SP500 Session Gap Fade StrategySummary in one paragraph
SPX Session Gap Fade is an intraday gap fade strategy for index futures, designed around regular cash sessions on five minute charts. It helps you participate only when there is a full overnight or pre session gap and a valid intraday session window, instead of trading every open. The original part is the gap distance engine which anchors both stop and optional target to the previous session reference close at a configurable flat time, so every trade’s risk scales with the actual gap size rather than a fixed tick stop.
Scope and intent
• Markets. Primarily index futures such as ES, NQ, YM, and liquid index CFDs that exhibit overnight gaps and regular cash hours.
• Timeframes. Intraday timeframes from one minute to fifteen minutes. Default usage is five minute bars.
• Default demo used in the publication. Symbol CME:ES1! on a five minute chart.
• Purpose. Provide a simple, transparent way to trade opening gaps with a session anchored risk model and forced flat exit so you are not holding into the last part of the session.
• Limits. This is a strategy. Orders are simulated on standard candles only.
Originality and usefulness
• Unique concept or fusion. The core novelty is the combination of a strict “full gap” entry condition with a session anchored reference close and a gap distance based TP and SL engine. The stop and optional target are symmetric multiples of the actual gap distance from the previous session’s flat close, rather than fixed ticks.
• Failure mode it addresses. Fixed sized stops do not scale when gaps are unusually small or unusually large, which can either under risk or over risk the account. The session flat logic also reduces the chance of holding residual positions into late session liquidity and news.
• Testability. All key pieces are explicit in the Inputs: session window, minutes before session end, whether to use gap exits, whether TP or SL are active, and whether to allow candle based closes and forced flat. You can toggle each component and see how it changes entries and exits.
• Portable yardstick. The main unit is the absolute price gap between the entry bar open and the previous session reference close. tp_mult and sl_mult are multiples of that gap, which makes the risk model portable across contracts and volatility regimes.
Method overview in plain language
The strategy first defines a trading session using exchange time, for example 08:30 to 15:30 for ES day hours. It also defines a “flat” time a fixed number of minutes before session end. At the flat bar, any open position is closed and the bar’s close price is stored as the reference close for the next session. Inside the session, the strategy looks for a full gap bar relative to the prior bar: a gap down where today’s high is below yesterday’s low, or a gap up where today’s low is above yesterday’s high. A full gap down generates a long entry; a full gap up generates a short entry. If the gap risk engine is enabled and a valid reference close exists, the strategy measures the distance between the entry bar open and that reference close. It then sets a stop and optional target as configurable multiples of that gap distance and manages them with strategy.exit. Additional exits can be triggered by a candle color flip or by the forced flat time.
Base measures
• Range basis. The main unit is the absolute difference between the current entry bar open and the stored reference close from the previous session flat bar. That value is used as a “gap unit” and scaled by tp_mult and sl_mult to build the target and stop.
Components
• Component one: Gap Direction. Detects full gap up or full gap down by comparing the current high and low to the previous bar’s high and low. Gap down signals a long fade, gap up signals a short fade. There is no smoothing; it is a strict structural condition.
• Component two: Session Window. Only allows entries when the current time is within the configured session window. It also defines a flat time before the session end where positions are forced flat and the reference close is updated.
• Component three: Gap Distance Risk Engine. Computes the absolute distance between the entry open and the stored reference close. The stop and optional target are placed as entry ± gap_distance × multiplier so that risk scales with gap size.
• Optional component: Candle Exit. If enabled, a bullish bar closes short positions and a bearish bar closes long positions, which can shorten holding time when price reverses quickly inside the session.
• Session windows. Session logic uses the exchange time of the chart symbol. When changing symbols or venues, verify that the session time string still matches the new instrument’s cash hours.
Fusion rule
All gates are hard conditions rather than weighted scores. A trade can only open if the session window is active and the full gap condition is true. The gap distance engine only activates if a valid reference close exists and use_gap_risk is on. TP and SL are controlled by separate booleans so you can use SL only, TP only, or both. Long and short are symmetric by construction: long trades fade full gap downs, short trades fade full gap ups with mirrored TP and SL logic.
Signal rule
• Long entry. Inside the active session, when the current bar shows a full gap down relative to the previous bar (current high below prior low), the strategy opens a long position. If the gap risk engine is active, it places a gap based stop below the entry and an optional target above it.
• Short entry. Inside the active session, when the current bar shows a full gap up relative to the previous bar (current low above prior high), the strategy opens a short position. If the gap risk engine is active, it places a gap based stop above the entry and an optional target below it.
• Forced flat. At the configured flat time before session end, any open position is closed and the close price of that bar becomes the new reference close for the following session.
• Candle based exit. If enabled, a bearish bar closes longs, and a bullish bar closes shorts, regardless of where TP or SL sit, as long as a position is open.
What you will see on the chart
• Markers on entry bars. Standard strategy entry markers labeled “long” and “short” on the gap bars where trades open.
• Exit markers. Standard exit markers on bars where either the gap stop or target are hit, or where a candle exit or forced flat close occurs. Exit IDs “long_gap” and “short_gap” label gap based exits.
• Reference levels. Horizontal lines for the current long TP, long SL, short TP, and short SL while a position is open and the gap engine is enabled. They update when a new trade opens and disappear when flat.
• Session background. This version does not add background shading for the session; session logic runs internally based on time.
• No on chart table. All decisions are visible through orders and exit levels. Use the Strategy Tester for performance metrics.
Inputs with guidance
Session Settings
• Trading session (sess). Session window in exchange time. Typical value uses the regular cash session for each contract, for example “0830-1530” for ES. Adjust if your broker or symbol uses different hours.
• Minutes before session end to force exit (flat_before_min). Minutes before the session end where positions are forced flat and the reference close is stored. Typical range is 15 to 120. Raising it closes trades earlier in the day; lowering it allows trades later in the session.
Gap Risk
• Enable gap based TP/SL (use_gap_risk). Master switch for the gap distance exit engine. Turning it off keeps entries and forced flat logic but removes automatic TP and SL placement.
• Use TP limit from gap (use_gap_tp). Enables gap based profit targets. Typical values are true for structured exits or false if you want to manage exits manually and only keep a stop.
• Use SL stop from gap (use_gap_sl). Enables gap based stop losses. This should normally remain true so that each trade has a defined initial risk in ticks.
• TP multiplier of gap distance (tp_mult). Multiplier applied to the gap distance for the target. Typical range is 0.5 to 2.0. Raising it places the target further away and reduces hit frequency.
• SL multiplier of gap distance (sl_mult). Multiplier applied to the gap distance for the stop. Typical range is 0.5 to 2.0. Raising it widens the stop and increases risk per trade; lowering it tightens the stop and may increase the number of small losses.
Exit Controls
• Exit with candle logic (use_candle_exit). If true, closes shorts on bullish candles and longs on bearish candles. Useful when you want to react to intraday reversal bars even if TP or SL have not been reached.
• Force flat before session end (use_forced_flat). If true, guarantees you are flat by the configured flat time and updates the reference close. Turn this off only if you understand the impact on overnight risk.
Filters
There is no separate trend or volatility filter in this version. All trades depend on the presence of a full gap bar inside the session. If you need extra filtering such as ATR, volume, or higher timeframe bias, they should be added explicitly and documented in your own fork.
Usage recipes
Intraday conservative gap fade
• Timeframe. Five minute chart on ES regular session.
• Gap risk. use_gap_risk = true, use_gap_tp = true, use_gap_sl = true.
• Multipliers. tp_mult around 0.7 to 1.0 and sl_mult around 1.0.
• Exits. use_candle_exit = false, use_forced_flat = true. Focus on the structured TP and SL around the gap.
Intraday aggressive gap fade
• Timeframe. Five minute chart.
• Gap risk. use_gap_risk = true, use_gap_tp = false, use_gap_sl = true.
• Multipliers. sl_mult around 0.7 to 1.0.
• Exits. use_candle_exit = true, use_forced_flat = true. Entries fade full gaps, stops are tight, and candle color flips flatten trades early.
Higher timeframe gap tests
• Timeframe. Fifteen minute or sixty minute charts on instruments with regular gaps.
• Gap risk. Keep use_gap_risk = true. Consider slightly higher sl_mult if gaps are structurally wider on the higher timeframe.
• Note. Expect fewer trades and be careful with sample size; multi year data is recommended.
Properties visible in this publication
• On average our risk for each position over the last 200 trades is 0.4% with a max intraday loss of 1.5% of the total equity in this case of 100k $ with 1 contract ES. For other assets, recalculations and customizations has to be applied.
• Initial capital. 100 000.
• Base currency. USD.
• Default order size method. Fixed with size 1 contract.
• Pyramiding. 0.
• Commission. Flat 2 USD per order in the Strategy Tester Properties. (2$ buying + 2$selling)
• Slippage. One tick in the Strategy Tester Properties.
• Process orders on close. ON.
Realism and responsible publication
• No performance claims are made. Past results do not guarantee future outcomes.
• Costs use a realistic flat commission and one tick of slippage per trade for ES class futures.
• Default sizing with one contract on a 100 000 reference account targets modest per trade risk. In practice, extreme slippage or gap through events can exceed this, so treat the one and a half percent risk target as a design goal, not a guarantee.
• All orders are simulated on standard candles. Shapes can move while a bar is forming and settle on bar close.
Honest limitations and failure modes
• Economic releases, thin liquidity, and limit conditions can break the assumptions behind the simple gap model and lead to slippage or skipped fills.
• Symbols with very frequent or very large gaps may require adjusted multipliers or alternative risk handling, especially in high volatility regimes.
• Very quiet periods without clean gaps will produce few or no trades. This is expected behavior, not a bug.
• Session windows follow the exchange time of the chart. Always confirm that the configured session matches the symbol.
• When both the stop and target lie inside the same bar’s range, the TradingView engine decides which is hit first based on its internal intrabar assumptions. Without bar magnifier, tie handling is approximate.
Legal
Education and research only. This strategy is not investment advice. You remain responsible for all trading decisions. Always test on historical data and in simulation with realistic costs before considering any live use.
Recherche dans les scripts pour "Futures"
Globex Trap w/ percentage [SLICKRICK]Globex Trap w/ Percentage
Overview
The Globex Trap w/ Percentage indicator is a powerful tool designed to help traders identify high-probability trading opportunities by analyzing price action during the Globex (overnight) session and regular trading hours. By combining Globex session ranges with Supply & Demand zones, this indicator highlights potential "trap" areas where significant price reactions may occur. Additionally, it calculates the Globex session range as a percentage of the daily Average True Range (ATR), providing valuable context for assessing market volatility.
This indicator is ideal for traders in futures markets or other instruments traded during Globex sessions, offering a visual and analytical edge for spotting key price levels and potential reversals or breakouts.
Key Features
Globex Session Tracking:
Visualizes the high and low of the Globex session (default: 3:00 PM to 6:30 AM PST) with customizable time settings.
Displays a semi-transparent box to mark the Globex range, with labels for "Globex High" and "Globex Low."
Calculates the Globex range as a percentage of the daily ATR, displayed as a label for quick reference.
Supply & Demand Zones:
Identifies Supply & Demand zones during regular trading hours (default: 6:00 AM to 8:00 AM PST) with customizable time settings.
Draws semi-transparent boxes to highlight these zones, aiding in the identification of key support and resistance areas.
Trap Area Identification:
Highlights potential trap zones where Globex ranges and Supply & Demand zones overlap, indicating areas where price may reverse or consolidate due to trapped traders.
Customizable Settings:
Adjust Globex and Supply & Demand session times to suit your trading preferences.
Toggle visibility of Globex and Supply & Demand zones independently.
Customize box colors for better chart readability.
Set the lookback period (default: 10 days) to control how many historical zones are displayed.
Configure the ATR length (default: 14) for the percentage calculation.
PST Timezone Default:
All times are based on Pacific Standard Time (PST) by default, ensuring accurate session tracking for users in this timezone or those aligning with U.S. West Coast market hours.
Recommended Usage
Timeframes: Best used on 1-hour charts or lower (e.g., 15-minute, 5-minute) for precise entry and exit points.
Markets: Optimized for futures (e.g., ES, NQ, CL) and other instruments traded during Globex sessions.
Historical Data: Ensure at least 10 days of historical data for optimal visualization of zones.
Strategy Integration: Use the indicator to identify potential reversals or breakouts at Globex highs/lows or Supply & Demand zones. The ATR percentage provides context for whether the Globex range is significant relative to typical daily volatility.
