filters or price structure before acting.
Inputs
AO Fast SMA (default 5)
AO Slow SMA (default 34)
AC Signal SMA (default 5) — smoothing for the AO used in AC calc
Use Median Price (HL2) for AO (on/off)
Show zero line (on/off)
Show AO (for reference) (on/off)
Show AC signal (SMA of AO) (on/off)
Plots
AC Histogram — column chart colored by acceleration (green/red).
Zero — optional baseline at 0.
AO — optional reference line.
AO Signal (SMA) — optional smoothing line of AO.
Alerts
AC crosses above 0 — acceleration flips positive.
AC crosses below 0 — acceleration flips negative.
AC green above zero — AC rising and > 0.
AC red below zero — AC falling and < 0.
Usage tips
On lower timeframes, consider a slightly larger signalLen to reduce noise.
Confirm with price action, trend filters, or volatility context.
Values update intrabar; for stricter signals, confirm on bar close.
Limitations
AC is built from moving averages and is therefore lagging relative to raw price.
It is not normalized; behavior can vary by instrument and timeframe.
Do not use in isolation for entries/exits without risk management.
Credits
Concept by Bill Williams. This script is an independent implementation for educational and research purposes.
Disclaimer
No financial advice. Markets involve risk; test thoroughly before live use.
COT Non-Commercial Net PositionsThis indicator displays the net position of Non-Commercial traders (speculators) in futures markets by subtracting short positions from long positions, based on CFTC COT data. It fetches the relevant COT long and short values weekly (or as per the user-selected timeframe) and plots the net positions relative to zero.
Buyer vs Seller Control CompanionBuyer vs Seller Control Companion (Overlay)
Crossover signal overlay based on candlestick wick analysis moving averages
Overview:
This companion indicator displays crossover signals directly on the price chart based on the same buyer vs seller control calculations. It identifies moments when the relationship between buying and selling pressure shifts by analyzing where prices close relative to their intraday ranges.
Calculation Method:
The indicator uses identical calculations to the main Buyer vs Seller Control indicator:
Visual Components:
Lime Triangle Up: Appears below price bars when buyer control SMA crosses above seller control SMA
Fuchsia Triangle Down: Appears above price bars when seller control SMA crosses above buyer control SMA
Signal Logic:
Crossover events are detected when one moving average crosses above or below the other. These crossovers indicate potential shifts in the balance between buying and selling pressure as measured by candlestick closing positions relative to their wicks.
Arrow Placement:
Upward Triangle: Positioned below the bar when buyer control moving average exceeds seller control moving average
Downward Triangle: Positioned above the bar when seller control moving average exceeds buyer control moving average
Size: Small triangular shapes to avoid cluttering the price chart
Timing: Arrows appear only on bars where actual crossovers occur
Settings:
Moving Average Period: Adjustable from 1-200 periods (default: 20)
Technical Notes:
This overlay version works on any timeframe
Arrows only appear when crossovers actually occur, not on every bar
The indicator uses the same mathematical foundation as the main oscillator version
Signal frequency depends on the chosen moving average period
Shorter periods generate more frequent crossovers, longer periods generate fewer
Relationship to Main Indicator:
This companion overlay displays the exact crossover points that can be observed in the main Buyer vs Seller Control indicator. It provides the same information but presents it directly on the price chart for convenient reference without switching between indicator panes.
This overlay serves as a visual reference tool for crossover events detected in the underlying buyer vs seller control analysis.
Buyer vs Seller ControlBuyer vs Seller Control Analysis
Technical indicator measuring market participation through candlestick wick analysis
Overview:
This indicator analyzes the relationship between closing prices and candlestick wicks to measure buying and selling pressure. It calculates two key metrics and displays their moving averages to help identify market sentiment shifts.
Calculation Method:
The indicator measures two distinct values for each candle:
Buyer Control Value: Distance from candle low to closing price (close - low)
Seller Control Value: Distance from candle high to closing price (high - close)
Both values are then smoothed using a Simple Moving Average (default period: 20) to reduce noise and show clearer trends.
Visual Components:
Lime Line: 20-period SMA of buyer control values
Fuchsia Line: 20-period SMA of seller control values
Area Fill: Colored region between the two lines
Histogram: Difference between buyer and seller control SMAs
Zero Reference Line: Horizontal line at zero level
Information Table: Current numerical values (optional display)
Interpretation:
When the lime line (buyer control) is above the fuchsia line (seller control), it indicates that recent candles have been closing closer to their highs than to their lows on average.
When the fuchsia line is above the lime line, recent candles have been closing closer to their lows than to their highs on average.
Fill Color Logic:
Lime (green) fill appears when buyer control SMA > seller control SMA
Fuchsia (red) fill appears when seller control SMA > buyer control SMA
Fill transparency adjusts based on the magnitude of difference between the two SMAs
Stronger differences result in more opaque fills
Settings:
Moving Average Period: Adjustable from 1-200 periods (default: 20)
Show Info Table: Toggle to display/hide the numerical values table
Technical Notes:
The indicator works on any timeframe
Values are displayed in the same units as the underlying asset's price
The histogram shows the mathematical difference between the two SMA lines
Transparency calculation uses a 50-period lookback for dynamic scaling
This indicator provides a quantitative approach to analyzing candlestick patterns by focusing on where prices close relative to their intraday ranges.
Initial Balance Breakout Signals [LuxAlgo]The Initial Balance Breakout Signals help traders identify breakouts of the Initial Balance (IB) range.
The indicator includes automatic detection of IB or can use custom sessions, highlights top and bottom IB extensions, custom Fibonacci levels, and goes further with an IB forecast with two different modes.
🔶 USAGE
The initial balance is the price range made within the first hour of the trading session. It is an intraday concept based on the idea that high volume and volatility enter the market through institutional trading at the start of the session, setting the tone for the rest of the day.
The initial balance is useful for gauging market sentiment, or, in other words, the relationship between buyers and sellers.
Bullish sentiment: Price trades above the IB range.
Mixed sentiment: Price trades within the IB range.
Bearish sentiment: Price trades below the IB range.
The initial balance high and low are important levels that many traders use to gauge sentiment. There are two main ideas behind trading around the IB range.
IB Extreme Breakout: When the price breaks and holds the IB high or low, there is a high probability that the price will continue in that direction.
IB Extreme Rejection: When the price tries to break those levels but fails, there is a high probability that it will reach the opposite IB extreme.
This indicator is a complete Initial Balance toolset with custom sessions, breakout signals, IB extensions, Fibonacci retracements, and an IB forecast. All of these features will be explained in the following sections.
🔹 Custom Sessions and Signals
By default, sessions for Initial Balance and breakout signals are in Auto mode. This means that Initial Balance takes the first hour of the trading session and shows breakout signals for the rest of the session.
