Statistcal Daily Profile & Ranges# Statistical Daily Profile & Ranges - TradingView Publication Guide
## Overview
The **Statistical Daily Profile & Ranges** indicator is a comprehensive tool designed to analyze intraday session behavior and daily range characteristics. It combines Average Daily Range (ADR) projection levels with detailed session-by-session statistics and probability-based trading insights derived from historical price action patterns.
## What This Indicator Does
This indicator provides traders with three core analytical components:
1. **ADR Projection Levels** - Dynamic support/resistance levels based on historical daily ranges
2. **Session Range Analysis** - Visual boxes and statistical breakdowns for four key trading sessions
3. **Dynamic Probability Display** - Real-time probability statistics based on overnight session relationships
## How It Works
### Average Daily Range (ADR) Calculation
The indicator calculates the average daily range over a user-defined lookback period (default: 10 days) and projects this range from each day's opening price. This creates two key levels:
- **ADR High**: Opening price + average daily range
- **ADR Low**: Opening price - average daily range
- **ADR Median**: The opening price (middle of the projected range)
These levels are recalculated at the start of each trading day and extend forward, providing dynamic support and resistance zones based on recent volatility characteristics.
### Session Tracking & Statistics
The indicator monitors four distinct trading sessions (times in Eastern Time):
1. **Asia Session** (8:00 PM - 2:00 AM)
2. **London Session** (2:00 AM - 8:00 AM)
3. **NY Open** (8:00 AM - 9:00 AM)
4. **NY Initial Balance** (9:30 AM - 10:30 AM)
For each session, the indicator:
- Draws a colored box showing the session's high-to-low range
- Tracks the opening price, high, and low
- Stores historical data for statistical analysis
- Calculates average ranges by day of week (Monday through Friday)
The session statistics are displayed in a customizable table showing average point ranges for each session across different weekdays, helping traders identify which sessions and days typically produce the most movement.
### Dynamic Probability System
The indicator analyzes the relationship between the Asia and London sessions to determine the current market setup. After the London session closes, it automatically detects one of four possible conditions:
**1. London Engulfs Asia**
- London session breaks both above Asia's high AND below Asia's low
- This indicates strong momentum during the European session
- Most common occurrence pattern
**2. Asia Engulfs London**
- Asia session range completely contains the London session range
- Indicates consolidation during London hours
- Relatively rare pattern (occurs approximately 5.36% of the time)
**3. London Partially Engulfs Upwards**
- London breaks above Asia's high but stays above Asia's low
- Suggests bullish momentum continuation from Asia into London
**4. London Partially Engulfs Downwards**
- London breaks below Asia's low but stays below Asia's high
- Suggests bearish momentum continuation from Asia into London
Once a condition is detected, the indicator displays a probability table showing historically observed outcomes for that specific setup, including:
- Probability of NY session taking out key levels (Asia high/low, London high/low)
- Probability of NY session engulfing the entire overnight range
- Directional bias for NY Cash session (9:30 AM - 4:00 PM)
## How to Use This Indicator
### Initial Setup
1. Add the indicator to your chart (works on any intraday timeframe below Daily)
2. Adjust the **ADR Days** setting (default: 10) to control the lookback period for range calculation
3. Adjust the **Session Lookback Days** setting (default: 50) to determine how much historical data feeds the statistics tables
### Reading the ADR Levels
- Use the **ADR High** and **ADR Low** lines as potential profit targets or areas where price may encounter resistance
- The **ADR Median** line represents the opening price and can act as a pivot point for intraday directional bias
- If price reaches the ADR High early in the session, it suggests strong bullish momentum; conversely for ADR Low
- These levels adapt daily based on recent volatility, making them more responsive than static levels
### Interpreting Session Boxes
- **Session boxes** visually highlight when each trading session is active and its price range
- Larger boxes indicate higher volatility during that session
- Compare current session ranges to the statistical averages shown in the table
- Sessions that are unusually quiet or active relative to historical averages may signal compression or expansion
### Using the Session Statistics Table
- The table shows average point ranges for each session broken down by weekday
- Identify which sessions typically produce the most movement on specific days
- For example, if London on Thursdays averages 40 points while Mondays average 25 points, you can adjust position sizing or expectations accordingly
- The **Total** column shows the overall average across all days
- Sample sizes (shown in brackets if enabled) indicate data reliability
### Trading with the Probability Table
The probability table updates dynamically after the London session closes and shows statistically probable outcomes based on 12 years of NQ futures data.
**Important Limitations:**
- **These probabilities are derived from NQ (Nasdaq E-mini futures) data only**
- **Do NOT apply these probability statistics to other instruments** (ES, stocks, forex, etc.)
- The probabilities represent historical frequencies, not guarantees
- Always combine with your own analysis, risk management, and market context
**How to Apply the Probabilities:**
When **London Engulfs Asia**:
- Watch for NY session to take out London's extremes (72.33% probability for high, 71.12% for low)
- Slight bullish bias in NY Cash session (54.80% vs 45.20%)
- Lower probability of complete overnight engulfment (44.13%)
When **Asia Engulfs London** (rare - 5.36% occurrence):
- Higher probability NY takes Asia's high (75.86%)
- Moderately high probability NY takes Asia's low (65.52%)
- Slight increase in bullish bias (58.42% vs 41.58%)
- Recognize this as an unusual setup
When **London Partially Engulfs Upwards**:
- Very high probability NY takes London high (81.51%)
- Strong probability NY takes London low (64.45%)
- Moderate probability NY takes Asian low (53.16%)
- Slight bullish bias (55.52%)
When **London Partially Engulfs Downwards**:
- Very high probability NY takes London low (75.29%)
- Strong probability NY takes London high (68.80%)
- Moderate probability NY takes Asian high (56.44%)
- Slight bullish bias maintained (52.99%)
### Practical Trading Applications
**Scenario 1: Range Projection**
If the ADR is 500 points and the market opens at 25,000:
- ADR High: 25,500 (potential resistance/target)
- ADR Low: 24,500 (potential support/target)
- Monitor how price interacts with these levels throughout the day
**Scenario 2: Session-Based Trading**
Using the statistics table, you notice London on Wednesdays averages 35 points. During a Wednesday London session:
- If London has already moved 30 points, the session may be exhausting its typical range
- If London has only moved 15 points with an hour remaining, there may be expansion potential
- Adjust stop losses and targets based on typical session behavior
**Scenario 3: Probability-Based Setup**
It's 8:05 AM ET and the indicator shows "London Partially Engulfs Upwards":
- You now know there's an 81.51% historical probability NY will take out London's high
- There's a 53.16% probability NY will reach down to Asia's low
- The NY Cash session has a slight bullish bias (55.52%)
- Consider this alongside your technical analysis for directional bias and level targeting
## Customization Options
### Visual Settings
- **Line Width**: Adjust thickness of ADR levels
- **ADR Color/Style**: Customize appearance of ADR projection lines (solid, dashed, dotted)
- **Median Line**: Toggle visibility and customize appearance separately
- **Session Box Colors**: Customize each session's box color independently
- **Show Session Boxes**: Toggle session box visibility on/off
### Label Settings
- **ADR Labels**: Show/hide labels for ADR High and ADR Low, adjust size
- **Median Label**: Separate control for median line label
- **Session Labels**: Show/hide session name labels, adjust size
- **Label Colors**: Customize text colors for all labels
### Table Settings
- **Session Stats Table**: Position (9 locations available), size (Tiny to Huge), toggle on/off
- **Sample Sizes**: Show/hide the number of historical samples used for each calculation
- **Probabilities Table**: Separate position and size controls, toggle on/off
### Session Times
- Each session's time range can be customized to fit different markets or preferences
- All times are in Eastern Time (America/New_York timezone)
## Technical Notes
### Data Requirements
- The indicator requires sufficient historical data based on your lookback settings
- Minimum recommended: 50+ days of intraday data for reliable statistics
- Works on any timeframe below Daily (1-minute, 5-minute, 15-minute, etc.)
### Calculation Methodology
- **ADR Calculation**: Simple average of absolute daily high-low ranges
- **Session Statistics**: Mean average of ranges for each session filtered by day of week
- **Condition Detection**: Boolean logic comparing session high/low relationships
- All calculations update in real-time as new bars form
### Probability Data Source
The probability statistics displayed in the dynamic table are derived from:
- **Dataset**: 12 years of NQ (Nasdaq E-mini futures) historical data
- **Methodology**: Frequency analysis of outcomes following specific setup conditions
- **Time Period**: Multiple market cycles including various volatility regimes
**Critical Warning**: These probabilities are specific to NQ and reflect that instrument's behavior patterns. Market microstructure, participant behavior, and volatility characteristics differ significantly across instruments. Do not apply these NQ-derived probabilities to other markets (ES, RTY, YM, individual stocks, forex, commodities, etc.).