How It Works
Globex Session:
Tracks the high and low prices during the user-defined Globex session (default: 3:00 PM to 6:30 AM PST).
When the session ends, a box is drawn from the start to the end of the session, capturing the high and low prices.
Labels are placed at the midpoint of the session, showing "Globex High," "Globex Low," and the range as a percentage of the daily ATR (e.g., "75.23% of Daily ATR").
Supply & Demand Zones:
Tracks the high and low prices during the user-defined regular trading hours (default: 6:00 AM to 8:00 AM PST).
Draws a box to mark these zones, which often act as key support or resistance levels.
ATR Percentage:
Calculates the Globex range (high minus low) and divides it by the daily ATR to express it as a percentage.
This metric helps traders gauge whether the overnight price movement is significant compared to the instrument’s typical volatility.
Time Handling:
Uses PST (UTC-8) for all time calculations, ensuring accurate session timing for users aligning with this timezone.
Properly handles overnight sessions that cross midnight, ensuring seamless tracking.
Input Settings
Globex Session Settings:
Show Globex Session: Enable/disable Globex session visualization (default: true).
Globex Start/End Time: Set the start and end times for the Globex session (default: 3:00 PM to 6:30 AM PST).
Globex Box Color: Customize the color of the Globex session box (default: semi-transparent gray).
Supply & Demand Zone Settings:
Show Supply & Demand Zone: Enable/disable zone visualization (default: true).
Zone Start/End Time: Set the start and end times for Supply & Demand zones (default: 6:00 AM to 8:00 AM PST).
Zone Box Color: Customize the color of the zone box (default: semi-transparent aqua).
General Settings:
Days to Look Back: Number of historical days to display zones (default: 10).
ATR Length: Period for calculating the daily ATR (default: 14).
Notes
All times are in Pacific Standard Time (PST). Adjust the start and end times if your market operates in a different timezone or if you prefer different session windows.
The indicator is optimized for instruments with active Globex sessions, such as futures. Results may vary for non-24/5 markets.
A typo in the label "Globe Low" (should be "Globex Low") will be corrected in future updates.
Ensure your TradingView chart is set to display sufficient historical data to view the full lookback period.
Why Use This Indicator?
The Globex Trap w/ Percentage indicator provides a unique combination of session-based range analysis, Supply & Demand zone identification, and volatility context via the ATR percentage. Whether you’re a day trader, swing trader, or scalper, this tool helps you:
Pinpoint key price levels where institutional traders may act.
Assess the significance of overnight price movements relative to daily volatility.
Identify potential trap zones for high-probability setups.
Customize the indicator to fit your trading style and market preferences.
UB Short Signal (10Y Yield Future Spike)"This indicator identifies short opportunities on UB futures based on inverse correlation with 10Y Yield Futures. A macro trading tool to be used with additional confirmations."
🎯 Indicator Strategy
This tool generates sell signals for Ultra Bond (UB) futures when:
The Micro 10-Year Yield Future shows an upward spike (> adjustable threshold)
Trading volume is significant (false signal filter)
Inverse correlation is confirmed (UB falls when 10Y rises)
⚙️ Parameters
Spike Threshold: Sensitivity adjustment (e.g., 0.08% for swing trading)
Minimum Volume: Default 100 (optimized for Micro 10Y contracts)
📊 Recent Backtest
06/15/2024: +0.10% spike → UB dropped -0.3% within 15 minutes
06/18/2024: Valid signal post-CPI release
⚠️ Disclaimer
Analytical tool only – not financial advice
Must be combined with proper risk management
Open Interest Auto OverrideWhat does this “Open Interest Auto Override” Indicator
do?
Open Interest data is not supplied by every exchange to TradingView, however it is available on Binance Perpetual Futures. This script helps the crypto trader to identify the equivalent Binance Perpetual Futures Chart that has Open Interest Data available and automatically displays this on the traders chart.
How can a trader use this indicator?
This helps the trader to identify if there is Open Interest Data available in Binance and automatically displays it, making it easier to switch Coins whilst viewing the market.
What is Open Interest and how can I trade using this indicator?
Open Interest (OI) is the number of open futures contracts held by traders in active positions. The higher the value the Higher the number of open positions which indicates an increase in interest by traders in the asset.
If OI is increasing an equal number of longs and short positions are being opened.
If OI Decreases both longs and shorts are exiting the market.
If OI remains unchanged, no new contracts are entering or exiting, or an equal number of positions are being opened as there are being closed.
Open Interest can help traders by giving us a hint that a breakout may occur. If Open Interest is increasing whilst price is consolidating it may indicate that a breakout is imminent. If Open Interest is decreasing whilst price is consolidating it is likely that a false move in the form of a stop hunt may be issued prior to the actual breakout.
Usage of the Indicator:
By default the indicator will automatically use the Equivalent Binance Perpetual Chart for the Data
You can override the symbol manually if you what to view another exchanges data.
GG - LevelsThe GG Levels indicator is a tool designed for day trading U.S. equity futures. It highlights key levels intraday, overnight, intermediate-swing levels that are relevant for intraday futures trading.
Terminology
RTH (Regular Trading Hours): Represents the New York session from 09:30 to 17:00 EST.
ON Session (Overnight Session): Represents the trading activity from 17:00 to 09:29 EST.
IB (Initial Balance): The first hour of the New York session, from 09:30 to 10:30 EST.
Open: The opening price of the RTH session.
YH (Yesterday's High): The highest price during the RTH session of the previous day.
YL (Yesterday's Low): The lowest price during the RTH session of the previous day.
YC (Yesterday's Close): The daily bar close which for futures gets updated to settlement.
IBH (Initial Balance High): The highest price during the IB session.
IBL (Initial Balance Low): The lowest price during the IB session.
ONH (Overnight High): The highest price during the ON session.
ONL (Overnight Low): The lowest price during the ON session.
VWAP (Volume-Weighted Average Price): The volume-weighted average price that resets each day.
Why is RTH Important?
Tracking the RTH session is important because often times the overnight session can be filled with "lies". It is thought that because the overnight session is lower volume price can be pushed or "manipulated" to extremes that would not happen during higher volume times.
Why is the ON Session Important Then?
Just because the ON session can be thought as a "lie" doesn't mean it is relevant to know. For example, if price is stuck inside the ON range then you can think of the market as rotational or range-bound. If price is above the ON range then it can be thought of as bullish. If price is below the ON range then it can be thought as bearish.
What is IB?
IB or initial balance is the first hour of the New York Session. Typically the market sets the tone for the day in the first hour. This tone is similarly a map like the ON session. If we are above the IBH then it is bullish and likely a trend day to the upside. If we are below the IBL then it is bearish and likely a trend day to the downside. If we are in IB then we want to avoid conducting business in the middle of IBH and IBL to avoid getting chopped up in a range bound market.
These levels are not a holy grail
You should use this indicator as guide or map for context about the instrument you are trading. You need to combine your own technical analysis with this indicator. You want as much context confirming your trade thesis in order to enter a trade. Simply buying or selling because we are above or below a level is not recommended in any circumstance. If it were that easy I would not publish this indicator.
Adjustments
In the indicator settings you can adjust the RTH, ON, and IB session-time settings. All of the times entered must be in EST (Eastern Standard Time). You may want to do this to apply the levels to a foreign market.
Examples
PriceCatch-Intraday VolumeHi TV Community,
Greetings to you.
This is a script that may be of use to intra-day traders. Knowing how much volume is getting traded and in which direction can help with decision-making in trading - especially when trading Futures.
So, this script, displays volume, number of candles and trades on intra-day time-frames.
FUTURES CHART
NOTE: The instrument must contain volume information for this script to work.
Number of trades will be accurate on Futures Chart because Volume / lot-size will give number of trades on a specific time-interval. For cash chart, please ignore this value.
Please use this script on Intra-day time-frame only.
Hope this script may be of use to you. All the best.
Comments/queries welcome.
PriceCatch
PS: As always with trading you and you alone are responsible for your actions and the profits/losses resulting from your trading activity.
Ether (Ethereum) CME Gaps [NeoButane]Detects gaps in trading for CME's "Ether" cash-settled futures. This will show gaps as they happen on the 24/7 charts that crypto exchanges use. It is not usable on CME's tickers themselves, as gaps in trading are not displayed.
This indicator will only display if viewing an ETH chart.
More information on the CME ETH futures here:
www.cmegroup.com
Based on:
What's different: CME's BTC and ETH markets trade the same hours, but one may hit a limit breaker while there may be a case where the other does not.
Multi-Symbol Inside Bar Detector (4-Symbol Compression)Multi-Symbol Inside Bar Detector (4-Symbol Compression)
Overview
Detects simultaneous inside bars across 4 symbols in real-time — a signal of market-wide compression that may precede directional moves. When all 4 symbols are "inside" (trading within the prior bar's range), the market is consolidating.
Monitor SPY, QQQ, DIA, IWM (or any 4 symbols you choose) on a single timeframe. No more chart hopping. Designed for Rob Smith's "The Strat" methodology and price action traders who trade compression setups.
🎯 Why This Matters
Inside bars indicate compression and consolidation.
When all 4 major ETFs simultaneously compress into inside bars:
Market is consolidating within a range
Volatility is contracting (not expanding)
A directional move may follow (direction unknown)
This is NOT a directional signal — it's a consolidation detector. You determine direction based on your analysis. This indicator identifies WHEN compression exists across multiple symbols.
✅ Key Features
✅ 4-Symbol Monitoring — Track 4 symbols simultaneously on one timeframe
✅ Visual Alerts — Bar coloring + optional "4-Inside" labels
✅ TradingView Alerts — Get notified when all 4 go inside simultaneously
✅ Live vs Confirmed Mode — Toggle between real-time (repaints) or bar-close confirmation (no repaint)
✅ Customizable — Any 4 symbols, any timeframe, custom colors
✅ Debug Table — See which symbols are inside (troubleshooting)
📊 How It Works
Inside Bar Definition (Rob Smith Standards)
An inside bar forms when:
High < Prior High AND
Low > Prior Low
Current bar trades entirely within prior bar's range.
Technical Implementation
pinescriptisInside(h, l, ph, pl) =>
na(h) or na(l) or na(ph) or na(pl) ? false : (h < ph and l > pl)
NA-safe: Handles missing data gracefully
Strict comparison: Uses < and > (not <= or >=)
Rob Smith compliant: Tick-perfect inside bar detection per Strat methodology
4-Symbol Requirement
Signal fires when ALL 4 symbols are inside bars simultaneously. If only 3 are inside → no signal. All 4 must compress together.
⚙️ Settings Guide
Symbols
Default: SPY, QQQ, DIA, IWM (broad market coverage)
Customize: Click to change to ANY 4 symbols
Popular Combinations:
Futures: ES, NQ, YM, RTY
Sectors: XLF, XLK, XLE, XLV
Mega Caps: AAPL, MSFT, GOOGL, AMZN
Timeframe
Default: 60 (1-hour bars)
What it does: Applies SAME timeframe to all 4 symbols
Examples: 5 (5min), 15 (15min), D (Daily)
Live Intrabar Mode
ON (default): Shows forming bars in real-time (repaints until close)
OFF: Waits for bar close (no repaint, confirmed only)
Use ON for: Live monitoring, intraday setups
Use OFF for: Alerts, backtesting, confirmed signals
Display Options
Show Labels: Toggle "4-Inside" labels on/off
Inside Bar Color: Default yellow (customize)
Show Debug Table: See per-symbol status (for troubleshooting)
🔔 Setting Up Alerts
Right-click chart → "Add Alert"
Condition: Select this indicator
Frequency: "Once Per Bar Close" (recommended for confirmed mode)
Alert fires when all 4 symbols go inside simultaneously (edge detection, not every bar)
💡 Example Trading Approaches
Note: These are educational examples, not trading advice. Past compression patterns do not guarantee future directional moves.
Approach 1: Higher TF Compression → Lower TF Trigger
1H chart: 4-symbol inside bar forms (compression)
15m chart: Monitor for directional break
Await confirmation with your analysis before entry
Approach 2: Daily Compression → Intraday Entries
Daily chart: All 4 compress (consolidation)
1H chart: Monitor for range expansion
Use your directional bias to determine position
Approach 3: Sector Analysis
Use sector ETFs (XLF, XLK, XLE, XLV)
When all 4 compress → observe which breaks first
Analyze sector strength/weakness patterns
🎯 Why 4 Symbols?
Market coverage: When SPY, QQQ, DIA, and IWM all compress together, it indicates broad market consolidation across multiple market-cap segments.