With this option, traders can use the tool for open range trading, making it highly versatile. The concept behind open range (OR) is the same as that of initial balance (IB), but in OR, the range is determined by the first minute, three or five minutes, or up to the first 30 minutes of the trading session.
As shown in the image above, the top chart uses the Auto feature for the IB and Breakouts sessions. The bottom chart has the Auto feature disabled to use custom sessions for both parameters. In this case, the first three minutes of the trading session are used, turning the tool into an Open Range trading indicator.
This chart shows another example of using custom sessions to display overnight NASDAQ futures sessions.
The left chart shows a custom session from the Tokyo open to the London open, and the right chart shows a custom session from the London open to the New York open.
The chart shows both the Asian and European sessions, their top and bottom extremes, and the breakout signals from those extremes.
🔹 Initial Balance Extensions
Traders can easily extend both extremes of the Initial Balance to display their preferred targets for breakouts. Enable or disable any of them and set the IB percentage to use for the extension.
As the chart shows, the percentage selected on the settings panel directly affects the displayed levels.
Setting 25 means the tool will use a quarter of the detected initial balance range for extensions beyond the IB extremes. Setting 100 means the full IB range will be used.
Traders can use these extensions as targets for breakout signals.
🔹 Fibonacci Levels
Traders can display default or custom Fibonacci levels on the IB range to trade retracements and assess the strength of market movements. Each level can be enabled or disabled and customized by level, color, and line style.
As we can see on the chart, after the IB was completed, prices were unable to fall below the 0.236 Fibonacci level. This indicates significant bullish pressure, so it is expected that prices will rise.
Traders can use these levels as guidelines to assess the strength of the side trying to penetrate the IB. In this case, the sellers were unable to move the market beyond the first level.
🔹 Initial Balance Forecast
The tool features two different forecasting methods for the current IB. By default, it takes the average of the last ten values and applies a multiplier of one.
IB Against Previous Open: averages the difference between IB extremes and the open of the previous session.
Filter by current day of the week: averages the difference between IB extremes and the open of the current session for the same day of the week.
This feature allows traders to see the difference between the current IB and the average of the last IBs. It makes it very easy to interpret: if the current IB is higher than the average, buyers are in control; if it is lower than the average, sellers are in control.
For example, on the left side of the chart, we can see that the last day was very bullish because the IB was completely above the forecasted value. This is the IB mean of the last ten trading days.
On the right, we can see that on Monday, September 15, the IB traded slightly higher but within the forecasted value of the IB mean of the last ten Mondays. In this case, it is within expectations.
🔶 SETTINGS
Display Last X IBs: Select how many IBs to display.
Initial Balance: Choose a custom session or enable the Auto feature.
Breakouts: Enable or disable breakouts. Choose custom session or enable the Auto feature.
🔹 Extensions
Top Extension: Enable or disable the top extension and choose the percentage of IB to use.
Bottom extension: Enable or disable the bottom extension and choose the percentage of IB to use.
🔹 Fibonacci Levels
Display Fibonacci: Enable or disable Fibonacci levels.
Reverse: Reverse Fibonacci levels.
Levels, Colors & Style
Display Labels: Enable or disable labels and choose text size.
🔹 Forecast
Display Forecast: Select the forecast method.
- IB Against Previous Open: Calculates the average difference between the IB high and low and the previous day's IB open price.
- Filter by Current Day of Week: Calculates the average difference between the IB high and low and the IB open price for the same day of the week.
Forecast Memory: The number of data points used to calculate the average.
Forecast Multiplier: This multiplier will be applied to the average. Bigger numbers will result in wider predicted ranges.
Forecast Colors: Choose from a variety of colors.
Forecast Style: Choose a line style.
🔹 Style
Initial Balance Colors
Extension Transparency: Choose the extension's transparency. 0 is solid, and 100 is fully transparent.
AlgoPilotX - Breakout & Breakdown Meter (v1)Version Note:
This is a revised and improved version of the AlgoPilotX – Breakout & Breakdown Meter. It includes expanded explanations of the underlying logic, variable usage, and originality to comply with TradingView guidelines.
AlgoPilotX – Breakout & Breakdown Meter is a structured trading tool that combines Fair Value Gap (FVG) detection, session-based support/resistance breakouts, and a clean market condition info panel. It’s designed to help traders spot potential setups early and confirm stronger breakouts or breakdowns with context from momentum, volatility, and trend indicators.
How It Works
Session Levels → The first candle high/low of the session defines dynamic support/resistance. Unlike static pivots, these levels update with each new trading session and reflect real intraday sentiment.
Fair Value Gaps (FVGs) → A three-candle imbalance highlights inefficiencies. When detected, the script marks the open of the third candle as a potential entry (light green/red arrow).
Pullback Confirmations → If price pulls back into session support/resistance and then breaks away strongly, a stronger entry signal (dark green/red arrow) is plotted.
Breakouts & Breakdowns → Additional arrows appear when price crosses decisively above resistance or below support.
Signal Hierarchy → Arrows vary by color/size:
Light = early/potential setups.
Dark/Large = stronger confirmations.
Info Panel Dashboard → RSI, MACD, Bollinger Bands, and EMAs are displayed in a compact table with both numeric values and Bullish/Bearish/Neutral states, color-coded for quick interpretation.
How the Functions and Variables Work Together
Session Levels (Support & Resistance)
The script uses time() and session inputs to identify the first candle of the chosen trading session.
Variables sessionHigh and sessionLow are stored with var so they persist until the next session.
These levels are then plotted as dynamic support/resistance lines. This approach is different from static pivots or daily highs/lows, because it adapts in real-time to the market open.
Fair Value Gap (FVG) Detection
Conditions check for three-candle imbalances ( low > high for bullish, high < low for bearish).
When detected, a potential entry is marked at the open of the third candle.
Variables fvgBull and fvgBear define this logic , making FVGs a core entry condition rather than a side overlay.
Entry Hierarchy (Light vs. Dark Arrows)
longPotentialEntry and shortPotentialEntry mark light green/red arrows as early signals.
pullbackToSupport and pullbackToResistance build on these by requiring price to return to session levels and then break away again.
This creates the dark green/red arrows for stronger entries, introducing a two-step filtering process.
Breakout & Breakdown Detection
breakAbove = ta.crossover(close, sessionHigh)
breakBelow = ta.crossunder(close, sessionLow)
These conditions confirm true breakouts or breakdowns beyond support/resistance, reducing noise.
Info Panel Construction
A table is created and updated each bar.
Functions like ta.rsi(), ta.ema(), ta.sma(), and ta.stdev() calculate RSI, MACD, EMAs, and Bollinger Bands.
Each indicator’s state is summarized into human-readable text (e.g., “Bullish,” “Bearish,” “Above,” “Oversold”) and displayed with color coding using the helper function f_stateColor().