## Best Practices
1. **Combine with Other Analysis**: Use this indicator as one component of a complete trading methodology, not a standalone system
2. **Respect Risk Management**: Probabilities are not certainties; always use proper position sizing and stop losses
3. **Context Matters**: High-impact news events, holiday trading, and extreme volatility can invalidate typical patterns
4. **Verify Statistics**: Monitor your own results and compare to the displayed probabilities
5. **Adapt Session Times**: If trading instruments with different active hours, adjust session times accordingly
6. **Regular Calibration**: Periodically review if the session averages and probabilities remain relevant to current market conditions
## Understanding Originality
This indicator is original in its approach to combining three analytical frameworks into a single tool:
1. **Dynamic ADR Projection**: Unlike static pivot points, these levels adapt daily based on recent volatility
2. **Session-Specific Statistics**: Goes beyond simple volume profiles by quantifying average ranges for specific time windows across weekdays
3. **Conditional Probability Display**: Automatically detects overnight session relationships and displays relevant probability data rather than showing all scenarios simultaneously
The conditional logic system that determines which probability set to display is a key differentiator—traders only see the statistics relevant to the current market setup, reducing information overload and improving decision-making clarity.
## Summary
The **Statistical Daily Profile & Ranges** indicator provides traders with a comprehensive framework for understanding daily range potential, session-specific behavior patterns, and probability-based setup analysis. By combining ADR projection levels with detailed session statistics and dynamic probability displays, traders gain multiple perspectives on potential price movement within the trading day.
The indicator is most effective when used to:
- Set realistic profit targets based on average daily range
- Identify which sessions typically produce movement on specific weekdays
- Understand probability-weighted outcomes for different overnight setup conditions (NQ only)
- Visualize session ranges and compare them to historical averages
Remember that all statistical analysis reflects historical patterns, and market behavior can change. Always combine indicator signals with sound risk management, proper position sizing, and your own market analysis.
Statistics
Open Interest Bubbles [BackQuant]Open Interest Bubbles
A visual OI positioning overlay that aggregates futures open interest across major venues, normalizes it into a consistent “signal strength” scale, then plots extreme events as bubbles, labels, and optional horizontal levels directly on price.
What this is for
Open interest is one of the cleanest ways to track when positioning is building, unwinding, or aggressively shifting. The problem is raw OI is noisy, exchange-specific, and hard to compare across time. This script solves that by:
- Aggregating OI across multiple exchanges.
- Letting you choose what “OI signal” you care about (raw, delta, percent versions).
- Normalizing the signal so “big events” are easy to spot.
- Plotting those events as bubbles and levels at the exact price they occurred.
You end up with a clean, fast visual map of where large positioning changes occurred, and where those events may later matter as reaction points.
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Plotting types (what you can display)
Bubbles
This mode plots OI events as size-bucketed circles on the chart. Bigger bubbles represent stronger normalized events. You can tune:
- Bubble sizing by bucket (Tiny → Huge).
- Heatmap vs solid color styling.
- Signed vs unsigned coloring (positive/negative separation or magnitude-only).
Best use:
- Spotting “where something changed” at a glance.
- Identifying clusters of positioning events around key price zones.
- Seeing whether the market is repeatedly building/closing positions at similar levels.
Levels
Levels mode draws a horizontal line at the anchor price when an extreme OI event triggers. These act like “positioning memory” levels:
- They do not claim to be support/resistance by themselves.
- They highlight prices where the derivatives market clearly did something meaningful.
Best use:
- Marking potential reaction zones.
- Combining with your price action tools (structure, OBs, FVGs) to confirm whether an OI level aligns with a technical level.
- Building a “map” of where leverage likely entered or exited.
Modes available in the script:
- Off
- Bubbles
- Bubbles + Labels
- Labels Only
- Levels + Labels
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Aggregated Open Interest source (multi-exchange)
This indicator builds a single aggregated OI series by requesting OI data from multiple exchanges and summing it. You can toggle exchanges on/off:
- Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit
You can also choose OI units:
- COIN , OI in base units (native sizing)
- USD , converted for a dollar-value representation
Important note:
Not every symbol has OI data on every venue. If the script cannot build an aggregated series for the symbol, it will throw an error rather than quietly plotting garbage.
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OI Source, what the bubbles are measuring
You control what “signal” is normalized and plotted:
- Delta , change in aggregated OI from the prior bar.
Use when you want to highlight bursts of new positioning or sudden unwind events.
- Raw OI , the aggregated open interest level itself.
Use when you want to highlight absolute positioning build-up periods.
- Delta % , percent change in OI.
Use when you want moves normalized to the current OI regime, useful across different market eras.
- Raw OI % , percent change form of the raw series.
Use when you want relative changes rather than absolute size.
Practical guidance:
- Delta modes are best for “event detection”.
- Raw modes are better for “regime context” and whether positioning is structurally rising or fading.
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Normalization (the key to making it readable)
Because OI varies massively across assets and time, the script includes multiple normalization modes to convert your chosen OI source into a comparable “strength” value.
Options:
- ZScore , deviation from a rolling mean in standard deviation units.
- StdNorm , scaled by rolling standard deviation.
- AbsZScore , absolute value version for magnitude-only mapping.
- AbsStdNorm , absolute value version for magnitude-only mapping.
- None , plots raw values (advanced users only, often too noisy visually).
Why this matters:
Normalization makes a “1.5” or “3.0” threshold mean something across different assets and timeframes, instead of being stuck to raw OI units.
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Threshold system (when bubbles/levels trigger)
The plot is driven by two user thresholds:
- Base Threshold
Controls where “meaningful” events start. Raising this reduces noise and focuses on larger deviations.
- Extreme Threshold
Controls what qualifies as a top-tier event. Extreme events are what you typically want to convert into labels and levels.
You also control side filtering:
- Both , show positive and negative events.
- Positive Only , show only increases (or positive signal side depending on source).
- Negative Only , show only decreases (or negative signal side).
In practice:
- Use Base Threshold to tune chart cleanliness.
- Use Extreme Threshold to mark only the “big stuff” that tends to matter later.
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Anchor Source (where the bubble/level is placed)
The indicator places bubbles, labels, and levels at a price anchor you choose:
- HL2, Close, Open, High, Low, VWAP
This is important because “where you pin the event” changes how it reads:
- Close is clean and consistent for backtesting and candle-close logic.
- High/Low can better represent where the fight occurred intrabar.
- VWAP can be useful for “fair price” anchoring in active markets.
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Style system (theme, palette, signed logic)
This script is built to look good and stay readable on busy charts.
Themes
- BackQuant, Classic, Ice, Fire, Mono, Custom
Palette Mode
- Solid , one consistent color
- Heatmap , intensity increases with magnitude
- Single Color Adaptive , adapts to chart background for clarity
Side Coloring
- Signed , positive and negative events can use different ramps
- Unsigned , magnitude-only coloring
Negative theme handling:
- Auto (mirrors your chosen theme),
- Invert (flips the ramp),
- Custom (fully user-defined negative palette).
What this gives you:
- You can run a clean “mono” look for professional charts.
- Or a high-contrast heatmap for fast scanning.
- Or fully custom branding colors for BackQuant-style presentation.
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Labels (what’s inside the label)
When labels are enabled, the script can display:
- OI , the aggregated OI value
- OI + Norm , OI plus normalized strength
- Norm Only , just the normalized strength
- Src + Norm , the selected source value (Delta, Raw, %) plus normalized strength
You can also control:
- Left/Center/Right label alignment
- Number formatting style (Raw, Compact, Volume format)
Best practice:
- Use “Src + Norm” when you want both the raw event size and its rarity.
- Use “Norm Only” when you want a clean, minimal chart.
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Levels and object limits (performance and cleanliness)
Because this script draws objects, it includes a hard cleanup system:
- You set Max Levels / Labels to control chart clutter.
- The script deletes older lines/labels when the limit is exceeded.
This is critical if you trade lower timeframes, where OI events can trigger frequently.
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How to interpret the signals
What a large bubble usually means:
- A statistically large positioning change relative to recent history.
- This can represent fresh leverage entering, forced liquidations, or aggressive de-risking, depending on direction and context.
How to use levels:
- Treat them as “attention levels”, not automatic entries.
- Combine them with structure and liquidity tools:
- If price revisits an OI level and shows rejection, it often confirms that level mattered.
- If price slices through with no reaction, it often indicates the OI event was transitional, not defended.
Common setups:
- Clustered extreme bubbles near a breakout zone, then retest later.
- Extreme negative event at capitulation low, followed by structure flip.
- Extreme positive build into resistance, then unwind and mean reversion.
Also, please check out @NoveltyTrade for the OI Aggregation logic & pulling the data source!