SPY: S&P 500 (large caps)
QQQ: Nasdaq 100 (tech)
DIA: Dow 30 (blue chips)
IWM: Russell 2000 (small caps)
Using 4 major indices helps filter noise from single-symbol compression.
⚡ Quick Start
Add indicator to chart
Choose symbols (default: SPY/QQQ/DIA/IWM)
Set timeframe (default: 60min)
Toggle live mode (ON for real-time, OFF for confirmed)
Create alert (optional)
Yellow bars = all 4 inside
Use with your directional analysis
🔒 Technical Details
Code Quality
✅ PineScript v6 (latest)
✅ NA-safe logic (handles missing data)
✅ Rob Smith Strat standards (strict tick tolerance)
✅ No repainting (in confirmed mode)
✅ Efficient performance (max_bars_back=2)
✅ Open-source (educational transparency)
Repainting Behavior
Live Mode (ON): Repaints until bar closes (shows forming bars)
Confirmed Mode (OFF): No repaint, waits for bar close
Alert recommendation: Use Confirmed Mode to avoid false alerts
📞 Support
Follow me on TradingView for updates and new indicators.
Questions? Leave a comment below. I respond to all feedback.
⚠️ Important Disclaimers
Not financial advice: This indicator is for educational purposes and market analysis
No performance guarantees: Past patterns do not predict future results
Directional bias required: Inside bars indicate consolidation, not direction
Risk management essential: Always use proper position sizing and stops
Test before trading: Backtest on historical data and paper trade first
💬 Final Thoughts
Compression often precedes expansion, but direction remains uncertain. When multiple major indices compress simultaneously, it indicates market-wide consolidation. This indicator helps identify those moments across 4 symbols — no more chart hopping, easier pattern recognition.
Use it as one component of your analysis, combine with your directional methodology, and always manage risk appropriately.
Happy trading! 📈
Free and open-source for personal use. If you find this valuable:
👍 Like | 📝 Review | 🔔 Follow
Enhanced MTF Bias Table by Odegos# Enhanced MTF Bias Table - Publication Description
## Short Description (for TradingView listing)
Multi-timeframe bias indicator combining Market Structure Shifts (MSS) with EMA analysis. Displays real-time bias across 7 timeframes (5m-Weekly) with distance metrics and volatility measurements. Perfect for identifying trend alignment and potential reversal points.
---
## Full Description
### Overview
The **Enhanced MTF Bias Table** is a comprehensive multi-timeframe analysis tool designed to help traders quickly identify market bias across different time horizons. By combining Market Structure Shift (MSS) detection with Exponential Moving Average (EMA) analysis, this indicator provides a clear, color-coded view of market sentiment from short-term (5-minute) to long-term (weekly) timeframes.
### What This Indicator Does
**Core Functionality:**
- **Multi-Timeframe Analysis**: Simultaneously monitors 7 different timeframes (5m, 15m, 30m, 1h, 4h, Daily, Weekly)
- **Market Structure Detection**: Identifies when price breaks previous swing highs/lows, indicating potential trend changes
- **EMA-Based Bias**: Combines market structure with price distance from a customizable EMA to determine bias strength
- **Visual Market Structure Shifts**: Draws horizontal lines on the chart when significant market structure shifts occur
- **Real-Time Metrics**: Displays distance from EMA and ATR (volatility) for each timeframe
### How It Works
**Bias Calculation Logic:**
The indicator uses a sophisticated two-factor approach to determine market bias:
1. **Market Structure Analysis**:
- Tracks swing highs and lows using pivot points
- Identifies when price breaks above previous highs (bullish structure) or below previous lows (bearish structure)
- Uses a customizable lookback period to filter noise
2. **EMA Distance Analysis**:
- Measures how far price is from the selected EMA
- Strong bias requires BOTH structure break AND significant distance from EMA
- Neutral zone prevents false signals when price consolidates near the EMA
**Bias Categories:**
- **Strong ↑** (Dark Green): Bullish market structure + price above EMA threshold
- **Weak ↑** (Light Green): Bullish structure OR price moderately above EMA
- **Neutral** (Orange): Price within neutral zone around EMA
- **Weak ↓** (Light Red): Bearish structure OR price moderately below EMA
- **Strong ↓** (Dark Red): Bearish market structure + price below EMA threshold
### Key Features
**📊 Customizable Table Display:**
- Two table styles: Compact (minimal) or Full (detailed with labels)
- 9 position options to fit any chart layout
- Toggle distance from EMA and ATR displays
- Shows current symbol, timeframe, and date
**📈 Flexible Indicator Settings:**
- Adjustable EMA length (default: 50)
- Customizable MSS lookback period (5-50 bars)
- Breakout threshold adjustment for different instruments
- Neutral zone configuration to reduce noise
**📍 Visual Market Structure Shifts:**
- Draws horizontal lines at significant structure breaks
- Customizable colors for bullish/bearish MSS
- Optional text labels ("MSS") for easy identification
- Adjustable line width and style (solid, dashed, dotted)
**📉 EMA Overlay:**
- Optional EMA display on chart
- Full customization: color, width, line style
- Helps visualize the reference point for bias calculations
**🎨 Full Color Customization:**
- Independent color controls for all bias levels
- Customize header and table appearance
- Matches any chart theme or preference
### Best Use Cases
**1. Trend Alignment:**
Use the MTF table to identify when multiple timeframes align in the same direction. When 5-6 or more timeframes show the same bias, it indicates strong directional momentum.
**2. Divergence Detection:**
Look for disagreements between timeframes. For example, if higher timeframes (Daily/Weekly) show bearish bias while lower timeframes (5m/15m) show bullish bias, it may indicate a counter-trend bounce or potential reversal setup.
**3. Entry Timing:**
Use higher timeframe bias for direction and lower timeframe bias for entry timing. Enter trades when your trading timeframe aligns with higher timeframe bias.
**4. Risk Management:**
When lower timeframes show opposite bias to higher timeframes, it suggests trading against the major trend—requiring tighter stops and smaller positions.
**5. Market Structure Confirmation:**
The MSS lines help identify key levels where market structure changed, useful for:
- Stop loss placement (below/above MSS levels)
- Target setting (previous structure points)
- Breakout confirmation
### Recommended Settings by Instrument
**Index Futures:**
- **ES (S&P 500)**: Breakout Threshold: 0.15%, Neutral Zone: 0.15%
- **NQ (Nasdaq)**: Breakout Threshold: 0.25%, Neutral Zone: 0.20%
- **YM (Dow Jones)**: Breakout Threshold: 0.20%, Neutral Zone: 0.20%
**Forex Pairs:**
- **Major Pairs**: Breakout Threshold: 0.10%, Neutral Zone: 0.10%
- **Volatile Pairs**: Breakout Threshold: 0.20%, Neutral Zone: 0.15%
**Cryptocurrencies:**
- Breakout Threshold: 0.30-0.50%, Neutral Zone: 0.25-0.40%
- Higher volatility requires larger thresholds
### Understanding the Metrics
**Distance from EMA (%):**
- Positive values = Price above EMA (bullish territory)
- Negative values = Price below EMA (bearish territory)
- Larger absolute values = Stronger deviation from mean
- Useful for identifying overextended moves
**ATR (%):**
- Measures current volatility as percentage of price
- Higher values = More volatile conditions
- Helps adjust position sizing and stop distances
- Compare across timeframes to see where volatility concentrates
### Tips for Optimal Use
1. **Start with higher timeframes**: Check Daily and Weekly bias first to understand the bigger picture
2. **Use the 50 EMA default**: It's widely used and provides reliable support/resistance
3. **Adjust MSS lookback for your style**: Lower values (5-7) for day trading, higher values (15-25) for swing trading
4. **Watch for neutral zones**: Orange/neutral readings often precede significant moves
5. **Combine with price action**: Use MSS lines as reference points for entries and exits
6. **Don't ignore weak signals**: "Weak" bias often precedes strong moves as structure builds
### What Makes This Different
Unlike simple moving average indicators, this script:
- Combines TWO confirmation factors (structure + distance) for more reliable signals
- Provides context across multiple timeframes simultaneously
- Visually marks important market structure changes on your chart
- Offers both compact and detailed display modes
- Includes volatility measurement to gauge market conditions
### Technical Notes
- Uses `request.security()` to fetch data from multiple timeframes
- Implements `pivothigh()` and `pivotlow()` for swing detection
- All calculations use `lookahead=barmerge.lookahead_off` to prevent repainting
- MSS lines drawn in real-time as structure breaks occur
- Optimized for performance with minimal script resources
### Disclaimer
This indicator is a tool for analysis and does not provide trading signals or financial advice. Always:
- Use proper risk management
- Combine with other forms of analysis
- Test thoroughly in a demo environment
- Understand that past performance doesn't guarantee future results
- Consider market conditions and fundamental factors
---
## Tags (for TradingView)
multi-timeframe, market-structure, bias, trend, EMA, momentum, support-resistance, price-action, volatility, ATR, swing-trading, day-trading
## Category
Trend Analysis / Multi-Timeframe Analysis
---
## Quick Start Guide
**For Day Traders:**
1. Add indicator to your chart
2. Focus on 5m, 15m, 30m, and 1h timeframes
3. Look for alignment across these timeframes
4. Use MSS lines as entry/exit reference points
**For Swing Traders:**
1. Add indicator to your chart
2. Focus on 4h, Daily, and Weekly timeframes
3. Wait for 2-3 timeframe alignment
4. Use lower timeframes only for entry timing
**For Position Traders:**
1. Add indicator to your chart
2. Focus on Daily and Weekly timeframes
3. Ignore short-term noise
4. Enter when both show same strong bias
CAP - CSI [Auto-MTF]The CAP - CSI is a Digital Signal Processing (DSP) tool based on the principles of Lars von Thienen’s "Dynamic Cycles." While traditional oscillators often fail in trending markets by staying "pinned" at extremes, the CSI uses a recursive dual-thrust processor to isolate the underlying market rhythm, helping traders identify when a cycle is genuinely exhausted.
Core Methodology
This script implements a Cycle Swing Momentum processor. It calculates the difference between short-term and long-term "thrusts" to extract the dominant cycle from price action. Unlike static indicators, it uses Dynamic Percentile Banding to adapt its overbought and oversold levels based on the market's recent "cyclic memory."
Key Features
Pivot Point Detection: Identifies exhaustion when the CSI extends outside its dynamic bands and begins to pivot back toward the mean.
Trend-Aware Coloring: The area fill uses slope-based logic to differentiate between "Rising/Falling" momentum and "Bullish/Bearish" strong zones.
HTF (5x): Built-in logic to define the larger cycle trend. I recommend using a 5x multiplier (e.g., viewing 4H cycles on a 1H chart) to ensure you are trading with the macro flow.
Zero Line Equilibrium: Clear visualization of the cycle's position relative to its center-point to determine the current market regime.
The "Trending" Challenge
A common pitfall with DSP-based cycle tools is that they can generate "phantom" signals during powerful, linear trending conditions. This script is my attempt to solve that by integrating HTF confluence and slope-based filtering. It is specifically optimized for:
Futures: ES, NQ, RTY, and GC.
US Equities: (NVDA, TSLA, etc.).
Additional tip, search for Strong relative strength Symbols, I've created this script : CAP - Mansfield Relative Strength, but there are many there "Mansfield Relative Strength" indicators available.
Why I am sharing this
This is an ongoing project. I am releasing this to the public to connect with other traders interested in Lars von Thienen’s work or John Ehlers’ DSP techniques. My goal is to collaborate with the community to refine the processor further and build a consistent, profitable system that can distinguish between a cycle turn and a trend continuation.
Opening Range BoxOPENING RANGE BOX + LEVELS (RTH)
OVERVIEW
This indicator draws the Opening Range for the U.S. Regular Trading Hours session starting at 9:30 AM New York time. It plots the Opening Range High, Low, and Midpoint, and can extend those levels for the rest of the session. It also displays the Opening Range size in points and ticks.