Values are also displayed numerically (RSI, MACD histogram, EMA levels, BB width), making this a dashboard rather than just arrows on a chart.
Helper Function for States
f_stateColor(state) translates qualitative states into consistent colors (green for bullish/above, red for bearish/below, orange for neutral, purple for overbought/oversold).
This ensures that every signal in the info panel has a visual identity that traders can read instantly.
Alerts Integration
alertcondition() is tied to each major event: FVG potential entries, strong pullback confirmations, and breakout/breakdown signals.
This allows the script to be used for alerts, notifications and automation , not just visual charting.
How to Use
1. Default timeframe = 15m (adjustable).
2. The first session candle defines support & resistance.
3. Watch for arrows:
Light green (▲) below candle → Potential breakout long (FVG detected).
Dark green (▲) below candle → Strong breakout confirmation after pullback.
Light red (▼) above candle → Potential breakdown short (FVG detected).
Dark red (▼) above candle → Strong breakdown confirmation after pullback.
Larger arrows = higher confidence signals.
4. Check the Info Panel for context:
RSI → momentum
MACD → trend confirmation
Bollinger Bands → overbought/oversold
EMA20 & EMA50 → short- and medium-term trend bias
5. Always confirm with your own price action, volume, and risk management rules.
6. Easily move the Info Panel to any corner of the chart via settings to keep your view clear.
Why This Structure Is Original
Not a mashup : Instead of simply overlaying RSI, MACD, or EMAs, the script integrates them into a signal-filtering framework.
Dynamic anchoring: Session-based high/low variables make levels adaptive to intraday structure, unlike fixed pivots.
Dual entry tiering: Light vs. dark arrows are built by combining FVGs + pullback conditions, offering nuance most breakout scripts lack.
Dashboard-style panel: Variables are summarized into a real-time info box with both numbers and state labels, replacing multiple chart overlays with one compact tool.
Modular functions: Breakout, pullback, FVG detection, and indicator states are modularized with separate variables — making the script flexible, extendable, and unique in design.
Disclaimer
This script is for educational purposes only. It does not constitute financial advice and does not guarantee profitable outcomes. Always backtest thoroughly, paper trade, and use proper risk management before trading live.
Premier Stochastic Oscillator [LazyBear, V2]This script builds on the well-known Premier Stochastic Oscillator (PSO) originally introduced by LazyBear, and adds a Z-Score extension to provide statistical interpretation of momentum extremes.
Features
Premier Stochastic Core: A smoothed stochastic calculation that highlights bullish and bearish momentum phases.
Z-Score Mapping: The PSO values are standardized into Z-Scores (from –3 to +3), quantifying the degree of momentum stretch.
Positive / Negative Z-Scores:
Positive Z values suggest momentum strength that can align with accumulation or favorable buying conditions.
Negative Z values indicate stronger bearish pressure, often aligning with selling or distribution conditions.
On-Chart Label: The current Z-Score is displayed on the latest bar for quick reference.
How to Use
Momentum Confirmation: Use the oscillator to confirm whether bullish or bearish momentum is intensifying.
Overextended Conditions: Extreme Z-Scores (±2 or beyond) highlight statistically stretched conditions, often preceding reversions.
Strategic Integration: Best applied in confluence with trend tools or higher-timeframe filters; not a standalone trading signal.
Originality
Unlike the standard PSO, this version:
Adds a Z-Score framework for objective statistical scaling.
Provides real-time labeling of Z values for clarity.
Extends the classic oscillator into a tool for both momentum detection and mean-reversion context.
350DMA bands + Z-score (V2)This script extends the classic 350-day moving average (350DMA) by building dynamic valuation bands and a Z-Score framework to evaluate how far price deviates from its long-term mean.
Features
350DMA Anchor: Uses the 350-day simple moving average as the baseline reference.
Fixed Multipliers: Key bands plotted at ×0.625, ×1.0, ×1.6, ×2.0, and ×2.5 of the 350DMA — historically significant levels for cycle analysis.
Z-Score Mapping: Price is converted into a Z-Score on a scale from +2 (deep undervaluation) to –2 (extreme overvaluation), using log-space interpolation for accuracy.
Custom Display: HUD panel and on-chart label show the current Z-Score in real time.
Clamp Option: Users can toggle between raw Z values or capped values (±2).
How to Use
Valuation Context: The 350DMA is often considered a “fair value” anchor; large deviations identify cycles of under- or over-valuation.
Z-Score Insight:
Positive Z values suggest favorable accumulation zones where price is below long-term average.
Negative Z values highlight zones of stretched valuation, often associated with distribution or profit-taking.
Strategic Application: This is not a standalone trading system — it works best in confluence with other indicators, cycle models, or macro analysis.
Originality
Unlike a simple DMA overlay, this script:
Provides multiple cycle-based bands derived from the 350DMA.
Applies a logarithmic Z-Score mapping for more precise long-term scaling.
Adds an integrated HUD and labeling system for quick interpretation.
200WMA Overlay + Z (heatmap mapping)This script enhances the classic 200-week moving average (200WMA), a long-term market reference line, by adding Z-Score mapping and optional helper bands for extended cycle analysis.
Features
200WMA Anchor: Plots the true 200-week simple moving average on any chart, a widely followed metric for long-term Bitcoin and crypto cycles.
Helper Multiples: Optional overlay of key historical ratios (×0.625, ×1.6, ×2.0, ×2.5) often referenced as cycle support/resistance zones.
Z-Score Mapping: Translates the ratio of price to 200WMA into a Z-Score scale (from +2.5 to –2.5), offering a statistical perspective on whether the market is undervalued, neutral, or overheated relative to its long-term mean.
On-Chart Label: Current Z-Score displayed directly on the last bar for quick reference.
How to Use
Long-Term Valuation: The 200WMA serves as a “fair value” baseline; large deviations highlight extended phases of market sentiment.
Heatmap Context:
Positive Z values typically mark undervaluation or favorable accumulation zones.
Negative Z values highlight overvaluation or profit-taking / distribution zones.
Strategic View: Best used to contextualize long-term market cycles, not for short-term signals.
Confluence Approach: This indicator should not be used alone — combine it with other technical or fundamental tools for stronger decision-making.
Originality
Unlike a basic 200WMA overlay, this version:
Incorporates multi-band ratios for extended cycle mapping.
Introduces a custom Z-Score scale tied directly to price/WMA ratios.
Provides both visual structure and statistical interpretation on a single overlay.
Yearly VWAP with Z-Score V2This script extends the traditional Volume Weighted Average Price (VWAP) by applying it to yearly sessions (with a customizable start month) and combining it with a Z-Score framework to standardize price deviations from VWAP.