Here is the original script:
Markov: Transition Matrix [Daily Timeframe]Description
This indicator computes a 3-state Markov chain from price action and visualizes the transition probabilities between daily states:
• Up: daily % change > threshold
• Down: daily % change < -threshold
• Sideways: |daily % change| ≤ threshold
From those states, it builds transition matrices:
• Today → Tomorrow (1 day ahead)
• Today → In 2 days
• Today → In 3 days
Each matrix cell shows:
P(next state | current state)
Rows are the current state (today), columns are the future state (tomorrow / +2 / +3).
Each row sums to 100% (when there is sufficient sample size).
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How to read it (trader workflow)
1. Identify the current regime (the most recent confirmed daily state).
2. Look at the row matching that regime:
• The ★ marks the highest probability outcome for that row (most likely next state).
• Heatmap intensity increases as probability increases.
• Each row shows its own sample size (n=...) so you can judge statistical support.
3. Use Quick-read:
• “Now” = current regime
• “Best” = top conditional outcome + probability
• “2nd” = second-best outcome + probability
4. Use Universe (N):
• Shows the marginal distribution: how often days are Up/Down/Sideways across the whole dataset.
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Settings
Core logic
• Sideways threshold: controls how strict “Sideways” is.
Example: 0.001 = ±0.10% daily move is considered Sideways.
Display
• Toggle 1D / 2D / 3D matrices.
• Highlight best probability per row (★).
• Show n per row (row transition count).
• Focus: current state row only to reduce noise and speed decision-making.
• Quick-read row for the current regime.
Theme (fully customizable)
All colors can be customized:
• Up / Down / Sideways base colors
• Header background + header text
• Values text
• Quick-read neutral background
This makes it suitable for both light and dark chart themes.
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Notes / Limitations
• The indicator is designed for daily sessions. It uses daily close-to-close returns to classify states and update the Markov chain once per day.
• On very volatile assets, a very small threshold can make Sideways rare. If you want a more frequent Sideways regime, increase the threshold.
• This is a statistical visualization tool, not a trading system.
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Disclaimer (TradingView-friendly)
This script is provided for educational and informational purposes only and does not constitute financial advice. Trading involves risk. Past probabilities do not guarantee future results. Use at your own discretion and always apply proper risk management.
Seasonality Table: % Move by Day x Month (Open vs Prev Close)Short description
A compact seasonality heatmap that shows the average daily open vs previous session close move for each calendar day (1–31) across months (Jan–Dec).
What it does
This indicator builds a Day × Month table where each cell displays the historical average of:
(Open/Close-1) -1 x 100
In other words: how the market typically “opened” relative to the prior day’s close, grouped by day of month and month.
How to read it
Rows = Day of month (1–31)
Columns = Months (Jan–Dec)
Cell value = average percentage move (signed format like +0.23% or -0.33%)
Heatmap = stronger color intensity indicates larger absolute average moves
Today highlight = the current calendar day cell is visually highlighted for fast context
Key settings
Reference timeframe (Daily): uses daily session data as the source of truth
Decimals / Signed formatting: control numeric display
Theme controls: fully customizable colors for positive/negative/neutral cells, headers, labels, and text
Font sizes: independently adjust header/labels/values
Heatmap scaling: set “max abs (%)” to match the volatility of the instrument
Notes / limitations
The indicator depends on the historical data available on TradingView for the selected
symbol and timeframe.
This is a statistical visualization tool. It does not predict future returns and does not generate trade signals.
Disclaimer
This script is for educational and informational purposes only and is not financial advice. Trading involves risk. Always do your own research and use proper risk management.
NQ Lunch High Low First Sweep StrategyThis script identifies the FIRST liquidity sweep of the Lunch session high or low
after the Lunch session has ended, based on ICT / Killzone concepts.
Logic summary:
• Tracks Lunch session High and Low (New York time)
• After Lunch session closes, monitors the market on 5-minute timeframe
• Triggers ONLY on the first sweep:
– Price wicks beyond Lunch High and closes back below → SHORT signal
– Price wicks beyond Lunch Low and closes back above → LONG signal
• Generates an alert at the exact bar where entry is expected
• Designed specifically for Nasdaq (NQ) futures
• One trade per day – no overtrading
Notes:
• Intended for 5-minute charts only
• Uses New York session timing
• This script does NOT manage exits (TP/SL) – entry logic only
• Best used as a confluence tool, not a standalone system
Educational & discretionary use only.
Statistical Deviation per AssetINDICATOR: STATISTICAL DEVIATION PER ASSET (SDPA)
1. Overview
The Statistical Deviation per Asset (SDPA) is a quantitative analysis tool designed to measure the strength and exhaustion of price movements. Unlike standard oscillators (like RSI ), the SDPA calculates the actual percentage deviation from the most recent pivot point (High or Low) and compares it against historical performance averages specific to each asset.
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2. Core Logic & Calculation
The script operates on a Mean Reversion principle. It assumes that every asset (Gold, Bitcoin, Ethereum, etc.) has a unique "volatility signature" depending on the timeframe.
* Dynamic Pivot Detection : The indicator identifies recent Swing Highs and Swing Lows using an adaptive lookback period.
* Real-Time Return Calculation : Once a pivot is confirmed, the script calculates the real-time percentage gain (from a Low) or loss (from a High).
* Zero-Indexed Histogram : This return is plotted as an oscillator centered around a Zero Line , representing the current trend's progress since the last reversal.
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3. Adaptive Intelligence (Multi-Asset & Multi-TF)
The SDPA is pre-loaded with a statistical database. It automatically adjusts its sensitivity and thresholds based on:
1. The Selected Asset : Whether trading XAUUSD , Bitcoin , or Solana , the deviation thresholds adapt to the specific volatility of that instrument.
2. The Timeframe (TF) : The calculation period ( period ) and performance targets ( hausse_perf / baisse_perf ) change dynamically. For example, a 1-minute scalping setup uses a longer lookback (200) compared to a Daily swing setup (10).
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4. Visual Anatomy
The interface is designed for instant "at-a-glance" interpretation:
* The Histogram :
* Green : Price is trending up since the last Swing Low .
* Red : Price is trending down since the last Swing High .
* Threshold Lines (The Statistical Averages) :
* Thick Line (60% Opacity) : Represents the Average Historical Deviation . When the histogram hits this line, the move is considered "statistically mature."
* Thin Line (70% Opacity) : Represents the Strong Deviation Zone (1.5x the average), indicating extreme momentum or potential exhaustion.
* Background Highlighting : The chart background colors automatically when the price exceeds historical averages, signaling a High-Probability Reversal Zone .
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5. How to Trade with SDPA
* Trend Maturity : If the histogram exceeds the Bullish Average (Green line), the current move has reached its typical historical limit. Traders should look for take-profit opportunities or wait for a reversal.
* Impulse Strength : A rapid move from the Zero Line toward the thresholds confirms strong institutional interest.
* Mean Reversion : When the histogram reaches the Strong Zone (1.5x), the price is "overextended" statistically, offering a high reward-to-risk ratio for counter-trend setups.
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6. Technical Parameters
* Asset Choice : Dropdown menu to select the specific asset.
* Colors : Customizable Bullish and Bearish colors to match any UI theme.
* Precision : Set to 4 decimal places to ensure accuracy across all asset types.
Flux Portfolio Visualizer | GL0WDASHFlux Portfolio Visualizer | GL0WDASH
Flux Portfolio Visualizer lets you simulate and track the performance of a multi-asset portfolio directly on the chart.
Choose up to 10 assets, assign custom allocation weights, and set a start date to generate a real-time equity curve based on historical price data.
The script performs one-time proportional allocation at the start date and then tracks equity forward without rebalancing, giving you a realistic view of how your portfolio would have evolved over time. It also includes a maximum equity drawdown tracker and an optional level line for reference.
Features:
• Allocate to up to 10 assets with custom weight percentages
• Specify initial capital and simulation start date
• Real-time equity curve based on confirmed bars
• Maximum equity drawdown tracking + table display
• Optional horizontal reference line
• Designed for long-horizon allocation experiments
Great for:
• Passive portfolio stress-testing
• Comparing allocation strategies
• Evaluating long-term crypto/asset mixes
• Visualizing risk via max drawdowns
This tool does not execute trades or rebalance—its purpose is pure visualization, giving traders clarity about how portfolios behave under different allocation assumptions.
If you expand or modify the indicator, please credit the original author.
HPDR Bands with projectionHPDR: Historical Price Delta Range
What is it? The HPDR indicator measures how much an asset’s price typically changes over a specific timeframe. It looks at historical price movements ("deltas") and organizes them into percentiles. These are then plotted on your chart as a median line surrounded by statistical bands.
This tool helps you understand an asset’s unique character and its typical price deviations.
Because the median is in this context a statistically relative stable value(if you add 7 values to 1000 it doesn't change much), it allows for high-probability projections of the future median.
For a clearer understanding of the indicator's logic, try setting the Range to 7 and the Offset to -7.
The 50% percentile Band signifies that in 50% of all bars, the price remained within this statistical range.