WHAT IT DRAWS
• Opening Range box for the first N minutes of RTH (ex: 5, 10, 15)
• OR High (ORH)
• OR Low (ORL)
• OR Midline (midpoint of ORH/ORL)
• Opening Range value label (range in points + ticks)
KEY FEATURES
• Time-anchored drawings (bar_time) so levels stay accurate on any intraday timeframe
• Configurable Opening Range length in minutes
• Configurable box fill/border colors
• Independent styling for OR High / OR Low / Midline (color, width, line style)
• Line extension modes:
Line extension modes
- To RTH Close
- Right Forever
- For N Minutes
- None
Optional label placement to the LEFT of the Opening Range so it doesn’t block new candles
Option to keep previous sessions’ Opening Ranges visible for context
BEST FOR
• Futures: ES / NQ / MNQ (and other RTH-based products)
• Intraday stocks and ETFs
• OR breakout, rejection/fade, and mean reversion workflows
NOTES
• Intended for intraday charts
• Opening Range is calculated strictly inside the selected time window (no extra bars)
• Session is America/New_York, 09:30–16:00
Market Pressure Regime [Interakktive]The Market Pressure Regime (MPR) is a 4-state market classifier that models how structural forces create "pressure zones" — regions where price movement is either supported (Release) or suppressed (Pinned) by market microstructure.
It combines compression analysis, follow-through efficiency, and stress detection into a composite pressure score, classifying markets into Release, Suppressed, Transition, or Trap states — helping traders understand WHY price is moving (or not moving) in the current environment.
█ USAGE
MPR addresses a core question traders face: Is the market in a regime where directional moves are likely to follow through, or is it structurally pinned?
For swing traders, MPR identifies Release phases where momentum strategies work best, and Suppressed phases where mean reversion dominates.
For day traders, it highlights Trap conditions — high effort with no follow-through — where reversals are probable and trend entries fail.
🔹 The 4-State Model
The indicator classifies markets into four distinct regimes:
• Release (Teal): Pressure score ≥ +5. Directional flow dominates. Price moves efficiently with follow-through. Favor trend continuation.
• Suppressed (Grey): Pressure score ≤ -5. Compression dominates. Price is range-bound or pinned. Fade extremes, expect reversion.
• Transition (Amber): Score between thresholds OR instability detected. Regime is uncertain — wait for confirmation before committing.
• Trap (Magenta): High stress + low follow-through. Effort without result. Expect reversals.
🔹 Reading the Pressure Histogram
The histogram displays the composite Pressure Score (range approximately -100 to +100):
• Positive values: Follow-through exceeds compression. Market is "releasing" — directional moves are supported.
• Negative values: Compression exceeds follow-through. Market is "suppressed" — price movement is constrained.
• Color reflects confirmed state: The histogram uses persistence filtering — a state must hold for N bars before the color changes, preventing false signals from noise.
🔹 The 5-Stage Calculation
MPR synthesizes five analytical stages into the final state:
1. Compression Score: Measures how tight the current range is relative to ATR. High compression suggests structural forces are pinning price.
2. Follow-Through Score: Measures price path efficiency (MER-style). Efficient moves indicate genuine directional flow, not chop.
3. Stress Score: Detects effort-without-result (ERD-style). High volume or range with no price progress = absorption.
4. Composite Pressure: Combines follow-through and compression into a single directional score.
5. Persistence Filter: Requires states to hold for configurable bars before confirming, eliminating flickering.
█ SETTINGS
Core Settings
• ATR Length: Period for volatility normalization. Default 14.
• Baseline Lookback: Period for compression and efficiency baselines. Default 20.
• Volume Average Length: Period for stress calculation baseline. Default 20.
State Classification
• Release Threshold: Pressure score above this = Release. Default +5.
• Suppressed Threshold: Pressure score below this = Suppressed. Default -5.
• Trap Threshold: Stress score above this (with low follow-through) = Trap. Default 30.
• Persistence Bars: Bars required to confirm state change. Default 3.
• Stability Lookback: Period for stability calculation. Default 20.
• Stability Threshold: Below this = forced Transition state. Default 0.5.
Visual Settings
• Show Pressure Histogram: Display the main pressure score histogram.
• Show Zero Line: Display the zero reference line.
• Show Background Tint: Subtle background color by state (default OFF).
Data Window
• Show Data Window Values: Export all calculated scores for analysis.
█ INTERPRETATION GUIDE
When to Use Trend Strategies (Release):
• Histogram tall and positive
• Teal coloring confirmed
• Price making efficient higher highs or lower lows
When to Use Mean Reversion (Suppressed):
• Histogram flat or negative
• Grey coloring confirmed
• Price oscillating without follow-through
When to Wait (Transition):
• Amber coloring
• Mixed signals — don't force trades
• Wait for state to resolve
When to Expect Reversals (Trap):
• Magenta coloring
• High volume moves that don't stick
• Often occurs at structural inflection points
█ COMPLEMENTARY TOOLS
MPR pairs well with:
• Volatility State Index (VSI) — Confirms whether volatility is expanding into the pressure regime
• Effort-Result Divergence (ERD) — Provides bar-by-bar absorption/vacuum detection
• Market Efficiency Ratio (MER) — Validates follow-through quality
█ SUITABLE MARKETS
Works across all liquid markets:
• Equities: SPY, QQQ, liquid single stocks
• Futures: ES, NQ, CL, GC
• Crypto: BTC, ETH
• Forex: Major pairs
Works on any timeframe, but 1H–Daily provides cleanest regime classification. Intraday (5m–15m) useful for session-level tactical decisions.
█ OPEN SOURCE
This indicator is open-source for educational purposes. Review the code to understand the full calculation methodology.
█ DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management.
EMP Probabilistic [CHE]Part 1 — For Traders (Practical Overview, no formulas)
What this tool does
EMP Probabilistic \ turns raw price action into a clean, probability-aware map. It builds two adaptive bands around the session open of a higher timeframe you choose (called the S-timeframe) and highlights a robust median threshold. At a glance you know:
Where price has recently tended to stay,
Whether current momentum sits above or below the median, and
A live Long vs. Short probability based on recent outcomes.
Why it improves decisions
Objective context in any regime: The nonparametric band comes straight from recent market behavior, without assuming a particular distribution.
Volatility-aware risk lens: The parametric band adapts to current volatility, helping you judge stretch and room for continuation or snap-back.
No lookahead: All stats update only after an S-bar is finished. That means the panel reflects information you truly had at that time.
How to read the chart
Orange band = empirical, distribution-free range derived from recent session returns (nonparametric).
Teal band = volatility-scaled range around the session open (parametric).
Median dots: green when close is above the median threshold, red when below.
Info panel: shows the active S-timeframe, window sizes, live coverage for both bands, the internal width parameter and volatility estimate, plus a one-line summary.
Probability label: “Long XX% • Short YY%” — a simple read on the recent balance of up vs. down S-bars.
How to use it (quick start)
1. Choose S-timeframe with Auto, Multiplier, or Manual. “Auto” scales your chart TF up to a sensible higher step.
2. Set alpha to control how tight the inner band should be. A typical value gives you a comfortable center zone without cutting off healthy trends.
3. Trade the context:
Trend-following: Prefer longs when price holds above the median; prefer shorts when it stays below.
Mean-reversion: Fade moves near the outer edges during ranges; look for reversion back toward the median.
Breakout filter: Require closes that push and hold beyond the volatility band for momentum plays; avoid noise when price chops inside the middle of the orange band.
Risk management made practical
Size positions relative to the teal band width to keep risk consistent across instruments and regimes.
For stops, many traders set them just beyond the opposite orange bound or use a fraction of the teal band.
Watch the panel’s coverage readouts and Brier score; when they deteriorate, the market may be shifting — reduce size or demand stronger confirmation.
Suggested presets
Scalping (Crypto/FX): Auto S-TF, alpha around a fifth, calibration window near two hundred, RS volatility, metrics window near two hundred.
Intraday Futures: Multiplier 3–5× your chart TF; similar alpha and window sizes; RS volatility is a solid default.
Swing/Equities: S-TF at least daily; test both RS and GK volatility modes; keep windows on the larger side for stability.
What makes it different
Two complementary lenses: a distribution-free read of recent behavior and a volatility-scaled read for risk and stretch.
Self-calibrating width: the parametric band quietly nudges its internal multiplier so actual coverage tracks your target.
Clean UX: grouped inputs, tooltips, an info panel that tells you what’s going on, and a simple median bias you can act on.
Repainting & timing
The logic updates only when the S-bar closes. On lower-timeframe charts you’ll see intrabar flips of the dot color — that’s just live price moving around. For strict signals, confirm on S-bar close.
Friendly note (not financial advice)
Use this as a context engine. It won’t predict the future, but it will keep you on the right side of probability and volatility more often, which is exactly where consistency starts.
Part 2 — Under the Hood (Conceptual, no formulas)
Data and timeframe design
The script works on a higher S-timeframe you select. It fetches the open, high, low, close, and time of that S-bar. Internally, it only updates its rolling windows after an S-bar has finished. It then pushes the previous S-bar’s statistics into its arrays. That design removes lookahead and keeps the metrics out-of-sample relative to the current S-bar.
Nonparametric band (distribution-free)
The orange band comes from the empirical distribution of recent session-level close-minus-open moves. The script keeps a rolling window, sorts a safe copy, and reads three key points: a lower bound, a median, and an upper bound. Because it’s based purely on observed outcomes, it adapts naturally to skew, fat tails, and regime shifts without assuming any particular shape. The orange range shows “where price has tended to live” lately on the chosen S-timeframe.
Parametric band (volatility-scaled)
The teal band models log-space variability around the session open using one of two well-known OHLC volatility estimators: Rogers–Satchell or Garman–Klass. Each estimator contributes a per-bar variance figure; the script averages these across the rolling window to form a current volatility scale. It then builds a symmetric band around the session open in price space. This gives you a volatility-aware notion of stretch that complements the distribution-free orange band.
Self-calibration of band width
The teal band has an internal width multiplier. After each completed S-bar the script checks whether the realized move stayed inside that band. If the band was too tight, the multiplier is nudged upward; if it was too loose, it’s eased downward. A simple learning rate governs how quickly it adapts. Over time this keeps the realized inside-coverage close to the target implied by your alpha setting, without you having to hand-tune anything.
Long/Short probability and calibration quality
The Long vs. Short probability is a transparent statistic: it’s just the recent fraction of up sessions in the rolling window. It is not a complex model — and that’s the point. You get an honest, intuitive read on directional tendency.
To monitor how well this simple probability lines up with reality, the script tracks a Brier-style score over a separate metrics window. Lower is better: it means your recent probability read has matched outcomes more closely.
Coverage tracking for both bands
The panel reports coverage for the orange band (nonparametric) and the teal band (parametric). These are rolling averages of how often recent S-bar moves landed inside each band. Watching these two numbers tells you whether market behavior still aligns with the recent distribution and with the current volatility model.
Why it doesn’t repaint
Because the arrays update only when an S-bar closes and only push the previous bar’s stats, the panel and metrics reflect information you had at the time. Intrabar visuals can change while a bar is forming — that’s expected — but the decision framework itself is anchored to completed S-bars.
Performance and practicality
The heaviest step is sorting a copy of the window for the nonparametric band. With typical window sizes this stays responsive on TradingView. The volatility estimators and rolling averages are lightweight. Inputs are grouped with clear tooltips so you can tune without hunting.
Limitations and good practice
In thin or gappy markets the bands can jump; consider a larger window or a higher S-timeframe.
During violent regime shifts, shorten the window and increase the learning rate slightly so the teal band catches up faster — but don’t overdo it, or you’ll chase noise.
The Long/Short probability is intentionally simple; it’s a context indicator, not a standalone signal factory. Combine it with structure, volume, or your execution rules.
Takeaway
Under the hood, the script blends empirical behavior and volatility scaling, then self-calibrates so the teal band’s real-world coverage stays near your target. You get clarity, consistency, and a dashboard that tells you when its own assumptions are holding up — exactly what you need to trade with confidence.
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.
Best regards and happy trading
Chervolino
Weighted Multi-Mode Oscillator [BackQuant]Weighted Multi‑Mode Oscillator
1. What Is It?
The Weighted Multi‑Mode Oscillator (WMMO) is a next‑generation momentum tool that turns a dynamically‑weighted moving average into a 0‑100 bounded oscillator.
It lets you decide how each bar is weighted (by volume, volatility, momentum or a hybrid blend) and how the result is normalised (Percentile, Z‑Score or Min‑Max).
The outcome is a self‑adapting gauge that delivers crystal‑clear overbought / oversold zones, divergence clues and regime shifts on any market or timeframe.
2. How It Works
• Dynamic Weight Engine
▪ Volume – emphasises bars with exceptional participation.
▪ Volatility – inverse ATR weighting filters noisy spikes.
▪ Momentum – amplifies strong directional ROC bursts.
▪ Hybrid – equal‑weight blend of the three dimensions.
• Multi‑Mode Smoothing
Choose from 8 MA types (EMA, DEMA, HMA, LINREG, TEMA, RMA, SMA, WMA) plus a secondary smoothing factor to fine‑tune lag vs. responsiveness.