Features
Yearly VWAP: Automatically resets at the selected month, making it possible to align VWAP with fiscal or seasonal cycles (e.g., June–May).
Volatility-Weighted Bands: Standard deviation is calculated using volume-weighted price variance, creating adaptive upper and lower bands around VWAP.
Z-Score Calculation: Converts price distance from VWAP into standardized scores, ranging from +2.5 to –2.5. This enables statistical interpretation of whether price is trading at fair value, extended, or oversold relative to VWAP.
Custom Session Control: Input allows users to change the yearly anchor month.
On-Chart Display: VWAP and bands are plotted, with a live Z-Score label shown on the latest bar.
How to Use
Fair Value Reference: VWAP reflects the average price weighted by volume over the yearly session — a natural equilibrium point.
Overbought / Oversold Detection: Extreme Z-Score readings (±2 or beyond) highlight when price is stretched relative to VWAP.
Cycle Analysis: Resetting VWAP by custom months allows studying market behavior over fiscal years, seasons, or custom trading cycles.
Part of a Broader Toolkit: This script is not a standalone trading system. It works best when aggregated with other indicators, confluence factors, or a structured strategy.
Originality
Unlike a standard VWAP, this version:
Uses yearly anchoring with custom start month instead of session/day anchoring.
Adds volume-weighted standard deviation bands for statistical context.
Translates distance into a Z-Score scale for objective overbought/oversold assessment.
Positive Z-Score values indicate zones where price is positioned favorably for accumulation or potential buys, while negative values highlight areas more suitable for distribution or profit-taking — always best used in confluence with other tools rather than as a standalone signal
triple Keltner Channels with Z-Score V2This script expands on the classic Keltner Channel by plotting three adaptive volatility bands around an EMA baseline and introducing a dynamic Z-Score calculation to quantify price positioning within or beyond those bands.
Features
Three Keltner Channels:
Inner Channel at ×2 ATR
Outer Channel at ×3 ATR
Extended Channel at ×3.5 ATR
Customizable Inputs: EMA length, ATR length, and multipliers can be adjusted to suit different market conditions or asset volatility.
Z-Score Integration: Converts price location relative to the channels into standardized scores (from +2.5 to –2.5). Positive Z indicate a good value/zone to buy while negative one is the contrary (do not use it alone, use it with other indicators )
This provides a statistical lens for identifying overextended, neutral, or mean-reverting conditions.
Visual Clarity: Channel fills highlight volatility zones, while an on-chart label dynamically displays the current Z-Score.
How to Use
Overbought/Oversold Signals: Extreme Z-Score readings (±2 and beyond) suggest stretched conditions that often precede pullbacks or reversions.
Mean Reversion vs Breakout: Traders can assess whether price is likely to revert to the mean (EMA) or sustain momentum beyond outer bands.
Originality
Unlike a standard Keltner Channel, this one:
Uses three progressively wider ATR multiples for deeper volatility mapping.
Adds a Z-Score framework to statistically measure price displacement.
Provides a visual + numerical hybrid output (bands + live Z-Score label).
use only on 1W timeframe
Stiffness IndexStiffness Index Indicator
Overview
The Stiffness Index is a technical analysis indicator created by Markos Katsanos and first introduced in the November 2018 issue of Technical Analysis of Stocks & Commodities magazine. This indicator attempts to recognize strong price trends by counting the number of times price was above the 100-day moving average during the indicator period.
Core Philosophy
The premise is the fewer number of times price penetrates the MA, the stronger the trend. The philosophy behind this indicator is that traders should trade when the trend is at its strongest point - when the trend is at its "stiffest". Based on the observation that in strong long-lasting uptrends, price seldom penetrates the 100-bar simple moving average, this indicator helps assess the quality and strength of an uptrend.
How It Works
The Stiffness Index operates through several key components:
1. Moving Average Baseline: Uses a 100-period moving average as the primary reference level
2. Volatility Threshold: Includes a volatility threshold to eliminate minor movements - typically 0.2 standard deviations to reject minimal penetrations above the moving average
3. Counting Mechanism: Calculates the stiffness coefficient as the ratio of the number of times the price has closed above the moving average during the indicator period to the length of that period
4. Smoothing: Applies additional smoothing to the final result for cleaner signals
Key Components
Input Parameters
- Period 1 (100): The moving average period for the baseline calculation
- MA Method 1: Type of moving average for the baseline (SMA, EMA, SMMA, LWMA)
- Summation Period (60): The lookback period for counting closes above the moving average
- Period 2 (3): Smoothing period for the final signal line
- MA Method 2: Smoothing method for the signal line
- Threshold Level (80): Reference level for identifying strong trends
Visual Elements
- Blue Signal Line: The main stiffness reading showing trend strength
- Dotted Line: Adjustable threshold level for reference
Interpretation and Trading Applications
Signal Readings
- High Values (Above Threshold): Indicates a "stiff" trend where price consistently stays above the moving average with minimal penetrations
- Low Values (Below Threshold): Suggests a weaker trend with frequent penetrations of the moving average
- Original threshold levels mentioned in research range from 75-95
Trading Strategy
The original strategy suggests entering long positions when the stiffness reading reaches 90 or higher, with exits when the reading drops below 50. Some implementations use a threshold of 75 for entry confirmation.
Key Characteristics
- Designed primarily for stocks and instruments with upward bias
- Trades infrequently - typically about once per year when using strict parameters
- Best suited for trend-following strategies in strongly trending markets
Advantages
- Trend Quality Assessment: Quantifies the "stiffness" or quality of trends
- Volatility Filtering: Built-in volatility threshold reduces false signals from minor price movements
- Objective Measurement: Provides a numerical assessment of trend strength
- Customizable: Multiple parameters allow adaptation to different markets and timeframes
Best Practices
- Use in conjunction with baseline trend indicators for confirmation
- Most effective in markets with strong directional bias
- Consider the low frequency of signals when developing trading strategies
- May not be suitable for instruments that "twitch up and down" frequently
*Note: This indicator is specifically designed to identify and trade the strongest trending periods, which naturally results in fewer but potentially higher-quality trading opportunities.*
88-Key Piano Range - Musical Price Levels88-Key Piano Range - Musical Price Levels
Description:
Explore price analysis through musical harmony! This educational indicator maps price movements to the standard 88-key piano keyboard (A0 to C8), offering a creative way to visualize market ranges and explore harmonic price relationships with authentic keyboard-style background fills.