MA Cross + Trend Stats (Probabilistic)Short description (one-liner)
A MA-regime framework with historical regime stats + forward performance + optional trend/noise filters for trending context.
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Full description (TradingView-ready)
Overview
This indicator turns a classic Moving Average Cross into a regime-based trend dashboard. Instead of treating a cross as a standalone “buy/sell” event, it measures what historically happened after similar regime shifts on the current symbol and timeframe, and displays the results in a compact table.
It supports:
• EMA or SMA
• Custom fast/slow lengths (including .5 lengths via floor/ceil averaging)
• Optional trend quality filters for trending decisions:
o Slope filter (Slow MA slope)
o Market noise filter using Efficiency Ratio (ER) in real time
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What the table shows (how to read it)
The table has two rows: Bull (Fast > Slow) and Bear (Slow > Fast). Metrics are computed on completed regimes (historical segments that already ended).
N
Number of completed regimes measured. More samples generally means more stable estimates.
μ Δ% / Med Δ%
Average and median regime return from regime start to regime end. Median helps reduce the impact of outliers.
⏱ Bars
Average regime duration (in bars). Useful to calibrate realistic holding expectations for trending.
⬆ MFE% / ⬇ MAE%
• MFE (Maximum Favorable Excursion): max move in favor during the regime
• MAE (Maximum Adverse Excursion): max move against during the regime
These are context metrics for typical run-up and typical heat.
ER μ | Hit
Trend-quality proxy:
• ER μ: average Efficiency Ratio during regimes (0–1, higher = more directional / less noisy)
• Hit: % of regimes with ER above the historical threshold you set
Forward performance (+H μ|Hit)
For two user-defined horizons (e.g., +10 / +20 bars):
• μ: average forward return after the cross
• Hit: probability (%) that the forward return was positive
This is designed to provide probabilistic context, not certainty.
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“Trending” decision filters (optional)
These filters apply to signals/alerts/markers, not to the raw regime statistics:
1. Slope filter (Slow MA):
Only allow Bull signals if the Slow MA slope is positive (and Bear signals if negative).
2. Market noise filter (ER realtime):
Only allow signals when current ER exceeds your chosen threshold (helps avoid choppy conditions).
________________________________________
Suggested usage (educational)
• Treat Bull/Bear as a regime label (state), not a prediction.
• Use Forward Hit% as an estimate of historical frequency, not a guarantee.
• If ER realtime is below threshold, consider it a noisier environment (higher whipsaw risk).
• Combine with your own risk rules and confirmation (structure, volatility, volume, HTF context, etc.).
________________________________________
Notes
• Results depend on symbol, timeframe, and loaded history.
• Statistics are historical summaries and can change as more data becomes available.
• This tool is intended for research and decision support, not as standalone trade advice.
________________________________________
Disclaimer
This script is for educational and informational purposes only and does not constitute financial, investment, or trading advice. Trading involves risk. You are responsible for your own decisions and risk management.
IQR Bands boromeyIQR is the price's "comfort zone," covering the middle 50% of activity.
Inside: Just noise. Ignore it.
Breakout: A real move. Pay attention.
It filters out choppy markets so you only catch the true trends.
Bullish/Bearish Movement SumThis indicator calculates and displays the cumulative sum of bullish and bearish price movements over a specified period.
Features:
- Green line: Cumulative sum of all bullish movements
- Red line: Cumulative sum of all bearish movements (absolute value)
- Blue area: Net difference (bullish - bearish)
- Information table showing current values and bull/bear ratio
Settings:
- Calculation Period: Choose rolling window size (default: 100 bars) or 0 for cumulative from start
- Calculation Mode: Choose between "Points" (absolute price changes) or "Percentage" (% changes)
Use Cases:
- Identify market directional strength
- Compare bullish vs bearish pressure
- Spot divergences between price and directional momentum
- Ratio > 1 indicates more bullish than bearish movement
Developed with assistance from Claude (Anthropic)
True S/R Ultimate [Wonra]# True S/R Ultimate - TradingView Description
## Short Description (for script settings)
```
Volume-weighted Support & Resistance levels with buyer/seller pressure analysis. Shows the strongest levels based on historical price reactions and trading volume.
```
## Full Description
```
█ OVERVIEW
True S/R Ultimate identifies genuine support and resistance levels by analyzing historical pivot points weighted by trading volume. Unlike traditional S/R indicators that draw lines everywhere, this indicator filters and displays only the strongest levels where significant trading activity occurred.
The indicator uses a multi-factor approach:
• Volume accumulation at each price level
• Number of times price has touched/reacted to the level
• Buyer vs Seller pressure ratio at each zone
█ HOW IT WORKS
The indicator detects pivot highs and lows across your specified lookback period. When multiple pivots occur near the same price, they are grouped together, and their volumes are accumulated. This creates "volume clusters" that represent areas where traders have historically found value.
LEVEL NAMING:
• S1, S2, S3... = Support levels (below current price), ranked by volume strength
• R1, R2, R3... = Resistance levels (above current price), ranked by volume strength
• S1/R1 = Strongest level with highest accumulated volume
• S5/R5 = Weakest displayed level
█ READING THE LABELS
Each level displays:
┌─────────────────────────────────┐
│ R2 │ 1,789 │ ← Level name + Price
│ Vol: 21.8M │ 🟢 BUY 64% │ ← Volume + Dominant pressure
└─────────────────────────────────┘
VOLUME (Vol):
Shows the total accumulated trading volume at this level. Higher volume = stronger level.
• K = Thousands (1K = 1,000)
• M = Millions (1M = 1,000,000)
• B = Billions (1B = 1,000,000,000)
PRESSURE INDICATOR:
• 🟢 BUY XX% = Buyers were dominant at this level (bullish pressure)
• 🔴 SELL XX% = Sellers were dominant at this level (bearish pressure)
• Percentage shows the strength of the dominant side
█ COLOR CODING
The indicator uses smart color coding based on WHO was in control at each level:
GREEN/TEAL ZONES (🟢 BUY pressure > 50%):
• Buyers were more aggressive when price hit this level
• For SUPPORT: Strong buy interest, likely to bounce again
• For RESISTANCE: May break through as buyers are willing to pay higher
RED ZONES (🔴 SELL pressure > 50%):
• Sellers were more aggressive when price hit this level
• For RESISTANCE: Strong selling pressure, likely to reject again
• For SUPPORT: Weaker support, may break down
█ HOW TO USE
SCENARIO 1: Price approaching GREEN Support (e.g., S1 with 🟢 BUY 76%)
✓ This is a HIGH-PROBABILITY bounce zone
✓ Previous touches showed strong buyer absorption
✓ Consider LONG entries with stop below the zone
SCENARIO 2: Price approaching RED Resistance (e.g., R1 with 🔴 SELL 71%)
✓ This is a HIGH-PROBABILITY rejection zone
✓ Previous touches showed strong seller distribution
✓ Consider SHORT entries with stop above the zone
SCENARIO 3: Price approaching GREEN Resistance (e.g., R2 with 🟢 BUY 64%)
⚠ This resistance may be WEAK
⚠ Buyers were aggressive here before - may break through
⚠ Wait for confirmation before shorting
SCENARIO 4: Price approaching RED Support (e.g., S3 with 🔴 SELL 72%)
⚠ This support may be WEAK
⚠ Sellers were aggressive here - may break down
⚠ Be cautious with long entries
█ WHY LEVELS ABOVE PRICE CAN BE GREEN
When you see a RESISTANCE level (above current price) colored GREEN:
• It means when price was previously AT that level, BUYERS were dominant
• This doesn't mean the level is now support
• It means if price revisits this zone, it might break THROUGH (not reject)
• The buying pressure from before suggests demand at that price
Conversely, when you see a SUPPORT level (below price) colored RED:
• Previous touches showed sellers were in control
• This support may be weaker than it appears
• Consider tighter stop losses if going long at this level
█ SETTINGS
📊 MAIN SETTINGS
• Lookback Bars: How far back to analyze (default: 500)
• Minimum Touches: Required reactions to form a valid level (default: 2)
• Zone Width: Tolerance for grouping similar prices (default: 1%)
• Pivot Length: Sensitivity for detecting pivots (default: 5)
🎨 DISPLAY
• Max Levels: How many S/R levels to show per side (default: 5)
• Show Zone Boxes: Visual boxes around each level
🎨 COLORS
• Bullish/Buyers: Color for buy-dominated zones
• Bearish/Sellers: Color for sell-dominated zones
█ BEST PRACTICES
1. Use on higher timeframes (4H, Daily) for stronger levels
2. Combine with other confluence (trendlines, EMAs, Fibonacci)
3. Watch for volume confirmation when price approaches a level
4. S1/R1 are your primary levels - trade these with more size
5. S4/S5 or R4/R5 may be weaker - use confirmation
█ ALERTS
The indicator includes built-in alert conditions:
• "Near Support" - Price approaching strongest support
• "Near Resistance" - Price approaching strongest resistance
█ CREDITS
Developed by Wonra
Concept: Volume Profile meets Smart Money Concepts
```
## Tags (for TradingView)
```
support, resistance, volume, levels, zones, institutional, smart-money, supply-demand, order-flow, volume-profile
```
[TA] Range Regime# Range Regime – Candle Range Monitor (RR)
## Short Description
Tracks current candle range vs historical average, flags range spikes, and labels volatility regime (LOW / NORMAL / HIGH) at a glance.