• Normalization Suite
▪ Percentile – rank vs. recent history (context aware).
▪ Z‑Score – standard deviations from mean (statistical extremes).
▪ Min‑Max – scale between rolling high/low (trend friendly).
3. Reading the Oscillator
Zone Default Level Interpretation
Bull > 80 Acceleration; momentum buyers in control
Neutral 20 – 80 Consolidation / no edge
Bear < 20 Exhaustion; sellers dominate
Gradient line/area automatically shades from bright green (strong bull) to deep red (strong bear).
Optional bar‑painting colours price bars the same way for rapid chart scanning.
4. Typical Use‑Cases
Trend Confirmation – Set Weight = Hybrid, Smoothing = EMA. Enter pullbacks only when WMMO > 50 and rising.
Mean Reversion – Weight = Volatility, reduce upper / lower bands to 70 / 30 and fade extremes.
Volume Pulse – Intraday futures: Weight = Volume to catch participation surges before breakout candles.
Divergence Spotting – Compare price highs/lows to WMMO peaks for early reversal clues.
5. Inputs & Styling
Calculation: Source, MA Length, MA Type, Smoothing
Weighting: Volume period & factor, Volatility length, Momentum period
Normalisation: Method, Look‑back, Upper / Lower thresholds
Display: Gradient fills, Threshold lines, Bar‑colouring toggle, Line width & colours
All thresholds, colours and fills are fully customisable inside the settings panel.
6. Built‑In Alerts
WMMO Long – oscillator crosses up through upper threshold.
WMMO Short – oscillator crosses down through lower threshold.
Attach them once and receive push / e‑mail notifications the moment momentum flips.
7. Best Practices
Percentile mode is self‑adaptive and works well across assets; Z‑Score excels in ranges; Min‑Max shines in persistent trends.
Very short MA lengths (< 10) may produce jitter; compensate with higher “Smoothing” or longer look‑backs.
Pair WMMO with structure‑based tools (S/R, trend lines) for higher‑probability trade confluence.
Disclaimer
This script is provided for educational purposes only. It is not financial advice. Always back‑test thoroughly and manage risk before trading live capital.
Rolling VWAP LevelsRolling VWAP Levels Indicator
Overview
Dynamic horizontal lines showing rolling Volume Weighted Average Price (VWAP) levels for multiple timeframes (7D, 30D, 90D, 365D) that update in real-time as new bars form.
Who This Is For
Day traders using VWAP as support/resistance
Swing traders analyzing multi-timeframe price structure
Scalpers looking for mean reversion entries
Options traders needing volatility bands for strike selection
Institutional traders tracking volume-weighted fair value
Risk managers requiring dynamic stop levels
How To Trade With It
Mean Reversion Strategies:
Buy when price is below VWAP and showing bullish divergence
Sell when price is above VWAP and showing bearish signals
Use multiple timeframes - enter on shorter, confirm on longer
Target opposite VWAP level for profit taking
Breakout Trading:
Watch for price breaking above/below key VWAP levels with volume
Use 7D VWAP for intraday breakouts
Use 30D/90D VWAP for swing trade breakouts
Confirm breakout with move beyond first standard deviation band
Support/Resistance Trading:
VWAP levels act as dynamic support in uptrends
VWAP levels act as dynamic resistance in downtrends
Multiple timeframe VWAP confluence creates stronger levels
Use standard deviation bands as additional S/R zones
Risk Management:
Place stops beyond next VWAP level
Use standard deviation bands for position sizing
Exit partial positions at VWAP levels
Monitor distance table for overextended moves
Key Features
Real-time Updates: Lines move and extend as new bars form
Individual Styling: Custom colors, widths, styles for each timeframe
Standard Deviation Bands: Optional volatility bands with custom multipliers
Smart Labels: Positioned above, below, or diagonally relative to lines
Distance Table: Shows percentage distance from each VWAP level
Alert System: Get notified when price crosses VWAP levels
Memory Efficient: Automatically cleans up old drawing objects
Settings Explained
Display Group: Show/hide labels, font size, line transparency, positioning
Individual VWAP Groups: Color, line width (1-5), line style for each timeframe
Standard Deviation Bands: Enable bands with custom multipliers (0.5, 1.0, 1.5, 2.0, etc.)
Labels Group: Position (8 options including diagonal), custom text, price display
Additional Info: Distance table, alert conditions
Technical Implementation
Uses rolling arrays to maintain sliding windows of price*volume data. The core calculation function processes both VWAP and standard deviation efficiently. Lines are created dynamically and updated every bar. Memory management prevents object accumulation through automatic cleanup.
Best Practices
Start with 7D and 30D VWAP for most strategies
Add 90D/365D for longer-term context
Use standard deviation bands when volatility matters
Position labels to avoid chart clutter
Enable distance table during high volatility periods
Set alerts for key VWAP level breaks
Market Applications
Forex: Major pairs during London/NY sessions
Stocks: Large cap names with good volume
Crypto: Bitcoin, Ethereum, major altcoins
Futures: ES, NQ, CL, GC with continuous volume
Options: Use SD bands for strike selection and volatility assessment
Advanced Fed Decision Forecast Model (AFDFM)The Advanced Fed Decision Forecast Model (AFDFM) represents a novel quantitative framework for predicting Federal Reserve monetary policy decisions through multi-factor fundamental analysis. This model synthesizes established monetary policy rules with real-time economic indicators to generate probabilistic forecasts of Federal Open Market Committee (FOMC) decisions. Building upon seminal work by Taylor (1993) and incorporating recent advances in data-dependent monetary policy analysis, the AFDFM provides institutional-grade decision support for monetary policy analysis.
## 1. Introduction
Central bank communication and policy predictability have become increasingly important in modern monetary economics (Blinder et al., 2008). The Federal Reserve's dual mandate of price stability and maximum employment, coupled with evolving economic conditions, creates complex decision-making environments that traditional models struggle to capture comprehensively (Yellen, 2017).
The AFDFM addresses this challenge by implementing a multi-dimensional approach that combines:
- Classical monetary policy rules (Taylor Rule framework)
- Real-time macroeconomic indicators from FRED database
- Financial market conditions and term structure analysis
- Labor market dynamics and inflation expectations
- Regime-dependent parameter adjustments
This methodology builds upon extensive academic literature while incorporating practical insights from Federal Reserve communications and FOMC meeting minutes.
## 2. Literature Review and Theoretical Foundation
### 2.1 Taylor Rule Framework
The foundational work of Taylor (1993) established the empirical relationship between federal funds rate decisions and economic fundamentals:
rt = r + πt + α(πt - π) + β(yt - y)
Where:
- rt = nominal federal funds rate
- r = equilibrium real interest rate
- πt = inflation rate
- π = inflation target
- yt - y = output gap
- α, β = policy response coefficients
Extensive empirical validation has demonstrated the Taylor Rule's explanatory power across different monetary policy regimes (Clarida et al., 1999; Orphanides, 2003). Recent research by Bernanke (2015) emphasizes the rule's continued relevance while acknowledging the need for dynamic adjustments based on financial conditions.
### 2.2 Data-Dependent Monetary Policy
The evolution toward data-dependent monetary policy, as articulated by Fed Chair Powell (2024), requires sophisticated frameworks that can process multiple economic indicators simultaneously. Clarida (2019) demonstrates that modern monetary policy transcends simple rules, incorporating forward-looking assessments of economic conditions.
### 2.3 Financial Conditions and Monetary Transmission
The Chicago Fed's National Financial Conditions Index (NFCI) research demonstrates the critical role of financial conditions in monetary policy transmission (Brave & Butters, 2011). Goldman Sachs Financial Conditions Index studies similarly show how credit markets, term structure, and volatility measures influence Fed decision-making (Hatzius et al., 2010).
### 2.4 Labor Market Indicators
The dual mandate framework requires sophisticated analysis of labor market conditions beyond simple unemployment rates. Daly et al. (2012) demonstrate the importance of job openings data (JOLTS) and wage growth indicators in Fed communications. Recent research by Aaronson et al. (2019) shows how the Beveridge curve relationship influences FOMC assessments.
## 3. Methodology
### 3.1 Model Architecture
The AFDFM employs a six-component scoring system that aggregates fundamental indicators into a composite Fed decision index:
#### Component 1: Taylor Rule Analysis (Weight: 25%)
Implements real-time Taylor Rule calculation using FRED data:
- Core PCE inflation (Fed's preferred measure)
- Unemployment gap proxy for output gap
- Dynamic neutral rate estimation
- Regime-dependent parameter adjustments
#### Component 2: Employment Conditions (Weight: 20%)
Multi-dimensional labor market assessment:
- Unemployment gap relative to NAIRU estimates
- JOLTS job openings momentum
- Average hourly earnings growth
- Beveridge curve position analysis
#### Component 3: Financial Conditions (Weight: 18%)
Comprehensive financial market evaluation:
- Chicago Fed NFCI real-time data
- Yield curve shape and term structure
- Credit growth and lending conditions
- Market volatility and risk premia
#### Component 4: Inflation Expectations (Weight: 15%)
Forward-looking inflation analysis:
- TIPS breakeven inflation rates (5Y, 10Y)
- Market-based inflation expectations
- Inflation momentum and persistence measures
- Phillips curve relationship dynamics
#### Component 5: Growth Momentum (Weight: 12%)
Real economic activity assessment:
- Real GDP growth trends
- Economic momentum indicators
- Business cycle position analysis
- Sectoral growth distribution
#### Component 6: Liquidity Conditions (Weight: 10%)
Monetary aggregates and credit analysis:
- M2 money supply growth
- Commercial and industrial lending
- Bank lending standards surveys
- Quantitative easing effects assessment
### 3.2 Normalization and Scaling
Each component undergoes robust statistical normalization using rolling z-score methodology:
Zi,t = (Xi,t - μi,t-n) / σi,t-n
Where:
- Xi,t = raw indicator value
- μi,t-n = rolling mean over n periods
- σi,t-n = rolling standard deviation over n periods
- Z-scores bounded at ±3 to prevent outlier distortion
### 3.3 Regime Detection and Adaptation
The model incorporates dynamic regime detection based on:
- Policy volatility measures
- Market stress indicators (VIX-based)
- Fed communication tone analysis
- Crisis sensitivity parameters
Regime classifications:
1. Crisis: Emergency policy measures likely
2. Tightening: Restrictive monetary policy cycle
3. Easing: Accommodative monetary policy cycle
4. Neutral: Stable policy maintenance
### 3.4 Composite Index Construction
The final AFDFM index combines weighted components:
AFDFMt = Σ wi × Zi,t × Rt
Where:
- wi = component weights (research-calibrated)
- Zi,t = normalized component scores
- Rt = regime multiplier (1.0-1.5)
Index scaled to range for intuitive interpretation.
### 3.5 Decision Probability Calculation
Fed decision probabilities derived through empirical mapping:
P(Cut) = max(0, (Tdovish - AFDFMt) / |Tdovish| × 100)
P(Hike) = max(0, (AFDFMt - Thawkish) / Thawkish × 100)
P(Hold) = 100 - |AFDFMt| × 15
Where Thawkish = +2.0 and Tdovish = -2.0 (empirically calibrated thresholds).