🎹 KEY FEATURES:
• Complete 88-Key Mapping - Full piano range from A0 to C8 mapped to your price range
• Piano-Style Visual Design - Clean background fills distinguishing white keys, black keys, and octaves
• Dual Anchor System - Set two time/price points to define your analytical range
• Flexible Display Options - Show all 88 keys, octaves only (C notes), or custom selections
• Harmonic Exploration - Explore consonant/dissonant key relationships based on music theory
• Real-time Price Note - See what musical note your current price represents
• Customizable Interface - Adjust colors, line widths, fills, and visual elements
🎵 EDUCATIONAL CONCEPTS:
• Octave Levels - C notes as harmonic reference points (similar to round numbers)
• Key Classifications - Natural notes (white keys) vs chromatic notes (black keys)
• Harmonic Intervals - Musical relationships applied to price analysis
• Creative Visualization - Alternative way to view price ranges and movements
⚙️ HOW TO USE:
1. Select Your Price Leg - Choose an upleg, downleg, or significant price movement to explore
2. Set Anchor A - Place at the start of your selected leg (swing low for upleg, swing high for downleg)
3. Set Anchor B - Place at the end of your selected leg (swing high for upleg, swing low for downleg)
4. Configure Display - Select all keys, octaves only, or enable background fills
5. Explore Harmonics - Enable harmony coloring to see musical relationships
6. Study Patterns - Observe how price movements align with musical intervals
🎼 CREATIVE APPLICATIONS:
• Experimental Analysis - Try a musical approach to leg analysis
• Educational Tool - Learn about mathematical relationships in both music and markets
• Alternative Perspective - View support/resistance through a musical lens
• Pattern Recognition - Explore if harmonic levels show interesting price behavior
• Fun Learning - Combine musical knowledge with trading concepts
📊 EXPERIMENTAL USE:
• Creative alternative to traditional Fibonacci levels
• Educational exploration of mathematical harmony in markets
• Interesting way to visualize price ranges and retracements
• Novel approach for musicians interested in trading concepts
Important Note: This is an educational and experimental tool that applies musical theory concepts to price analysis. It should be used for learning and exploration purposes alongside proven technical analysis methods. The musical relationships are mathematically based but not validated as reliable trading signals.
Options Max Pain Calculator [BackQuant]Options Max Pain Calculator
A visualization tool that models option expiry dynamics by calculating "max pain" levels, displaying synthetic open interest curves, gamma exposure profiles, and pin-risk zones to help identify where market makers have the least payout exposure.
What is Max Pain?
Max Pain is the theoretical expiration price where the total dollar value of outstanding options would be minimized. At this price level, option holders collectively experience maximum losses while option writers (typically market makers) have minimal payout obligations. This creates a natural gravitational pull as expiration approaches.
Core Features
Visual Analysis Components:
Max Pain Line: Horizontal line showing the calculated minimum pain level
Strike Level Grid: Major support and resistance levels at key option strikes
Pin Zone: Highlighted area around max pain where price may gravitate
Pain Heatmap: Color-coded visualization showing pain distribution across prices
Gamma Exposure Profile: Bar chart displaying net gamma at each strike level
Real-time Dashboard: Summary statistics and risk metrics
Synthetic Market Modeling**
Since Pine Script cannot access live options data, the indicator creates realistic synthetic open interest distributions based on configurable market parameters including volume patterns, put/call ratios, and market maker positioning.
How It Works
Strike Generation:
The tool creates a grid of option strikes centered around the current price. You can control the range, density, and whether strikes snap to realistic market increments.
Open Interest Modeling:
Using your inputs for average volume, put/call ratios, and market maker behavior, the indicator generates synthetic open interest that mirrors real market dynamics:
Higher volume at-the-money with decay as strikes move further out
Adjustable put/call bias to reflect current market sentiment
Market maker inventory effects and typical short-gamma positioning
Weekly options boost for near-term expirations
Pain Calculation:
For each potential expiry price, the tool calculates total option payouts:
Call options contribute pain when finishing in-the-money
Put options contribute pain when finishing in-the-money
The strike with minimum total pain becomes the Max Pain level
Gamma Analysis:
Net gamma exposure is calculated at each strike using standard option pricing models, showing where hedging flows may be most intense. Positive gamma creates price support while negative gamma can amplify moves.
Key Settings
Basic Configuration:
Number of Strikes: Controls grid density (recommended: 15-25)
Days to Expiration: Time until option expiry
Strike Range: Price range around current level (recommended: 8-15%)
Strike Increment: Spacing between strikes
Market Parameters:
Average Daily Volume: Baseline for synthetic open interest
Put/Call Volume Ratio: Market sentiment bias (>1.0 = bearish, <1.0 = bullish) It does not work if set to 1.0
Implied Volatility: Current option volatility estimate
Market Maker Factors: Dealer positioning and hedging intensity
Display Options:
Model Complexity: Simple (line only), Standard (+ zones), Advanced (+ heatmap/gamma)
Visual Elements: Toggle individual components on/off
Theme: Dark/Light mode
Update Frequency: Real-time or daily calculation
Reading the Display
Dashboard Table (Top Right):
Current Price vs Max Pain Level
Distance to Pain: Percentage gap (smaller = higher pin risk)
Pin Risk Assessment: HIGH/MEDIUM/LOW based on proximity and time
Days to Expiry and Strike Count
Model complexity level
Visual Elements:
Red Line: Max Pain level where payout is minimized
Colored Zone: Pin risk area around max pain
Dotted Lines: Major strike levels (green = support, orange = resistance)
Color Bar: Pain heatmap (blue = high pain, red = low pain/max pain zones)
Horizontal Bars: Gamma exposure (green = positive, red = negative)
Yellow Dotted Line: Gamma flip level where hedging behavior changes
Trading Applications
Expiration Pinning:
When price is near max pain with limited time remaining, there's increased probability of gravitating toward that level as market makers hedge their positions.
Support and Resistance:
High open interest strikes often act as magnets, with max pain representing the strongest gravitational pull.
Volatility Expectations:
Above gamma flip: Expect dampened volatility (long gamma environment)
Below gamma flip: Expect amplified moves (short gamma environment)
Risk Assessment:
The pin risk indicator helps gauge likelihood of price manipulation near expiry, with HIGH risk suggesting potential range-bound action.
Best Practices
Setup Recommendations
Start with Model Complexity set to "Standard"
Use realistic strike ranges (8-12% for most assets)
Set put/call ratio based on current market sentiment
Adjust implied volatility to match current levels
Interpretation Guidelines:
Small distance to pain + short time = high pin probability
Large gamma bars indicate key hedging levels to monitor
Heatmap intensity shows strength of pain concentration
Multiple nearby strikes can create wider pin zones
Update Strategy:
Use "Daily" updates for cleaner visuals during trading hours
Switch to "Every Bar" for real-time analysis near expiration
Monitor changes in max pain level as new options activity emerges
Important Disclaimers
This is a modeling tool using synthetic data, not live market information. While the calculations are mathematically sound and the modeling realistic, actual market dynamics involve numerous factors not captured in any single indicator.