---
## What It Does
Range Regime (RR) is a volatility/range monitoring indicator designed to help you quickly understand whether the market is *quiet, normal, or expanding* on the current timeframe.
It calculates:
* Current Range
* Either Candle Range (High–Low) *or* True Range (TR)
* Average Range over a lookback window (optionally smoothed)
* Max / Min / Mid range levels over the same lookback
* Spike detection
* Marks candles where current range is ≥ (Spike Threshold × Average)
* Regime state
* Compares the current range vs a longer Baseline Average
* Labels LOW / NORMAL / HIGH volatility regime in a small table
It also shows a compact stats table with points and ticks (based on `syminfo.mintick`) so you can think in the units you actually trade.
---
## Why It’s Helpful
This tool is useful because range expansion and compression often determine:
* Whether a setup is worth taking right now
* Whether your stops/targets are realistic for the session
* Whether you should size down (high regime) or avoid forcing trades (low regime)
* When the market is shifting from chop → impulse (spikes) or impulse → stall (compression)
In practice, RR helps you answer:
* “Is volatility expanding or contracting?”
* “Is this move unusually large relative to recent history?”
* “Are we in a high-vol environment where risk needs to change?”
---
## How To Use It
1. Add to chart (it plots in its own pane).
2. Choose your Range Mode :
* Candle (H–L) : pure bar range (great for clean range monitoring)
* True Range (TR) : includes gaps (better for overnight / news / gap-prone markets)
3. Set Lookback (N) :
* Typical: 20–100
* Smaller = more reactive, larger = more stable
4. Optionally enable Smooth the Average :
* Helps reduce noise and false “spike” triggers
5. Adjust Spike Threshold (× Avg) :
* Common values:
* 1.3–1.6 = more frequent spike flags
* 1.8–2.5 = only “real” expansions get flagged
6. Set Baseline Length (Regime) :
* Typical: 150–300
* This is your “background volatility context”
---
## How To Read The Plots
* Current Range (columns): what the market just “spent” in range.
* Avg: normal range for this timeframe.
* Max / Min: extremes over the lookback window.
* Mid: midpoint between Max and Min (quick “center” reference).
* Spike Line (× Avg): the threshold for a “spike.”
* Background highlight: appears when the current candle qualifies as a spike.
* Regime table (top-left):
* HIGH when current range > 1.25× baseline average
* LOW when current range < 0.75× baseline average
* Otherwise NORMAL
---
## Practical Trading Uses (Examples)
* Risk calibration: If regime is HIGH , consider wider stops / smaller size.
* Trade selection: Avoid mean-reversion scalps when spikes are frequent (momentum environment).
* Session context: Spot when market transitions from tight range (LOW) into expansion (spike + HIGH).
* Instrument comparison: Great for comparing how “active” ES vs NQ vs CL is *on the same timeframe*.
---
## Suggested Defaults
* Lookback (N): 50
* Range Mode: True Range (TR) for gap-prone markets; Candle (H–L) for cleaner intraday bars
* Smoothing: On, length 10
* Spike Threshold: 1.5×
* Baseline Length: 200
---
## Notes / Limitations
* This is not a buy/sell signal . It’s a volatility/range context tool .
* Results depend on timeframe. A spike on 1m means something very different than a spike on 1h.
* “Ticks” display uses the symbol’s `mintick` and will be most meaningful on instruments with standardized tick sizes (futures, many FX pairs, etc.).
---
## Invite-Only / Access Copy
This script is published as “Invite-Only.”
If you’ve been granted access, it will appear under Indicators → Invite-only scripts on TradingView.
If you don’t see it, you likely haven’t been added yet—request access from the publisher.
---
Kairos MA Strategy [Personal Version] BHow it Works:
Trend Definition: Uses a Fast MA (e.g., SMA 10) and a Slow MA (e.g., SMA 11).
Uptrend: Fast MA > Slow MA.
Downtrend: Fast MA < Slow MA.
Entry Trigger: The price must retrace to touch the Fast MA.
Validation: The pullback is validated by ATR limits to ensure the price hasn't wicked or closed too far past the MA (preventing "catching a falling knife").
Filters:
Slope Filter: Ensures the MAs have a steep enough angle to avoid trading during flat/choppy markets.
Volatility: Checks VIX (maximum fear) and ATR (minimum movement) to ensure safe market conditions.
Confluence: Optional checks from oscillators like RSI, Stochastic, CCI, etc.
Exits:
Fixed Targets: Uses a defined Take Profit and Stop Loss in points.
No Trade Zone (NTZ): A specific time window that forces all active trades to close (e.g., to avoid holding overnight).
Unique Features:
Custom Dashboard: Displays real-time win rates, streaks, and a "Strategy Grade" directly on the chart.
Dual-Engine: Runs as both a visual indicator (with custom labels) and a backtestable strategy simultaneously.
RsRotation Dashboard [Multi-MA + RSI] USThis uses the relative strength of the stock compared with the QQQ ticker.
Tether Dynamics - Statistical Exhaustion EngineOverview
This strategy detects statistical exhaustion in price movement by modeling price as a particle tethered to a dynamic anchor. When price stretches too far from equilibrium and multiple independent statistical detectors confirm anomalous behavior, the strategy identifies high-probability mean-reversion opportunities.
Unlike simple oversold/overbought indicators, this system fuses concepts from classical mechanics , stochastic filtering , multivariate statistics , and statistical process control into a unified detection framework.
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THEORETICAL FOUNDATION
1. The Tethered Particle Model
The framework draws inspiration from Polyak's heavy ball method in optimization theory, where a particle with momentum navigates a loss landscape. Here, price is modeled as a particle connected to a moving anchor (adaptive EMA) by an elastic "chain" whose length scales with volatility (ATR). This creates a natural physics framework:
Displacement (x) : Distance from anchor, normalized by chain length
Velocity (v) : Rate of change of displacement
Acceleration (a) : Rate of change of velocity
This state vector defines the system's "phase space" — a complete description of price dynamics relative to equilibrium.
2. Adaptive Anchor (Kaufman Efficiency)
The anchor uses an adaptive smoothing approach inspired by Perry Kaufman's Adaptive Moving Average. The Efficiency Ratio measures trend strength:
ER = |Direction| / Volatility = |Price - Price | / Σ|ΔPrice|
High efficiency (trending) → faster adaptation
Low efficiency (choppy) → slower, more stable anchor
This prevents whipsaws in ranging markets while staying responsive in trends.
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DETECTION ARCHITECTURE
The strategy employs three independent statistical detectors , each grounded in distinct mathematical frameworks. A signal fires when price shows extended tension AND any detector confirms anomalous behavior AND momentum is decelerating (exhaustion).
Detector 1: Mahalanobis Distance (Multivariate Outlier Detection)
The Mahalanobis distance measures how "unusual" the current state vector is, accounting for correlations between displacement, velocity, and acceleration:
D² = (x - μ)ᵀ Σ⁻¹ (x - μ)
Where Σ is the full 3×3 covariance matrix. Under multivariate normality, D² follows a chi-squared distribution with 3 degrees of freedom:
χ²(3, 0.90) = 6.25 → 10% of observations exceed this
χ²(3, 0.95) = 7.81 → 5% of observations exceed this
This detector identifies states that are jointly extreme — even if no single variable looks unusual alone.
Why it matters: A price might have moderate displacement and moderate velocity, but the combination could be highly improbable. Mahalanobis captures this multivariate structure that univariate indicators miss.
Detector 2: CUSUM Change-Point Detection
Cumulative Sum (CUSUM) is a sequential analysis technique from statistical process control. It accumulates standardized deviations from the mean:
S⁺ₜ = max(0, S⁺ₜ₋₁ + zₜ - drift)
S⁻ₜ = min(0, S⁻ₜ₋₁ + zₜ + drift)
When either cumulative sum breaches a threshold, a "change point" is detected — the process has shifted from its baseline regime.
Why it matters: CUSUM detects subtle, persistent shifts that might not trigger on any single bar. It's sensitive to regime changes that precede reversals.
Detector 3: Kalman Innovation Filter (Ornstein-Uhlenbeck Model)
This detector models displacement as an Ornstein-Uhlenbeck process — the continuous-time analog of AR(1) mean-reversion:
dx = θ(μ - x)dt + σdW
A Kalman filter tracks the expected displacement and computes the innovation (prediction error):
νₜ = (yₜ - x̂ₜ|ₜ₋₁) / √Sₜ
Under correct model specification, normalized innovations should be ~N(0,1). Large innovations indicate the mean-reversion model is breaking down — price is behaving "unexpectedly" relative to equilibrium dynamics.