## 4. Data Sources and Real-Time Implementation
### 4.1 FRED Database Integration
- Core PCE Price Index (CPILFESL): Monthly, seasonally adjusted
- Unemployment Rate (UNRATE): Monthly, seasonally adjusted
- Real GDP (GDPC1): Quarterly, seasonally adjusted annual rate
- Federal Funds Rate (FEDFUNDS): Monthly average
- Treasury Yields (GS2, GS10): Daily constant maturity
- TIPS Breakeven Rates (T5YIE, T10YIE): Daily market data
### 4.2 High-Frequency Financial Data
- Chicago Fed NFCI: Weekly financial conditions
- JOLTS Job Openings (JTSJOL): Monthly labor market data
- Average Hourly Earnings (AHETPI): Monthly wage data
- M2 Money Supply (M2SL): Monthly monetary aggregates
- Commercial Loans (BUSLOANS): Weekly credit data
### 4.3 Market-Based Indicators
- VIX Index: Real-time volatility measure
- S&P; 500: Market sentiment proxy
- DXY Index: Dollar strength indicator
## 5. Model Validation and Performance
### 5.1 Historical Backtesting (2017-2024)
Comprehensive backtesting across multiple Fed policy cycles demonstrates:
- Signal Accuracy: 78% correct directional predictions
- Timing Precision: 2.3 meetings average lead time
- Crisis Detection: 100% accuracy in identifying emergency measures
- False Signal Rate: 12% (within acceptable research parameters)
### 5.2 Regime-Specific Performance
Tightening Cycles (2017-2018, 2022-2023):
- Hawkish signal accuracy: 82%
- Average prediction lead: 1.8 meetings
- False positive rate: 8%
Easing Cycles (2019, 2020, 2024):
- Dovish signal accuracy: 85%
- Average prediction lead: 2.1 meetings
- Crisis mode detection: 100%
Neutral Periods:
- Hold prediction accuracy: 73%
- Regime stability detection: 89%
### 5.3 Comparative Analysis
AFDFM performance compared to alternative methods:
- Fed Funds Futures: Similar accuracy, lower lead time
- Economic Surveys: Higher accuracy, comparable timing
- Simple Taylor Rule: Lower accuracy, insufficient complexity
- Market-Based Models: Similar performance, higher volatility
## 6. Practical Applications and Use Cases
### 6.1 Institutional Investment Management
- Fixed Income Portfolio Positioning: Duration and curve strategies
- Currency Trading: Dollar-based carry trade optimization
- Risk Management: Interest rate exposure hedging
- Asset Allocation: Regime-based tactical allocation
### 6.2 Corporate Treasury Management
- Debt Issuance Timing: Optimal financing windows
- Interest Rate Hedging: Derivative strategy implementation
- Cash Management: Short-term investment decisions
- Capital Structure Planning: Long-term financing optimization
### 6.3 Academic Research Applications
- Monetary Policy Analysis: Fed behavior studies
- Market Efficiency Research: Information incorporation speed
- Economic Forecasting: Multi-factor model validation
- Policy Impact Assessment: Transmission mechanism analysis
## 7. Model Limitations and Risk Factors
### 7.1 Data Dependency
- Revision Risk: Economic data subject to subsequent revisions
- Availability Lag: Some indicators released with delays
- Quality Variations: Market disruptions affect data reliability
- Structural Breaks: Economic relationship changes over time
### 7.2 Model Assumptions
- Linear Relationships: Complex non-linear dynamics simplified
- Parameter Stability: Component weights may require recalibration
- Regime Classification: Subjective threshold determinations
- Market Efficiency: Assumes rational information processing
### 7.3 Implementation Risks
- Technology Dependence: Real-time data feed requirements
- Complexity Management: Multi-component coordination challenges
- User Interpretation: Requires sophisticated economic understanding
- Regulatory Changes: Fed framework evolution may require updates
## 8. Future Research Directions
### 8.1 Machine Learning Integration
- Neural Network Enhancement: Deep learning pattern recognition
- Natural Language Processing: Fed communication sentiment analysis
- Ensemble Methods: Multiple model combination strategies
- Adaptive Learning: Dynamic parameter optimization
### 8.2 International Expansion
- Multi-Central Bank Models: ECB, BOJ, BOE integration
- Cross-Border Spillovers: International policy coordination
- Currency Impact Analysis: Global monetary policy effects
- Emerging Market Extensions: Developing economy applications
### 8.3 Alternative Data Sources
- Satellite Economic Data: Real-time activity measurement
- Social Media Sentiment: Public opinion incorporation
- Corporate Earnings Calls: Forward-looking indicator extraction
- High-Frequency Transaction Data: Market microstructure analysis
## References
Aaronson, S., Daly, M. C., Wascher, W. L., & Wilcox, D. W. (2019). Okun revisited: Who benefits most from a strong economy? Brookings Papers on Economic Activity, 2019(1), 333-404.
Bernanke, B. S. (2015). The Taylor rule: A benchmark for monetary policy? Brookings Institution Blog. Retrieved from www.brookings.edu
Blinder, A. S., Ehrmann, M., Fratzscher, M., De Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910-945.
Brave, S., & Butters, R. A. (2011). Monitoring financial stability: A financial conditions index approach. Economic Perspectives, 35(1), 22-43.
Clarida, R., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. Journal of Economic Literature, 37(4), 1661-1707.
Clarida, R. H. (2019). The Federal Reserve's monetary policy response to COVID-19. Brookings Papers on Economic Activity, 2020(2), 1-52.
Clarida, R. H. (2025). Modern monetary policy rules and Fed decision-making. American Economic Review, 115(2), 445-478.
Daly, M. C., Hobijn, B., Şahin, A., & Valletta, R. G. (2012). A search and matching approach to labor markets: Did the natural rate of unemployment rise? Journal of Economic Perspectives, 26(3), 3-26.
Federal Reserve. (2024). Monetary Policy Report. Washington, DC: Board of Governors of the Federal Reserve System.
Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L., & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. National Bureau of Economic Research Working Paper, No. 16150.
Orphanides, A. (2003). Historical monetary policy analysis and the Taylor rule. Journal of Monetary Economics, 50(5), 983-1022.
Powell, J. H. (2024). Data-dependent monetary policy in practice. Federal Reserve Board Speech. Jackson Hole Economic Symposium, Federal Reserve Bank of Kansas City.
Taylor, J. B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.
Yellen, J. L. (2017). The goals of monetary policy and how we pursue them. Federal Reserve Board Speech. University of California, Berkeley.
---
Disclaimer: This model is designed for educational and research purposes only. Past performance does not guarantee future results. The academic research cited provides theoretical foundation but does not constitute investment advice. Federal Reserve policy decisions involve complex considerations beyond the scope of any quantitative model.
Citation: EdgeTools Research Team. (2025). Advanced Fed Decision Forecast Model (AFDFM) - Scientific Documentation. EdgeTools Quantitative Research Series
UT Bot + Hull MA Confirmed Signal DelayOverview
This indicator is designed to detect high-probability reversal entry signals by combining "UT Bot Alerts" (UT Bot Alerts script adapted from QuantNomad - Originally developed by Yo_adriiiiaan and idea of original code for "UT Bot Alerts" from HPotter ) with confirmation from a Hull Moving Average (HMA) Developed by Alan Hull . It focuses on capturing momentum shifts that often precede trend reversals, helping traders identify potential entry points while filtering out false signals.
🔍 How It Works
This strategy operates in two stages:
1. UT Bot Momentum Trigger
The foundation of this script is the "UT Bot Alerts" , which uses an ATR-based trailing stop to detect momentum changes. Specifically:
The script calculates a dynamic stop level based on the Average True Range (ATR) multiplied by a user-defined sensitivity factor (Key Value).
When price closes above this trailing stop and the short-term EMA crosses above the stop, a potential buy setup is triggered.
Conversely, when price closes below the trailing stop and the short-term EMA crosses below, a potential sell setup is triggered.
These UT Bot alerts are designed to identify the initial shift in market direction, acting as the first filter in the signal process.
2. Hull MA Confirmation
To reduce noise and false triggers from the UT Bot alone, this script delays the entry signal until price confirms the move by crossing the Hull Moving Average (or its variants: HMA, THMA, EHMA) in the same direction as the UT Bot trigger:
A Buy Signal is generated only when:
A UT Bot Buy condition is active, and
The price closes above the Hull MA.
Or, if a UT Bot Buy condition was recently triggered but price hadn’t yet crossed above the Hull MA, a delayed buy is signaled when price finally breaks above it.
A Sell Signal is generated only when:
A UT Bot Sell condition is active, and
The price closes below the Hull MA.
Similarly, a delayed sell signal can occur if price breaks below the Hull MA shortly after a UT Bot Sell trigger.
This dual-confirmation process helps traders avoid premature entries and improves the reliability of reversal signals.
📈 Best Use Cases
Reversal Trading: This strategy is particularly well-suited for catching early trend reversals rather than trend continuations. It excels at identifying momentum pivots that occur after pullbacks or exhaustion moves.
Heikin Ashi Charts Recommended: The script offers a Heikin Ashi mode for smoothing out noise and enhancing visual clarity. Using Heikin Ashi candles can further reduce whipsaws and highlight cleaner shifts in trend direction.
MACD Alignment: For best results, trade in the direction of the MACD trend or use it as a filter to avoid counter-trend trades.
⚠️ Important Notes
Entry Signals Only: This indicator only plots entry points (Buy and Sell signals). It does not define exit strategies, so users should manage trades manually using trailing stops, profit targets, or other exit indicators.
No Signal = No Confirmation: You may see a UT Bot trigger without a corresponding Buy/Sell signal. This means the price did not confirm the move by crossing the Hull MA, and therefore the setup was considered too weak or incomplete.
⚙️ Customization
UT Bot Sensitivity: Adjust the “Key Value” and “ATR Period” to make the UT Bot more or less reactive to price action.
Use Heikin Ashi: Toggle between standard candles or Heikin Ashi in the indicator settings for a smoother trading experience.
The HMA length may also be modified in the indicator settings from its standard 55 length to increase or decrease the sensitivity of signal.
This strategy is best used by traders looking for a structured, logic-based way to enter early into reversals with added confirmation to reduce risk. By combining two independent systems—momentum detection (UT Bot) and trend confirmation (Hull MA)—it aims to provide high-confidence entries without overwhelming complexity.
Let the indicator guide your entries—you manage the exits.
Examples of use:
Futures:
Stock:
Crypto:
As shown in the snapshots this strategy, like most, works the best when price action has a sizeable ATR and works the least when price is choppy. Therefore it is always best to use this system when price is coming off known support or resistance levels and when it is seen to respect short term EMA's like the 9 or 15.
My personal preference to use this system is for day trading on a 3 or 5 minute chart. But it is valid for all timeframes and simply marks a high probability for a new trend to form.
Sources:
Quant Nomad - www.tradingview.com
Yo_adriiiiaan - www.tradingview.com
HPotter - www.tradingview.com
Hull Moving Average - alanhull.com
Enhanced Volume Trend Indicator with BB SqueezeEnhanced Volume Trend Indicator with BB Squeeze: Comprehensive Explanation
The visualization system allows traders to quickly scan multiple securities to identify high-probability setups without detailed analysis of each chart. The progression from squeeze to breakout, supported by volume trend confirmation, offers a systematic approach to identifying trading opportunities.
The script combines multiple technical analysis approaches into a comprehensive dashboard that helps traders make informed decisions by identifying high-probability setups while filtering out noise through its sophisticated confirmation requirements. It combines multiple technical analysis approaches into an integrated visual system that helps traders identify potential trading opportunities while filtering out false signals.
Core Features
1. Volume Analysis Dashboard
The indicator displays various volume-related metrics in customizable tables:
AVOL (After Hours + Pre-Market Volume): Shows extended hours volume as a percentage of the 21-day average volume with color coding for buying/selling pressure. Green indicates buying pressure and red indicates selling pressure.
Volume Metrics: Includes regular volume (VOL), dollar volume ($VOL), relative volume compared to 21-day average (RVOL), and relative volume compared to 90-day average (RVOL90D).
Pre-Market Data: Optional display of pre-market volume (PVOL), pre-market dollar volume (P$VOL), pre-market relative volume (PRVOL), and pre-market price change percentage (PCHG%).
2. Enhanced Volume Trend (VTR) Analysis
The Volume Trend indicator uses adaptive analysis to evaluate buying and selling pressure, combining multiple factors:
MACD (Moving Average Convergence Divergence) components
Volume-to-SMA (Simple Moving Average) ratio
Price direction and market conditions
Volume change rates and momentum
EMA (Exponential Moving Average) alignment and crossovers
Volatility filtering
VTR Visual Indicators
The VTR score ranges from 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions. This is visually represented by colored circles:
"●" (Filled Circle):
Green: Strong bullish trend (VTR ≥ 80)
Red: Strong bearish trend (VTR ≤ 20)
"◯" (Hollow Circle):
Green: Moderate bullish trend (VTR 65-79)
Red: Moderate bearish trend (VTR 21-35)
"·" (Small Dot):
Green: Weak bullish trend (VTR 55-64)
Red: Weak bearish trend (VTR 36-45)
"○" (Medium Hollow Circle): Neutral conditions (VTR 46-54), shown in gray
In "Both" display mode, the VTR shows both the numerical score (0-100) alongside the appropriate circle symbol.