Max pain represents theoretical minimum payout levels and suggests where natural market forces may create gravitational pull, but it does not guarantee price movement or predict exact expiration levels. Market gaps, news events, and changing volatility can override these dynamics.
Use this tool as additional context for your analysis, not as a standalone trading signal. The synthetic nature of the data makes it most valuable for understanding market structure and potential zones of interest rather than precise price prediction.
Technical Notes
The indicator uses established option pricing principles with simplified implementations optimized for Pine Script performance. Gamma calculations use standard financial models while pain calculations follow the industry-standard definition of minimized option payouts.
All visual elements use fixed positioning to prevent movement when scrolling charts, and the tool includes performance optimizations to handle real-time calculation without timeout errors.
Universal Gann Square & Cube LevelsUniversal Gann Square & Cube Levels - Dynamic Support/Resistance
Description:
📊 UNIVERSAL GANN LEVELS INDICATOR
This powerful indicator automatically plots Gann Square and Cube levels around the current stock price, providing dynamic support and resistance levels based on W.D. Gann's mathematical theories.
🎯 KEY FEATURES:
✅ Auto-Adaptive: Works for ANY stock price (₹20 to ₹100,000+)
✅ Real-time Detection: Uses current close price automatically
✅ Dual Level System: Square levels (black) + Cube levels (red)
✅ Customizable Range: Adjust percentage range (5% to 50%)
✅ Clean Display: Toggle square/cube lines independently
✅ Universal Compatibility: Works on all timeframes and instruments
📈 HOW IT WORKS:
Square Levels (Black Lines): Based on perfect squares (n²) around current price
Cube Levels (Red Lines): Based on perfect cubes (n³) around current price
Smart Range: Automatically calculates relevant levels within your specified percentage range
Info Display: Shows current price and level counts
⚙️ SETTINGS:
Price Range %: Control how many levels appear (default: 15%)
Show Square Levels: Toggle black square lines on/off
Show Cube Levels: Toggle red cube lines on/off
🔥 PERFECT FOR:
Day traders seeking precise entry/exit points
Swing traders identifying key support/resistance zones
Gann theory practitioners and students
Multi-timeframe analysis across all instruments
💡 USAGE TIPS:
Use 10-20% range for active day trading
Use 30-50% range for swing trading analysis
Watch for price reactions at square/cube intersections
Combine with volume analysis for confirmation
🌟 WHY THIS INDICATOR?
Unlike fixed Gann calculators, this indicator dynamically adapts to ANY price level, making it truly universal for Indian stocks, crypto, forex, and commodities.
⚠️ DISCLAIMER:
This indicator is for educational and informational purposes only. It is not financial advice and should not be considered as a recommendation to buy or sell any security. Trading involves significant risk of loss and may not be suitable for all investors. Past performance does not guarantee future results. Always conduct your own research and consult with a qualified financial advisor before making any investment decisions. The developer assumes no responsibility for any trading losses incurred through the use of this indicator.
📋 COMPATIBILITY:
All TradingView plans
All timeframes (1m to 1M)
Stocks, Crypto, Forex, Commodities
Mobile and desktop platforms
StdDev Supertrend {CHIPA}StdDev Supertrend ~ C H I P A is a supertrend style trend engine that replaces ATR with standard deviation as the volatility core. It can operate on raw prices or log return volatility, with optional smoothing to control noise.
Key features include:
Supertrend trailing rails built from a stddev scaled envelope that flips the regime only when price closes through the opposite rail.
Returns-based mode that scales volatility by log returns for more consistent behavior across price regimes.
Optional smoothing on the volatility input to tune responsiveness versus stability.
Directional gap fill between price and the active trend line on the main chart; opacity adapts to the distance (vs ATR) so wide gaps read stronger and small gaps stay subtle.
Secondary pane view of the rails with the same adaptive fade, plus an optional candle overlay for context.
Clean alerts that fire once when state changes
Use cases: medium-term trend following, stop/flip systems, and visual regime confirmation when you prefer stddev-based distance over ATR.
Note: no walk-forward or robustness testing is implied; parameter choices and risk controls are on you.
TA█ TA Library
📊 OVERVIEW
TA is a Pine Script technical analysis library. This library provides 25+ moving averages and smoothing filters , from classic SMA/EMA to Kalman Filters and adaptive algorithms, implemented based on academic research.
🎯 Core Features
Academic Based - Algorithms follow original papers and formulas
Performance Optimized - Pre-calculated constants for faster response
Unified Interface - Consistent function design
Research Based - Integrates technical analysis research
🎯 CONCEPTS
Library Design Philosophy
This technical analysis library focuses on providing:
Academic Foundation
Algorithms based on published research papers and academic standards
Implementations that follow original mathematical formulations
Clear documentation with research references
Developer Experience
Unified interface design for consistent usage patterns
Pre-calculated constants for optimal performance
Comprehensive function collection to reduce development time
Single import statement for immediate access to all functions
Each indicator encapsulated as a simple function call - one line of code simplifies complexity
Technical Excellence
25+ carefully implemented moving averages and filters
Support for advanced algorithms like Kalman Filter and MAMA/FAMA
Optimized code structure for maintainability and reliability
Regular updates incorporating latest research developments
🚀 USING THIS LIBRARY
Import Library
//@version=6
import DCAUT/TA/1 as dta
indicator("Advanced Technical Analysis", overlay=true)
Basic Usage Example
// Classic moving average combination
ema20 = ta.ema(close, 20)
kama20 = dta.kama(close, 20)
plot(ema20, "EMA20", color.red, 2)
plot(kama20, "KAMA20", color.green, 2)
Advanced Trading System
// Adaptive moving average system
kama = dta.kama(close, 20, 2, 30)
= dta.mamaFama(close, 0.5, 0.05)
// Trend confirmation and entry signals
bullTrend = kama > kama and mamaValue > famaValue
bearTrend = kama < kama and mamaValue < famaValue
longSignal = ta.crossover(close, kama) and bullTrend
shortSignal = ta.crossunder(close, kama) and bearTrend
plot(kama, "KAMA", color.blue, 3)
plot(mamaValue, "MAMA", color.orange, 2)
plot(famaValue, "FAMA", color.purple, 2)
plotshape(longSignal, "Buy", shape.triangleup, location.belowbar, color.green)
plotshape(shortSignal, "Sell", shape.triangledown, location.abovebar, color.red)
📋 FUNCTIONS REFERENCE
ewma(source, alpha)
Calculates the Exponentially Weighted Moving Average with dynamic alpha parameter.
Parameters:
source (series float) : Series of values to process.
alpha (series float) : The smoothing parameter of the filter.