Adaptive Q Estimation: The filter continuously adjusts its process noise estimate based on innovation autocorrelation, maintaining calibration across different volatility regimes.
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SIGNAL LOGIC
Long Signal Requirements:
Z-Displacement < -σ threshold (price stretched below anchor)
ANY detector fires (Mahalanobis outlier OR CUSUM change OR Kalman innovation < -2σ)
Z-Acceleration > 0 (downward momentum decelerating)
Short Signal Requirements:
Z-Displacement > +σ threshold (price stretched above anchor)
ANY detector fires
Z-Acceleration < 0 (upward momentum decelerating)
The deceleration requirement ensures we're catching exhaustion rather than fighting momentum.
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RISK MANAGEMENT
Scale-Out Exit Strategy
Rather than all-or-nothing exits, the strategy takes profits at multiple R-levels:
Scale 1: 20% at 0.5R
Scale 2: 20% at 1.0R
Scale 3: 10% at 1.5R (optional)
Remainder: Trailing stop
This locks in gains while allowing winners to run.
Adaptive Trailing Stop
After reaching the activation threshold (default 1R), the stop trails from the highest high (longs) or lowest low (shorts) at a configurable ATR multiple.
Reversal Logic
When an opposite signal fires while in position, the strategy can close and flip direction rather than waiting for a stop-out.
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PARAMETER GUIDANCE
Anchor Period (24) : Base period for adaptive anchor
ATR Period (14) : Volatility measurement
Chain Length Mult (2.5) : Tether elasticity — higher = more stretch allowed
Long Tension σ (1.5) : Lower = more signals
Short Tension σ (2.0) : Higher threshold for shorts (trend asymmetry)
Mahalanobis Threshold (6.25) : χ²(3, 0.90) — adjust for signal frequency
CUSUM Threshold (3.0) : Lower = more sensitive to regime shifts
Lookback Window (100) : Statistical estimation window
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BACKTEST NOTES
Historical testing on NQ (2020-2025) suggests:
Long signals show stronger edge than shorts in equity indices
1H and 30-min timeframes balance signal quality vs. frequency
"Long Only" mode recommended for equity index futures
Important: Past performance does not guarantee future results. This strategy involves significant risk of loss.
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MATHEMATICAL REFERENCES
Polyak, B.T. (1964). "Some methods of speeding up the convergence of iteration methods" (Heavy ball method)
Bertsekas, D.P. (1999). "Nonlinear Programming" (Heavy ball method / momentum dynamics)
Mahalanobis, P.C. (1936). "On the generalized distance in statistics"
Page, E.S. (1954). "Continuous inspection schemes" (CUSUM)
Kalman, R.E. (1960). "A new approach to linear filtering and prediction problems"
Uhlenbeck, G.E. & Ornstein, L.S. (1930). "On the theory of Brownian motion"
Kaufman, P. (1995). "Smarter Trading" (Adaptive Moving Average)
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DISCLAIMER
This strategy is provided for educational and research purposes. Trading futures involves substantial risk of loss. The statistical methods employed do not guarantee profitable outcomes. Always use appropriate position sizing and risk management.
NTA MTF Context Pro🔹 NTA – MTF Context Pro
Multi-Timeframe Market Context & Institutional Bias Panel
📌 Overview
NTA – MTF Context Pro is a public, closed-source multi-timeframe market context indicator designed to help traders objectively evaluate directional bias, trend quality, and market conditions across multiple higher and lower timeframes from a single panel.
This indicator does not generate trade entries or signals.
Its purpose is to provide context, confirmation, and environmental filtering prior to executing trades with an external strategy or execution model.
🧠 Methodology & Conceptual Logic
The indicator follows a top-down institutional analysis framework, combining multiple analytical dimensions to describe market conditions rather than predict price.
For each timeframe (Monthly, Weekly, Daily, 4H, and 1H), the indicator performs the following conceptual evaluations:
1️⃣ Trend Structure Classification
Trend direction is determined through moving-average structure analysis, comparing medium-term and long-term averages to classify each timeframe as:
Bullish
Bearish
Neutral
This step defines structural market bias, not trade timing.
2️⃣ Trend Strength & Quality Assessment
To avoid low-quality or transitional environments, the indicator applies:
Directional strength measurement
ADX-based trend validation
This helps filter:
Weak momentum phases
Ranging or choppy conditions
Incomplete trend development
3️⃣ Volatility & Price Expansion Analysis
The indicator evaluates volatility normalization using ATR-based measurements to confirm that price movement is supported by sufficient expansion.
This step helps distinguish:
Active institutional participation
Compressed or inefficient price conditions
4️⃣ Multi-Timeframe Weighting
Higher timeframes are assigned greater influence in the final assessment to reflect institutional prioritization of macro structure over lower-timeframe noise.
This weighting framework reduces bias from isolated lower-timeframe movements.
🔢 Global Market Score (0–100)
All evaluated components are aggregated into a Global Market Score, summarizing the overall market environment:
65–100 → Bullish Bias
35–64 → Neutral / Range Environment
0–34 → Bearish Bias
The score is designed as a context filter, not a trading signal.
📊 Panel Output & Interpretation
For each timeframe, the panel displays:
TF → Timeframe analyzed
Trend → Bullish / Bearish / Neutral
Strength → Relative directional intensity
ADX → Trend validity
ATR % → Volatility expansion level
The top section displays:
Global Score
Dominant Market Bias
Confirmation status (Confirmed / Weak)
Visual elements dynamically adapt to market state for clarity and readability.
🎯 Intended Use
This indicator is intended for:
Advanced discretionary traders
Smart Money & market structure approaches
Swing and intraday analysis
Trade filtering and directional bias confirmation
Manual or algorithmic trading systems requiring contextual validation
Best used in conjunction with a separate execution model.
⚠️ Disclaimer
❌ Not a buy/sell signal generator
❌ No entry or exit logic
✅ Context and confirmation tool only
Always apply proper risk management.
🏷️ Credits
Developed by NexTrade Academy
Educational and analytical tool
Use at your own risk.
CPG - Institutional Premium Arbitrage SystemConcept & Logic:
This strategy captures institutional sentiment by analyzing the Cross-Exchange Arbitrage Data between Coinbase (USD pair) and Binance (USDT pair). Instead of using raw price difference which is noisy, this script employs a Proprietary Dynamic Threshold Algorithm. It normalizes the premium data using a custom volatility-adjusted window to filter out retail noise and identify genuine "Whale Accumulation" zones.
Key Features:
Data Source: Real-time BTC/USD vs BTC/USDT spread analysis.
Signal Filtering: The proprietary algorithm (closed-source logic) dynamically adjusts upper and lower bands to prevent false signals during low liquidity periods.
Execution:
Bullish: When the premium breaks the dynamic upper threshold (Strong Institutional Buying).
Bearish: When the premium drops below the dynamic lower threshold (Institutional Selling).
Usage:
Note: The dynamic threshold algorithm is specifically calibrated for Bitcoin's unique liquidity structure. Extensive backtesting shows that this logic is NOT suitable for altcoins (like ETH or SOL). Please strictly use it on BTC pairs.
策略核心：
本策略透過分析 Coinbase (USD) 與 Binance (USDT) 之間的跨交易所資金流 (Arbitrage Data)，來捕捉機構投資者的動向。 原始的價差數據通常充滿雜訊，因此本腳本內建了一套**「獨家動態閥值演算法」**。該算法能對數據進行平滑處理與正規化，有效過濾市場雜訊，精準識別出機構大戶的資金流向。
功能特點：
數據源： 即時運算 BTC/USD 與 BTC/USDT 的溢價差。
獨家過濾： 閉源的動態演算法會根據波動率自動調整上下軌閥值，避免假突破。
交易訊號：
看多： 溢價突破動態上軌（機構強力買入）。
看空： 溢價跌破動態下軌（機構拋售）。
用法：
注意： 本策略的動態閥值演算法是針對比特幣的流動性結構進行嚴格校準的。回測數據顯示，此邏輯不適用於 ETH 或 SOL 等其他幣種。請務必僅在 BTC 圖表上使用。
Cross-Option Pair Intelligence# Elite Cross-Option Pair Intelligence System
## **Discover Options Trades BEFORE The Breakout - Institutional Cross-Strike Compression Analysis**
***
## **🔥 THE GAME-CHANGING DIFFERENCE**
Most option traders wait for price to move, then chase expensive options. **This indicator does the opposite** - it identifies **low-risk option combinations** where Call and Put premiums are **compressed (similar prices)** across different strikes, then alerts you **before the breakout** happens.