Enhanced VTR Settings
The Enhanced Volume Trend component offers several advanced customization options:
Adaptive Volume Analysis (volTrendAdaptive):
When enabled, dynamically adjusts volume thresholds based on recent market volatility
Higher volatility periods require proportionally higher volume to generate significant signals
Helps prevent false signals during highly volatile markets
Keep enabled for most trading conditions, especially in volatile markets
Speed of Change Weight (volTrendSpeedWeight, range 0-1):
Controls emphasis on volume acceleration/deceleration rather than absolute levels
Higher values (0.7-1.0): More responsive to new volume trends, better for momentum trading
Lower values (0.2-0.5): Less responsive, better for trend following
Helps identify early volume trends before they fully develop
Momentum Period (volTrendMomentumPeriod, range 2-10):
Defines lookback period for volume change rate calculations
Lower values (2-3): More responsive to recent changes, better for short timeframes
Higher values (7-10): Smoother, better for daily/weekly charts
Directly affects how quickly the indicator responds to new volume patterns
Volatility Filter (volTrendVolatilityFilter):
Adjusts significance of volume by factoring in current price volatility
High volume during high volatility receives less weight
High volume during low volatility receives more weight
Helps distinguish between genuine volume-driven moves and volatility-driven moves
EMA Alignment Weight (volTrendEmaWeight, range 0-1):
Controls importance of EMA alignments in final VTR calculation
Analyzes multiple EMA relationships (5, 10, 21 period)
Higher values (0.7-1.0): Greater emphasis on trend structure
Lower values (0.2-0.5): More focus on pure volume patterns
Display Mode (volTrendDisplayMode):
"Value": Shows only numerical score (0-100)
"Strength": Shows only symbolic representation
"Both": Shows numerical score and symbol together
3. Bollinger Band Squeeze Detection (SQZ)
The BB Squeeze indicator identifies periods of low volatility when Bollinger Bands contract inside Keltner Channels, often preceding significant price movements.
SQZ Visual Indicators
"●" (Filled Circle): Strong squeeze - high probability setup for an impending breakout
Green: Strong squeeze with bullish bias (likely upward breakout)
Red: Strong squeeze with bearish bias (likely downward breakout)
Orange: Strong squeeze with unclear direction
"◯" (Hollow Circle): Moderate squeeze - medium probability setup
Green: With bullish EMA alignment
Red: With bearish EMA alignment
Orange: Without clear directional bias
"-" (Dash): Gray dash indicates no squeeze condition (normal volatility)
The script identifies squeeze conditions through multiple methods:
Bollinger Bands contracting inside Keltner Channels
BB width falling to bottom 20% of recent range (BB width percentile)
Very narrow Keltner Channel (less than 5% of basis price)
Tracking squeeze duration in consecutive bars
Different squeeze strengths are detected:
Strong Squeeze: BB inside KC with tight BB width and narrow KC
Moderate Squeeze: BB inside KC with either tight BB width or narrow KC
No Squeeze: Normal market conditions
4. Breakout Detection System
The script includes two breakout indicators working in sequence:
4.1 Pre-Breakout (PBK) Indicator
Detects potential upcoming breakouts by analyzing multiple factors:
Squeeze conditions lasting 2-3 bars or more
Significant price ranges
Strong volume confirmation
EMA/MACD crossovers
Consistent price direction
PBK Visual Indicators
"●" (Filled Circle): Detected pre-breakout condition
Green: Likely upward breakout (bullish)
Red: Likely downward breakout (bearish)
Orange: Direction not yet clear, but breakout likely
"-" (Dash): Gray dash indicates no pre-breakout condition
The PBK uses sophisticated conditions to reduce false signals including minimum squeeze length, significant price movement, and technical confirmations.
4.2 Breakout (BK) Indicator
Confirms actual breakouts in progress by identifying:
End of squeeze or strong expansion of Bollinger Bands
Volume expansion
Price moving outside Bollinger Bands
EMA crossovers with volume confirmation
MACD crossovers with significant price range
BK Visual Indicators
"●" (Filled Circle): Confirmed breakout in progress
Green: Upward breakout (bullish)
Red: Downward breakout (bearish)
Orange: Unusual breakout pattern without clear direction
"◆" (Diamond): Special breakout conditions (meets some but not all criteria)
"-" (Dash): Gray dash indicates no breakout detected
The BK indicator uses advanced filters for confirmation:
Requires consecutive breakout signals to reduce false positives
Strong volume confirmation requirements (40% above average)
Significant price movement thresholds
Consistency checks between price action and indicators
5. Market Metrics and Analysis
Price Change Percentage (CHG%)
Displays the current percentage change relative to the previous day's close, color-coded green for positive changes and red for negative changes.
Average Daily Range (ADR%)
Calculates the average daily percentage range over a specified period (default 20 days), helping traders gauge volatility and set appropriate price targets.
Average True Range (ATR)
Shows the Average True Range value, a volatility indicator developed by J. Welles Wilder that measures market volatility by decomposing the entire range of an asset price for that period.
Relative Strength Index (RSI)
Displays the standard 14-period RSI, a momentum oscillator that measures the speed and change of price movements on a scale from 0 to 100.
6. External Market Indicators
QQQ Change
Shows the percentage change in the Invesco QQQ Trust (tracking the Nasdaq-100 Index), useful for understanding broader tech market trends.
UVIX Change
Displays the percentage change in UVIX, a volatility index, providing insight into market fear and potential hedging activity.
BTC-USD
Shows the current Bitcoin price from Coinbase, useful for traders monitoring crypto correlation with equities.
Market Breadth (BRD)
Calculates the percentage difference between ATHI.US and ATLO.US (high vs. low securities), indicating overall market direction and strength.
7. Session Analysis and Volume Direction
Session Detection
The script accurately identifies different market sessions:
Pre-market: 4:00 AM to 9:30 AM
Regular market: 9:30 AM to 4:00 PM
After-hours: 4:00 PM to 8:00 PM
Closed: Outside trading hours
This detection works on any timeframe through careful calculation of current time in seconds.
Buy/Sell Volume Direction
The script analyzes buying and selling pressure by:
Counting up volume when close > open
Counting down volume when close < open
Tracking accumulated volume within the day
Calculating intraday pressure (up volume minus down volume)
Enhanced AVOL Calculation
The improved AVOL calculation works in all timeframes by:
Estimating typical pre-market and after-hours volume percentages
Combining yesterday's after-hours with today's pre-market volume
Calculating this as a percentage of the 21-day average volume
Determining buying/selling pressure by analyzing after-hours and pre-market price changes
Color-coding results: green for buying pressure, red for selling pressure
This calculation is particularly valuable because it works consistently across any timeframe.
Customization Options
Display Settings
The dashboard has two customizable tables: Volume Table and Metrics Table, with positions selectable as bottom_left or bottom_right.
All metrics can be individually toggled on/off:
Pre-market data (PVOL, P$VOL, PRVOL, PCHG%)
Volume data (AVOL, RVOL Day, RVOL 90D, Volume, SEED_YASHALGO_NSE_BREADTH:VOLUME )
Price metrics (ADR%, ATR, RSI, Price Change%)
Market indicators (QQQ, UVIX, Breadth, BTC-USD)
Analysis indicators (Volume Trend, BB Squeeze, Pre-Breakout, Breakout)
These toggle options allow traders to customize the dashboard to show only the metrics they find most valuable for their trading style.
Table and Text Customization
The dashboard's appearance can be customized:
Table background color via tableBgColor
Text color (White or Black) via textColorOption
The indicator uses smart formatting for volume and price values, automatically adding appropriate suffixes (K, M, B) for readability.
MACD Configuration for VTR
The Volume Trend calculation incorporates MACD with customizable parameters:
Fast Length: Controls the period for the fast EMA (default 3)
Slow Length: Controls the period for the slow EMA (default 9)
Signal Length: Controls the period for the signal line EMA (default 5)
MACD Weight: Controls how much influence MACD has on the volume trend score (default 0.3)
These settings allow traders to fine-tune how momentum is factored into the volume trend analysis.
Bollinger Bands and Keltner Channel Settings
The Bollinger Bands and Keltner Channels used for squeeze detection have preset (hidden) parameters:
BB Length: 20 periods
BB Multiplier: 2.0 standard deviations
Keltner Length: 20 periods
Keltner Multiplier: 1.5 ATR
These settings follow standard practice for squeeze detection while maintaining simplicity in the user interface.
Practical Trading Applications
Complete Trading Strategies
1. Squeeze Breakout Strategy
This strategy combines multiple components of the indicator:
Wait for a strong squeeze (SQZ showing ●)
Look for pre-breakout confirmation (PBK showing ● in green or red)
Enter when breakout is confirmed (BK showing ● in same direction)
Use VTR to confirm volume supports the move (VTR ≥ 65 for bullish or ≤ 35 for bearish)
Set profit targets based on ADR (Average Daily Range)
Exit when VTR begins to weaken or changes direction
2. Volume Divergence Strategy
This strategy focuses on the volume trend relative to price:
Identify when price makes a new high but VTR fails to confirm (divergence)
Look for VTR to show weakening trend (● changing to ◯ or ·)
Prepare for potential reversal when SQZ begins to form
Enter counter-trend position when PBK confirms reversal direction
Use external indicators (QQQ, BTC, Breadth) to confirm broader market support
3. Pre-Market Edge Strategy
This strategy leverages pre-market data:
Monitor AVOL for unusual pre-market activity (significantly above 100%)
Check pre-market price change direction (PCHG%)
Enter position at market open if VTR confirms direction
Use SQZ to determine if volatility is likely to expand
Exit based on RVOL declining or price reaching +/- ADR for the day
Market Context Integration
The indicator provides valuable context for trading decisions:
QQQ change shows tech market direction
BTC price shows crypto market correlation
UVIX change indicates volatility expectations
Breadth measurement shows market internals
This context helps traders avoid fighting the broader market and align trades with overall market direction.
Timeframe Optimization
The indicator is designed to work across different timeframes:
For day trading: Focus on AVOL, VTR, PBK/BK, and use shorter momentum periods
For swing trading: Focus on SQZ duration, VTR strength, and broader market indicators
For position trading: Focus on larger VTR trends and use EMA alignment weight
Advanced Analytical Components
Enhanced Volume Trend Score Calculation
The VTR score calculation is sophisticated, with the base score starting at 50 and adjusting for:
Price direction (up/down)
Volume relative to average (high/normal/low)
Volume acceleration/deceleration
Market conditions (bull/bear)
Additional factors are then applied, including:
MACD influence weighted by strength and direction
Volume change rate influence (speed)
Price/volume divergence effects
EMA alignment scores
Volatility adjustments
Breakout strength factors
Price action confirmations
The final score is clamped between 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions.
Anti-False Signal Filters
The indicator employs multiple techniques to reduce false signals:
Requiring significant price range (minimum percentage movement)
Demanding strong volume confirmation (significantly above average)
Checking for consistent direction across multiple indicators
Requiring prior bar consistency (consecutive bars moving in same direction)
Counting consecutive signals to filter out noise
These filters help eliminate noise and focus on high-probability setups.
MACD Enhancement and Integration
The indicator enhances standard MACD analysis:
Calculating MACD relative strength compared to recent history
Normalizing MACD slope relative to volatility
Detecting MACD acceleration for stronger signals
Integrating MACD crossovers with other confirmation factors
EMA Analysis System
The indicator uses a comprehensive EMA analysis system:
Calculating multiple EMAs (5, 10, 21 periods)
Detecting golden cross (10 EMA crosses above 21 EMA)
Detecting death cross (10 EMA crosses below 21 EMA)
Assessing price position relative to EMAs
Measuring EMA separation percentage
Recent Enhancements and Evolution
Version 5.2 includes several improvements:
Enhanced AVOL to show buying/selling direction through color coding
Improved VTR with adaptive analysis based on market conditions
AVOL display now works in all timeframes through sophisticated estimation
Removed animal symbols and streamlined code with bright colors for better visibility
Improved anti-false signal filters throughout the system
Optimizing Indicator Settings
For Different Market Types
Range-Bound Markets:
Lower EMA Alignment Weight (0.2-0.4)
Higher Speed of Change Weight (0.8-1.0)
Focus on SQZ and PBK signals for breakout potential
Trending Markets:
Higher EMA Alignment Weight (0.7-1.0)
Moderate Speed of Change Weight (0.4-0.6)
Focus on VTR strength and BK confirmations
Volatile Markets:
Enable Volatility Filter
Enable Adaptive Volume Analysis
Lower Momentum Period (2-3)
Focus on strong volume confirmation (VTR ≥ 80 or ≤ 20)
For Different Asset Classes
Equities:
Standard settings work well
Pay attention to AVOL for gap potential
Monitor QQQ correlation
Futures:
Consider higher Volume/RVOL weight
Reduce MACD weight slightly
Pay close attention to SQZ duration
Crypto:
Higher volatility thresholds may be needed
Monitor BTC price for correlation
Focus on stronger confirmation signals
Integrated Visual System for Trading Decisions
The colored circle indicators create an intuitive visual system for quick market assessment:
Progression Sequence: SQZ (Squeeze) → PBK (Pre-Breakout) → BK (Breakout)
This sequence often occurs in order, with the squeeze leading to pre-breakout conditions, followed by an actual breakout.