Returns: (float) The exponentially weighted moving average value.
dema(source, length)
Calculates the Double Exponential Moving Average (DEMA) of a given data series.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Double Exponential Moving Average value.
tema(source, length)
Calculates the Triple Exponential Moving Average (TEMA) of a given data series.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Triple Exponential Moving Average value.
zlema(source, length)
Calculates the Zero-Lag Exponential Moving Average (ZLEMA) of a given data series. This indicator attempts to eliminate the lag inherent in all moving averages.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Zero-Lag Exponential Moving Average value.
tma(source, length)
Calculates the Triangular Moving Average (TMA) of a given data series. TMA is a double-smoothed simple moving average that reduces noise.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Triangular Moving Average value.
frama(source, length)
Calculates the Fractal Adaptive Moving Average (FRAMA) of a given data series. FRAMA adapts its smoothing factor based on fractal geometry to reduce lag. Developed by John Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: (float) The calculated Fractal Adaptive Moving Average value.
kama(source, length, fastLength, slowLength)
Calculates Kaufman's Adaptive Moving Average (KAMA) of a given data series. KAMA adjusts its smoothing based on market efficiency ratio. Developed by Perry J. Kaufman.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the efficiency calculation.
fastLength (simple int) : Fast EMA length for smoothing calculation. Optional. Default is 2.
slowLength (simple int) : Slow EMA length for smoothing calculation. Optional. Default is 30.
Returns: (float) The calculated Kaufman's Adaptive Moving Average value.
t3(source, length, volumeFactor)
Calculates the Tilson Moving Average (T3) of a given data series. T3 is a triple-smoothed exponential moving average with improved lag characteristics. Developed by Tim Tillson.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
volumeFactor (simple float) : Volume factor affecting responsiveness. Optional. Default is 0.7.
Returns: (float) The calculated Tilson Moving Average value.
ultimateSmoother(source, length)
Calculates the Ultimate Smoother of a given data series. Uses advanced filtering techniques to reduce noise while maintaining responsiveness. Based on digital signal processing principles by John Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the smoothing calculation.
Returns: (float) The calculated Ultimate Smoother value.
kalmanFilter(source, processNoise, measurementNoise)
Calculates the Kalman Filter of a given data series. Optimal estimation algorithm that estimates true value from noisy observations. Based on the Kalman Filter algorithm developed by Rudolf Kalman (1960).
Parameters:
source (series float) : Series of values to process.
processNoise (simple float) : Process noise variance (Q). Controls adaptation speed. Optional. Default is 0.05.
measurementNoise (simple float) : Measurement noise variance (R). Controls smoothing. Optional. Default is 1.0.
Returns: (float) The calculated Kalman Filter value.
mcginleyDynamic(source, length)
Calculates the McGinley Dynamic of a given data series. McGinley Dynamic is an adaptive moving average that adjusts to market speed changes. Developed by John R. McGinley Jr.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the dynamic calculation.
Returns: (float) The calculated McGinley Dynamic value.
mama(source, fastLimit, slowLimit)
Calculates the Mesa Adaptive Moving Average (MAMA) of a given data series. MAMA uses Hilbert Transform Discriminator to adapt to market cycles dynamically. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: (float) The calculated Mesa Adaptive Moving Average value.
fama(source, fastLimit, slowLimit)
Calculates the Following Adaptive Moving Average (FAMA) of a given data series. FAMA follows MAMA with reduced responsiveness for crossover signals. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: (float) The calculated Following Adaptive Moving Average value.
mamaFama(source, fastLimit, slowLimit)
Calculates Mesa Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA).
Parameters:
source (series float) : Series of values to process.
fastLimit (simple float) : Maximum alpha (responsiveness). Optional. Default is 0.5.
slowLimit (simple float) : Minimum alpha (smoothing). Optional. Default is 0.05.
Returns: ( ) Tuple containing values.
laguerreFilter(source, length, gamma, order)
Calculates the standard N-order Laguerre Filter of a given data series. Standard Laguerre Filter uses uniform weighting across all polynomial terms. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Length for UltimateSmoother preprocessing.
gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.8.
order (simple int) : The order of the Laguerre filter (1-10). Higher order increases lag. Optional. Default is 8.
Returns: (float) The calculated standard Laguerre Filter value.
laguerreBinomialFilter(source, length, gamma)
Calculates the Laguerre Binomial Filter of a given data series. Uses 6-pole feedback with binomial weighting coefficients. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Length for UltimateSmoother preprocessing.
gamma (simple float) : Feedback coefficient (0-1). Lower values reduce lag. Optional. Default is 0.5.
Returns: (float) The calculated Laguerre Binomial Filter value.
superSmoother(source, length)
Calculates the Super Smoother of a given data series. SuperSmoother is a second-order Butterworth filter from aerospace technology. Developed by John F. Ehlers.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Period for the filter calculation.
Returns: (float) The calculated Super Smoother value.
rangeFilter(source, length, multiplier)
Calculates the Range Filter of a given data series. Range Filter reduces noise by filtering price movements within a dynamic range.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the average range calculation.
multiplier (simple float) : Multiplier for the smooth range. Higher values increase filtering. Optional. Default is 2.618.
Returns: ( ) Tuple containing filtered value, trend direction, upper band, and lower band.
qqe(source, rsiLength, rsiSmooth, qqeFactor)
Calculates the Quantitative Qualitative Estimation (QQE) of a given data series. QQE is an improved RSI that reduces noise and provides smoother signals. Developed by Igor Livshin.
Parameters:
source (series float) : Series of values to process.
rsiLength (simple int) : Number of bars for the RSI calculation. Optional. Default is 14.
rsiSmooth (simple int) : Number of bars for smoothing the RSI. Optional. Default is 5.
qqeFactor (simple float) : QQE factor for volatility band width. Optional. Default is 4.236.
Returns: ( ) Tuple containing smoothed RSI and QQE trend line.
sslChannel(source, length)
Calculates the Semaphore Signal Level (SSL) Channel of a given data series. SSL Channel provides clear trend signals using moving averages of high and low prices.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
Returns: ( ) Tuple containing SSL Up and SSL Down lines.
ma(source, length, maType)
Calculates a Moving Average based on the specified type. Universal interface supporting all moving average algorithms.
Parameters:
source (series float) : Series of values to process.
length (simple int) : Number of bars for the moving average calculation.
maType (simple MaType) : Type of moving average to calculate. Optional. Default is SMA.
Returns: (float) The calculated moving average value based on the specified type.
atr(length, maType)
Calculates the Average True Range (ATR) using the specified moving average type. Developed by J. Welles Wilder Jr.
Parameters:
length (simple int) : Number of bars for the ATR calculation.
maType (simple MaType) : Type of moving average to use for smoothing. Optional. Default is RMA.
Returns: (float) The calculated Average True Range value.
macd(source, fastLength, slowLength, signalLength, maType, signalMaType)
Calculates the Moving Average Convergence Divergence (MACD) with customizable MA types. Developed by Gerald Appel.