### **What Makes This Unique?**
This is the **ONLY indicator on TradingView** that performs **cross-strike compression analysis** - comparing EVERY Call option premium with EVERY Put option premium to find the **sweet spot** where:
✅ Premiums are nearly equal (low volatility skew)
✅ Time decay risk is minimized
✅ Market is coiled and ready to explode
✅ Risk-reward is optimal
**When compression breaks = High-probability directional move!**
***
## **📊 HOW IT WORKS - INSTITUTIONAL METHODOLOGY**
### **Step 1: Cross-Option Pair Matrix Analysis**
The indicator fetches **real-time premium data** from 8 customizable strikes and performs a **matrix comparison**:
```
25800 CE vs 25500 PE ✓
25800 CE vs 25550 PE ✓
25800 CE vs 25600 PE ✓
... (64 total comparisons)
```
**When it finds:** `25750 CE (₹120) ≈ 25700 PE (₹118)` → **COMPRESSION DETECTED! ✓✓**
### **Step 2: Lowest Price Match Identification**
The system identifies the **cheapest compressed pair** - this is your **optimal entry zone** because:
- **Low premium** = Lower capital risk
- **Compression** = Fair pricing (no IV inflation)
- **Cross-strike match** = Market indecision = Breakout imminent
### **Step 3: Compression Zone Tracking**
The indicator draws a **yellow compression box** on your chart and tracks:
- How long compression persists (minimum 3 bars default)
- Price boundaries during compression
- Volume and momentum buildup
### **Step 4: Breakout Signal Generation**
When price breaks out of compression with:
- ✅ **High volume surge** (1.3x+ average)
- ✅ **Strong momentum** (ATR-based)
- ✅ **RSI confirmation** (>55 bullish, <45 bearish)
**→ BUY CALL or BUY PUT signal fires!**
***
## **🎯 REAL TRADING EXAMPLE**
**Scenario:** NIFTY consolidating around 25,700
**What You See:**
1. **Option Chain Table** shows:
- 25750 CE: ₹115 ✓
- 25700 PE: ₹112 ✓✓
- **Status: "Lowest Price Match: 25750CE / 25700PE ✓"**
2. **Chart displays:**
- Yellow compression box between 25,680 - 25,720
- "⚠️ COMPRESSION ZONE ACTIVE - PREPARE FOR BREAKOUT"
3. **Price breaks above 25,720 with volume**
- 🔥 **BUY CALL signal appears!**
- **Strike: 25750CE**
- **Entry: ₹25,735**
- **T1: ₹25,795 (1.5x compression range)**
- **T2: ₹25,855 (2.5x compression range)**
- **SL: ₹25,680 (compression low)**
**Result:** You bought the option **BEFORE** the move, at **compressed premium**, with **clear targets and stop loss**!
***
## **💎 KEY FEATURES**
### **1. Live NSE Option Chain Display**
- Real-time premium tracking for 8 strikes
- Color-coded compression zones (Green ✓✓)
- Automatically highlights lowest price match
- Works with NIFTY, BANKNIFTY, FINNIFTY
### **2. Cross-Strike Compression Detection**
- Compares ALL Calls with ALL Puts (64 comparisons)
- Identifies similar premiums across different strikes
- Finds the cheapest compressed pair automatically
- Adjustable compression tolerance (1-20 points)
### **3. Visual Compression Zone**
- Yellow box on chart showing consolidation
- Real-time boundary updates
- Background color highlighting
- Duration tracking (min bars configurable)
### **4. Smart Breakout Signals**
- Multi-factor confirmation (Price + Volume + RSI + ATR)
- Directional labels: "🔥 BUY CALL" or "🔥 BUY PUT"
- Shows exact strike to trade
- Entry price displayed on label
### **5. Automatic Target Calculation**
- T1: 1.5x compression range expansion
- T2: 2.5x compression range expansion
- Stop Loss: Compression boundary
- Visual target lines on chart
### **6. Professional Table Display**
- Top: Option chain with live premiums
- Strikes highlighted when compressed
- Market status indicator
- Fully customizable position and size
### **7. Alert System**
- Compression zone entry alert
- Buy Call/Put signal alerts
- Includes strike, entry, and targets
- One alert per bar (no spam)
***
## **⚙️ CONFIGURATION - FULLY CUSTOMIZABLE**
### **Option Chain Setup:**
- Choose Index: NIFTY / BANKNIFTY / FINNIFTY
- Set Expiry: YYMMDD format (e.g., 251226)
- Configure 8 strikes manually (50-point intervals typical)
### **Compression Detection:**
- **Tolerance:** 1-20 points (default 5.0)
- Lower = Stricter compression
- Higher = More matches found
- **Min Duration:** 1-10 bars (default 3)
- Ensures persistent compression
### **Breakout Settings:**
- **ATR Multiplier:** 0.5-5.0 (default 1.5)
- **Volume Threshold:** 1.0-3.0x (default 1.3x)
- **RSI Bullish/Bearish:** 55/45 default
### **Display Options:**
- Enable/disable table, compression box, labels, targets
- Table position: Top/Middle/Bottom × Left/Center/Right
- Text size: Tiny/Small/Normal
***
## **📈 TRADING STRATEGY GUIDE**
### **For Intraday Traders:**
1. **Morning Setup:**
- Apply indicator to 5-min NIFTY/BANKNIFTY chart
- Check option chain table for compression
2. **Wait for Compression:**
- Watch for green checkmarks (✓✓) in table
- Note the "Lowest Price Match" strikes
- Compression zone box appears on chart
3. **Entry Signal:**
- Wait for breakout signal (BUY CALL/PUT label)
- Enter the exact strike shown
- Set stop loss at compression boundary
4. **Exit Strategy:**
- Take partial profit at T1 (1.5x move)
- Trail stop loss to entry
- Full exit at T2 (2.5x move)
### **For Swing Traders:**
1. **Daily Chart Analysis:**
- Apply to daily timeframe
- Look for multi-day compression zones
- Larger compression = Bigger breakout potential
2. **Position Sizing:**
- Compression zones on daily = Higher confidence
- Can hold options for multiple days
- Targets are proportionally larger
### **For Option Sellers:**
1. **Compression = Volatility Crush Zone**
- When compression detected, IV is balanced
- Consider selling strangles/straddles INSIDE compression
- Exit when breakout signal fires
***
## **🎓 UNDERSTANDING THE EDGE**
### **Why Cross-Strike Compression Works:**
**Traditional Approach:**
- Traders compare same strike: "25700 CE vs 25700 PE"
- Limited information
- Miss the bigger picture
**Institutional Approach (This Indicator):**
- Compare ALL strikes: "25750 CE vs 25700 PE"
- **Reveals true market structure**
- Shows where smart money is positioned
### **The Psychology Behind It:**
When a **Call at 25750** trades at the same premium as a **Put at 25700**:
1. **Option writers** (institutions) see balanced risk
2. **Implied volatility** is not inflated
3. **Market makers** are comfortable with prices
4. **Time decay** is priced fairly
**This creates a LOW-RISK entry point!**
When compression breaks → Market has chosen direction → Follow with confidence!
***
## **⚡ TECHNICAL SPECIFICATIONS**
### **Indicator Type:**
- Overlay: Yes (signals on price chart)
- Separate Pane: No
- Max Labels: 500
- Max Lines: 500
- Max Boxes: 500
### **Data Requirements:**
- Works with NSE option data
- Requires TradingView Pro/Premium for multiple `request.security()` calls
- Real-time or delayed data supported
- Minimum timeframe: 1-minute
### **Option Symbol Format:**
- NSE standard: `NSE:NIFTY251226C25700`
- Automatically constructed from inputs
- Supports all NSE option contracts
### **Performance:**
- 8 Call options fetched
- 8 Put options fetched
- 64 cross-comparisons per bar
- Optimized array operations
- No repainting
***
## **🚀 QUICK START GUIDE**
### **Step 1: Add to Chart**
1. Open NIFTY or BANKNIFTY chart (any timeframe)
2. Add "Guru Dronacharya - Cross-Option Pair Intelligence"
3. Chart will show option chain table on right side
### **Step 2: Configure Strikes**
1. Check current spot price (e.g., 25,700)
2. Set Strike 5 (ATM) = 25700
3. Set other strikes in 50-point intervals:
- Strike 1: 25500
- Strike 2: 25550
- Strike 3: 25600
- Strike 4: 25650
- Strike 5: 25700 (ATM)
- Strike 6: 25750
- Strike 7: 25800
- Strike 8: 25850
### **Step 3: Set Expiry**
1. Find current/next weekly expiry
2. Format as YYMMDD (e.g., 26-Dec-2025 = 251226)
3. Enter in "Expiry" input field
### **Step 4: Watch for Signals**
- Green ✓✓ in table = Compression detected
- Yellow box on chart = Consolidation zone
- 🔥 BUY CALL/PUT label = Trade signal!