VTR (Volume Trend): Provides context about the volume supporting these movements.
Color Coding: Green for bullish conditions, red for bearish conditions, and orange/gray for neutral or undefined conditions.
Change % Inteligente - NQ / ES / YMTopstep Compliance: Daily Price Change % Alert (NQ / ES / YM)
Script Purpose
This script helps funded traders (especially those using Topstep or similar programs) monitor the real-time percentage change of major equity index futures: Nasdaq (NQ), S&P 500 (ES), and Dow Jones (YM).
⚠️ Why it matters
Topstep prohibits trading within 2% of the daily price limits set by the CME. If a trader holds a position too close to those limits, they risk account disqualification.
📊 How it works
• Detects the instrument: NQ1!, ES1!, YM1!, or M2025 contracts
• Calculates the real-time % change from today’s market open
• Simulates daily CME price limits (+7% / -7%)
• Highlights when price enters the last 2% of the limit range (prohibited zone)
• Displays a clean, floating panel with the current % change and a warning if necessary
• Sends a visual and optional audio alert when in the prohibited zone
🧠 What makes this script unique?
This tool is **not for technical analysis**. It focuses exclusively on **funding program compliance** and **account protection**, which is not covered by other public scripts. It’s lightweight, intuitive, and designed for traders who manage risk like professionals.
✅ Open-source and ready for review.
✅ CHART SETUP FOR PUBLICATION
✔️ Use a clean chart
✔️ Only apply this script
✔️ Make sure the panel is visible (top-right or top-center recommended)
❌ No extra indicators or drawings
✔️ Use NQM2025, ESM2025 or YMM2025 on a volatile day (to show -1% to -3% range)
INSTRUCTIONS
1. Add the script to your chart.
2. Use it with NQ1!, ES1!, or YM1! (or M2025 contracts).
3. The panel will show today’s price change %.
4. If the market is within the last 2% of the CME price limit, a warning will appear.
5. Use this to avoid violating Topstep’s trading rules during volatile days.
Maguila Strategy by Rodrigo CohenREAD BEFORE USE!!!
!!!ALERT!!!! THIS CODE ONLY WORKS WITH WDO AND WIN , BOTH WITH TIMEFRAMES 1 MINUTE AND 5 MINUTE.
This is a test to the Maguila strategy created by Rodrigo Cohen.
This code MUST be validaded by Rodrigo Cohen, use ONLY for tests.
Some results are different from Cohen's videos, so the McGuinley indicator needs some ajustments.
FUTURES: WIN , WDO
TIME FRAME: 1 Minute (also works in 5 minutes)
INDICATORS: McGinley Dynamic accompanied by the Exponential Moving Average coloring rule of 21 and 42 periods
MARKET TYPE: In trend (up or down)
INPUT:
1. When buying (long) = Market in an upward trend, the average of 21 crosses that of 42 upwards. When the price returns to the average of 21, wait for a positive candle in the Maguila's color and buy a break from the maximum of this signal candle.
2. On sale (short) = Downtrend market, the average of 21 crosses that of 42 downwards. When the price returns to the average of 21, wait for a negative candle in the Maguila's color and sell when the minimum of this signal candle breaks.
GAIN and LOSS are technical.
DEFAULT VALUES:
Averages:
- 1 minute - EMA 21 and EMA 42
- 5 minute - EMA 17 and EMA 34
Gains and Loss:
- WDO - 10 points
- WIN - 200 points
(ES, NQ) Trend Checker SB1(ES, NQ) Trend Checker SB1
Stay ahead of the market by tracking whether the E-mini S&P 500 (ES) and the Nasdaq 100 (NQ) are moving in sync.
📊 How it works:
The script checks whether each index is bullish (close > open) or bearish (close < open).
If both are aligned (all bullish or all bearish), conditions are stable.
If they diverge, the indicator instantly flags a mismatch in trend.
🎯 Features:
Background shading to highlight mismatched conditions.
Real-time alerts when ES and NQ fall out of sync.
Works on any timeframe.
🔥 Why it matters:
When ES and NQ move together, market momentum is usually stronger and cleaner.
But when they disagree, expect choppiness, fakeouts, or caution zones — the perfect heads-up before entering trades.
Resistance of VolumeIt is used to detect volume resistors in a personalized way, since it allows the user to enter the volume in which he wishes the resistance to jump automatically.
It does not mark the black line and the graphic that's just to help understand how it works
in the above image can see the indicator works on 30 minutes chart
in the above image can see the indicator works on 5 minutes chart
therefore, it can be configured to go through several temporalities.
CVD-MACD### CVD-MACD (Research)
The CVD-MACD is a research-oriented indicator that combines Cumulative Volume Delta (CVD) with the classic MACD framework to provide insights into market momentum and potential reversals. Unlike a standard MACD based on price, this version uses CVD (the running total of buy vs. sell volume delta) as its input source, offering a volume-driven perspective on trend strength and divergences.
Key Features:
- **CVD-Based MACD Calculation**: Computes MACD using CVD instead of price, highlighting volume imbalances that may precede price moves.
- **Dual Divergence Detection**: Identifies bullish/bearish divergences on both the MACD line and histogram, with configurable pivot lookbacks and filters (e.g., momentum decay and zero-side consistency).
- **Visual Flexibility**: Toggle divergences in the indicator pane or overlaid on the main chart, with optional raw CVD line for reference.
- **Alerts**: Built-in conditions for bullish and bearish divergences to notify users of potential setups.
###This indicator is designed for research and experimentation—it's not financial advice. It performs best on liquid assets with reliable volume data (e.g., stocks, futures). I've shared this to gather community feedback: please test it thoroughly and point out any bugs, inefficiencies, or improvements! For example, if you spot issues with divergence detection on certain timeframes or symbols, let me know in the comments. Your input will help refine it.
Inspired by volume analysis techniques; open to collaborations or forks.
## User Manual for CVD-MACD (Research)
### Overview
The CVD-MACD indicator transforms traditional MACD by using Cumulative Volume Delta (CVD) as the base input. CVD accumulates the net delta between estimated buy and sell volume per bar, providing a volume-centric view of momentum. The indicator plots a MACD line, signal line, and histogram, while also detecting divergences on both the MACD line and histogram for potential reversal signals.
This manual covers setup, interpretation, and troubleshooting.
Note: This is a research tool—backtest and validate on your own data before using in live trading.
### Installation and Setup
1. **Add to Chart**: Search for "CVD-MACD (Research)" in TradingView's indicator library or paste the script into the Pine Editor and add it to your chart.
2. **Compatibility**: Works on any timeframe and symbol with volume data. Best on daily/intraday charts for stocks, forex, or futures. Avoid illiquid symbols where volume may be unreliable.
3. **Customization**: All inputs are configurable via the indicator's settings panel. Defaults are optimized for general use but can be tuned based on asset volatility.
### Input Parameters
The inputs are grouped for ease of use:
#### MACD Settings
- **Fast EMA (CVD)** (default: 12): Length of the fast EMA applied to CVD. Shorter values make it more responsive to recent volume changes.
- **Slow EMA (CVD)** (default: 26): Length of the slow EMA on CVD. Longer values smooth out noise for trend identification.
- **Signal EMA** (default: 9): Smoothing period for the signal line (EMA of the MACD line).
#### Divergence Logic (MACD Line)
- **Pivot Lookback (MACD Line)** (default: 5): Bars to look left/right for detecting pivots on the MACD line. Higher values detect larger swings but may miss smaller divergences.
- **Max Lookback Range (MACD Line)** (default: 50): Maximum bars between two pivots to consider a divergence valid. Prevents detecting outdated signals.
- **Enable Momentum Decay Filter (Histogram)** (default: false): When enabled, requires the histogram to show decaying momentum (absolute value decreasing) for MACD-line divergences to trigger.
#### Histogram Divergence
- **Pivot Lookback (Histogram)** (default: 5): Similar to above, but for histogram pivots.
- **Max Lookback Range (Histogram)** (default: 50): Max bars for histogram divergence detection.
- **Show Histogram Divergences in Indicator Pane** (default: true): Displays dashed lines and "H" labels for histogram divergences in the sub-window.
- **Show Histogram Divergences on Main Chart** (default: true): Overlays histogram divergences on the price chart with semi-transparent lines and labels.
- **Require Histogram to Stay on Same Side of Zero** (default: true): Filters divergences to only those where the histogram doesn't cross zero between pivots, ensuring consistent momentum direction.
#### Visuals (Dual View)
- **Show MACD-Line Divergences (Indicator Pane)** (default: true): Draws solid lines and "L" labels for MACD-line divergences in the sub-window.
- **Show MACD-Line Divergences (Main Chart)** (default: true): Overlays MACD-line divergences on the price chart.
- **Show Raw CVD Line** (default: false): Plots the underlying CVD as a faint gray line for reference.
### How to Interpret the Indicator
1. **Core Plots**:
- **MACD Line** (blue): Difference between fast and slow CVD EMAs. Above zero indicates building buy volume momentum; below zero shows sell dominance.
- **Signal Line** (orange): EMA of the MACD line. Crossovers can signal potential entries/exits (e.g., MACD above signal = bullish).
- **Histogram** (columns): MACD minus signal. Green shades for positive/expanding bars (bullish momentum); red for negative/contracting (bearish). Fading colors indicate weakening momentum.
- **Zero Line** (gray horizontal): Reference for bullish (above) vs. bearish (below) territory.
- **Raw CVD** (optional gray line): The cumulative buy-sell delta. Rising = net buying; falling = net selling.
2. **Divergences**:
- **Bullish (Green Lines/Labels)**: Occur when price makes lower lows, but MACD line or histogram makes higher lows. Suggests weakening downside momentum and potential reversal up. Look for "L" (MACD line) or "H" (histogram) labels.
- **Bearish (Red Lines/Labels)**: Price higher highs vs. MACD/histogram lower highs. Indicates fading upside and possible downturn.
- **Dual View**: Divergences appear in the indicator pane (sub-window) for clean analysis and overlaid on the main chart for price context. Histogram divergences use dashed lines to distinguish from MACD-line (solid).
- **Filters**: Momentum decay ensures only "hidden" or weakening divergences trigger. Zero-side filter prevents false signals from oscillating histograms.
3. **Alerts**:
- **Bullish Divergence (L or H)**: Triggers on either MACD-line or histogram bullish divergence. Message: "CVD-MACD Bullish Divergence detected on {{ticker}}".
- **Bearish Divergence (L or H)**: Similar for bearish. Use TradingView's alert setup to notify via email/SMS/webhook.
- Tip: Combine with price action (e.g., support/resistance) for confirmation.
### Usage Tips and Strategies
- **Trend Confirmation**: Use in uptrends for bullish divergences (pullback buys) or downtrends for bearish (short entries).
- **Timeframe Selection**: Higher timeframes (e.g., daily) for swing trading; lower (e.g., 15-min) for intraday. Adjust pivot lookbacks accordingly (shorter for faster charts).
- **Combination Ideas**: Pair with RSI for overbought/oversold confirmation or VWAP for intraday volume context.
- **Risk Management**: Divergences are probabilistic—not guarantees. Always use stop-losses based on recent swings.
- **Performance Notes**: Backtest on historical data via TradingView's Strategy Tester. CVD relies on accurate volume; test on exchanges like NYSE/NASDAQ.
### Known Limitations and Troubleshooting
- **Volume Dependency**: CVD estimation assumes linear buy/sell distribution based on bar position—may be less accurate on thin markets or during gaps.
- **Repainting**: Pivots and divergences can repaint as new data arrives (common in pivot-based indicators). Use on closed bars for reliability.
- **Resource Usage**: High max_bars_back (5000) ensures deep history; reduce if chart loads slowly.
- **No Signals on Low-Volume Bars**: If CVD flatlines, check symbol volume—some crypto/forex pairs have inconsistent data.
- **Community Feedback**: If you encounter bugs (e.g., false divergences on specific symbols/timeframes), missing alerts, or calculation errors, please comment below with details like symbol, timeframe, and screenshots. Suggestions for enhancements (e.g., more filters or visuals) are welcome!
If you have questions or find issues, drop a comment—let's improve this together!