Parameters:
source (series float) : Series of values to process.
fastLength (simple int) : Period for the fast moving average.
slowLength (simple int) : Period for the slow moving average.
signalLength (simple int) : Period for the signal line moving average.
maType (simple MaType) : Type of moving average for main MACD calculation. Optional. Default is EMA.
signalMaType (simple MaType) : Type of moving average for signal line calculation. Optional. Default is EMA.
Returns: ( ) Tuple containing MACD line, signal line, and histogram values.
dmao(source, fastLength, slowLength, maType)
Calculates the Dual Moving Average Oscillator (DMAO) of a given data series. Uses the same algorithm as the Percentage Price Oscillator (PPO), but can be applied to any data series.
Parameters:
source (series float) : Series of values to process.
fastLength (simple int) : Period for the fast moving average.
slowLength (simple int) : Period for the slow moving average.
maType (simple MaType) : Type of moving average to use for both calculations. Optional. Default is EMA.
Returns: (float) The calculated Dual Moving Average Oscillator value as a percentage.
continuationIndex(source, length, gamma, order)
Calculates the Continuation Index of a given data series. The index represents the Inverse Fisher Transform of the normalized difference between an UltimateSmoother and an N-order Laguerre filter. Developed by John F. Ehlers, published in TASC 2025.09.
Parameters:
source (series float) : Series of values to process.
length (simple int) : The calculation length.
gamma (simple float) : Controls the phase response of the Laguerre filter. Optional. Default is 0.8.
order (simple int) : The order of the Laguerre filter (1-10). Optional. Default is 8.
Returns: (float) The calculated Continuation Index value.
📚 RELEASE NOTES
v1.0 (2025.09.24)
✅ 25+ technical analysis functions
✅ Complete adaptive moving average series (KAMA, FRAMA, MAMA/FAMA)
✅ Advanced signal processing filters (Kalman, Laguerre, SuperSmoother, UltimateSmoother)
✅ Performance optimized with pre-calculated constants and efficient algorithms
✅ Unified function interface design following TradingView best practices
✅ Comprehensive moving average collection (DEMA, TEMA, ZLEMA, T3, etc.)
✅ Volatility and trend detection tools (QQE, SSL Channel, Range Filter)
✅ Continuation Index - Latest research from TASC 2025.09
✅ MACD and ATR calculations supporting multiple moving average types
✅ Dual Moving Average Oscillator (DMAO) for arbitrary data series analysis
All Levels This script draws key price levels on your chart, including:
• Previous Day (PD): High, Low, Close
• Day Before Yesterday (DBY): High, Low, Close
• Pre-Market (PM): High and Low
• Today’s levels: High, Low, Open, Close
• Current bar levels: High, Low, Open, Close
Each level is displayed as a horizontal line with a label showing the level value.
It works on any timeframe, including 1-minute charts, and automatically updates as new bars form.
⸻
2. Features
1. Custom Colors
Each type of level has its own color, declared as a const color. For example:
• Previous Day High = red
• Today’s Close = gold
• Pre-Market High = fuchsia
2. Right-Extending Lines
All horizontal levels extend to the right, so you always see them on the chart.
3. Persistent Labels
Every line has a label at the right side showing its name and price. For example:
• PDH 422
• TODL 415.5
4. Dynamic Updates
The script updates automatically whenever a new bar forms, so levels stay accurate.
5. Session-Based Pre-Market
You can define the pre-market session (default “04:00–09:30 EST”). The script calculates the high and low of this session only.
6. Checkbox Inputs
You can enable/disable entire groups of levels:
• Previous Day
• Day Before Yesterday
• Pre-Market
• Today
• Current bar
Trend Pro V2 [CRYPTIK1]Introduction: What is Trend Pro V2?
Welcome to Trend Pro V2! This analysis tool give you at-a-glance understanding of the market's direction. In a noisy market, the single most important factor is the dominant trend. Trend Pro V2 filters out this noise by focusing on one core principle: trading with the primary momentum.
Instead of cluttering your chart with confusing signals, this indicator provides a clean, visual representation of the trend, helping you make more confident and informed trading decisions.
The dashboard provides a simple, color-coded view of the trend across multiple timeframes.
The Core Concept: The Power of Confluence
The strength of any trading decision comes from confluence—when multiple factors align. Trend Pro V2 is built on this idea. It uses a long-term moving average (200-period EMA by default) to define the primary trend on your current chart and then pulls in data from three higher timeframes to confirm whether the broader market agrees.
When your current timeframe and the higher timeframes are all aligned, you have a state of "confluence," which represents a higher-probability environment for trend-following trades.
Key Features
1. The Dynamic Trend MA:
The main moving average on your chart acts as your primary guide. Its color dynamically changes to give you an instant read on the market.
Teal MA: The price is in a confirmed uptrend (trading above the MA).
Pink MA: The price is in a confirmed downtrend (trading below the MA).
The moving average changes color to instantly show you if the trend is bullish (teal) or bearish (pink).
2. The Multi-Timeframe (MTF) Trend Dashboard:
Located discreetly in the bottom-right corner, this dashboard is your window into the broader market sentiment. It shows you the trend status on three customizable higher timeframes.
Teal Box: The trend is UP on that timeframe.
Pink Box: The trend is DOWN on that timeframe.
Gray Box: The price is neutral or at the MA on that timeframe.
How to Use Trend Pro V2: A Simple Framework
Step 1: Identify the Primary Trend
Look at the color of the MA on your chart. This is your starting point. If it's teal, you should generally be looking for long opportunities. If it's pink, you should be looking for short opportunities.
Step 2: Check for Confluence
Glance at the MTF Trend Dashboard.
Strong Confluence (High-Probability): If your main chart shows an uptrend (Teal MA) and the dashboard shows all teal boxes, the market is in a strong, unified uptrend. This is a high-probability environment to be a buyer on dips.
Weak or No Confluence (Caution Zone): If your main chart shows an uptrend, but the dashboard shows pink or gray boxes, it signals disagreement among the timeframes. This is a sign of market indecision and a lower-probability environment. It's often best to wait for alignment.
Here, the daily trend is down, but the MTF dashboard shows the weekly trend is still up—a classic sign of weak confluence and a reason for caution.
Best Practices & Settings
Timeframe Synergy: For best results, use Trend Pro on a lower timeframe and set your dashboard to higher timeframes. For example, if you trade on the 1-hour chart, set your MTF dashboard to the 4-hour, 1-day, and 1-week.
Use as a Confirmation Tool: Trend Pro V2 is designed as a foundational layer for your analysis. First, confirm the trend, then use your preferred entry method (e.g., support/resistance, chart patterns) to time your trade.
This is a tool for the community, so feel free to explore the open-source code, adapt it, and build upon it. Happy trading!
For your consideration @TradingView