***
## **💡 PRO TIPS**
### **Best Timeframes:**
- **5-min:** Intraday scalping (3-5 signals/day)
- **15-min:** Swing intraday (1-2 signals/day)
- **Daily:** Positional trades (high-conviction setups)
### **Best Market Conditions:**
- ✅ **Consolidation after trend:** Compression forms naturally
- ✅ **Pre-event/news:** IV crush opportunities
- ✅ **Range-bound markets:** Multiple compression zones
- ❌ **Strong trending markets:** Less compression, more chasing
### **Risk Management:**
- Never risk more than 2% account per trade
- Always use stop loss (provided automatically)
- Take partial profits at T1
- Let winners run to T2
### **Strike Selection:**
- ATM ± 4 strikes covers 90% of scenarios
- Wider range for high volatility (BANKNIFTY)
- Adjust strikes if price moves >2% from center
***
## **🏆 WHAT TRADERS ARE SAYING**
✅ **"Finally, an indicator that shows option premiums on the chart!"**
✅ **"The cross-strike compression detection is genius - never seen this before"**
✅ **"Stopped me from chasing expensive options after the move"**
✅ **"The table shows exactly which strike to trade - no guesswork"**
✅ **"Compression zones work like magic - high win rate setups"**
***
## **⚠️ IMPORTANT NOTES**
### **Data Requirements:**
- Requires TradingView Premium or Pro subscription
- NSE option data must be available
- Some strikes may show 0 if not listed/traded
### **Not Financial Advice:**
- This is an analysis tool, not trading advice
- Always do your own research
- Options trading carries significant risk
- Past performance ≠ future results
### **Best Practices:**
- Test on paper/demo account first
- Start with small position sizes
- Understand option Greeks before trading
- Never trade illiquid strikes
- Check bid-ask spreads before entry
***
## **📞 SUPPORT & UPDATES**
- **Version:** 1.0 (December 2025)
- **Pine Script:** v5
- **Updates:** Regular improvements based on feedback
- **Documentation:** Detailed tooltips in settings
- **Community:** Comment section for questions
***
## **🎯 WHO IS THIS FOR?**
### **Perfect For:**
✅ Options traders (beginner to advanced)
✅ Intraday scalpers looking for edge
✅ Swing traders seeking high-probability setups
✅ Traders who want to BUY options at fair value
✅ Anyone tired of chasing expensive options after the move
### **Not Suitable For:**
❌ Stock/equity traders only
❌ Long-term investors
❌ Traders without option trading knowledge
❌ Users without TradingView Premium/Pro
***
## **🌟 FINAL WORDS**
**Guru Dronacharya** brings **institutional-grade cross-option pair analysis** to retail traders for the first time.
The ability to see **real-time compression** between Calls and Puts across different strikes is a **game-changer** that was previously only available to professional trading desks.
**Stop chasing expensive options.**
**Start trading compression breakouts.**
**Let the market show you where the smart money is positioned.**
***
## **📊 TECHNICAL TAGS**
`#Options` `#NIFTY` `#BANKNIFTY` `#OptionsTrading` `#Compression` `#Breakout` `#PairTrading` `#PremiumAnalysis` `#CrossStrike` `#OptionChain` `#NSE` `#IndianMarket` `#IntradayTrading` `#SwingTrading` `#OptionStrategy` `#VolatilityAnalysis` `#InstitutionalTrading` `#SmartMoney`
***
**Install now and discover the edge professional traders have been using for years!** 🚀📈
***
*Disclaimer: Options trading involves substantial risk of loss. This indicator is for educational and analytical purposes only. Always consult with a qualified financial advisor before making trading decisions.*
ORB Fusion ML AdaptiveORB FUSION ML - ADAPTIVE OPENING RANGE BREAKOUT SYSTEM
INTRODUCTION
ORB Fusion ML is an advanced Opening Range Breakout (ORB) system that combines traditional ORB methodology with machine learning probability scoring and adaptive reversal trading. Unlike basic ORB indicators, this system features intelligent breakout filtering, failed breakout detection, and complete trade lifecycle management with real-time visual feedback.
This guide explains the theoretical concepts, system components, and educational examples of how the indicator operates.
WHAT IS OPENING RANGE BREAKOUT (ORB)?
Core Concept:
The Opening Range Breakout strategy is based on the observation that the first 15-60 minutes of trading often establish a range that serves as support/resistance for the remainder of the session. Breakouts beyond this range have historically indicated potential directional moves.
How It Works:
Range Formation: System identifies high and low during opening period (default 30 minutes)
Breakout Detection: Monitors price for confirmed breaks above/below range
Signal Generation: Generates signals based on breakout method and filters
Target Projection: Projects extension targets based on range size
Why ORB May Be Effective:
Opening period often represents institutional positioning
Range boundaries historically act as support/resistance
Breakouts may indicate strong directional bias
Failed breakouts may signal reversal opportunities
Note: Historical patterns do not guarantee future occurrences.
SYSTEM COMPONENTS
1. OPENING RANGE DETECTION
Primary ORB:
Default: First 30 minutes of regular trading hours (9:30-10:00 AM ET)
Configurable: 5, 15, 30, or 60-minute ranges
Precision: Optional lower timeframe (LTF) data for exact high/low detection
LTF Precision Mode:
When enabled, system uses 1-minute data to identify precise range boundaries, even on higher timeframe charts. This may improve accuracy of breakout detection.
Session ORBs (Optional):
Asian Session: Typically 00:00-01:00 UTC
London Session: Typically 08:00-09:00 UTC
NY Session: Typically 13:30-14:30 UTC
These provide additional reference levels for 24-hour markets.
2. INITIAL BALANCE (IB)
The Initial Balance concept extends ORB methodology:
Components:
A-Period: First 30 minutes (9:30-10:00)
B-Period: Second 30 minutes (10:00-10:30)
IB Range: Combined high/low of both periods
IB Extensions:
System projects multiples of IB range (0.5×, 1.0×, 1.5×, 2.0×) as potential targets and key reference levels.
Historical Context:
IB methodology was popularized by traders observing that the first hour often establishes the day's trading range. Extensions beyond IB may indicate trend day development.
3. BREAKOUT CONFIRMATION METHODS
The system offers three confirmation methods:
A. Close Beyond Range (Default):
Bullish: Close > ORB High
Bearish: Close < ORB Low
Most balanced approach - requires bar to close beyond level.
B. Wick Beyond Range:
Bullish: High > ORB High
Bearish: Low < ORB Low
Most sensitive - any touch triggers. May generate more signals but higher false breakout rate.
C. Body Beyond Range:
Bullish: Min(Open, Close) > ORB High
Bearish: Max(Open, Close) < ORB Low
Most conservative - entire candle body must be beyond range.
Volume Confirmation:
Optional requirement that breakout occurs on above-average volume (default 1.5× 20-bar average). May filter weak breakouts lacking institutional participation.
4. MACHINE LEARNING PROBABILITY SCORING
The system's key differentiator is ML-based breakout filtering using logistic regression.
How It Works:
Feature Extraction:
When breakout candidate detected, system calculates:
ORB Range / ATR (range size normalization)
Volume Ratio (current vs. average)
VWAP Distance × Direction (alignment)
Gap Size × Direction (overnight gap influence)
Bar Impulse (momentum strength)
Probability Calculation:
pContinue = Probability breakout continues
pFail = Probability breakout fails and reverses
Calculated via logistic regression:
P = 1 / (1 + e^(-z))
where z = β₀ + β₁×Feature₁ + β₂×Feature₂ + ...
Coefficient Examples (User Configurable):
pContinue Model:
Intercept: -0.20 (slight bearish bias)
ORB Range/ATR: +0.80 (larger ranges favored)
Volume Ratio: +0.60 (higher volume increases probability)
VWAP Alignment: +0.50 (aligned with VWAP helps)
pFail Model:
Intercept: -0.30 (assumes most breakouts valid)
Volume Ratio: -0.50 (low volume increases failure risk)
VWAP Alignment: -0.90 (breaking away from VWAP risky)
ML Gating:
When enabled, breakout only signaled if:
pContinue ≥ Minimum Threshold (default 55%)
pFail ≤ Maximum Threshold (default 35%)
This filtering aims to reduce false breakouts by requiring favorable probability scores.
Model Training:
Users should backtest and optimize coefficients for their specific instrument and timeframe. Default values are educational starting points, not guaranteed optimal parameters.
Educational Note: ML models assume past feature relationships continue into the future. Market conditions may change in ways not captured by historical data.
5. FAILED BREAKOUT DETECTION & REVERSAL TRADING
A unique feature is automatic detection of failed breakouts and generation of counter-trend reversal setups.
Detection Logic:
Failure Conditions:
For Bullish Breakout that fails:
- Initially broke above ORB High
- After N bars (default 3), price closes back inside range
- Must close below (ORB High - Buffer)
- Buffer = ATR × 0.1 (default)
For Bearish Breakout that fails:
- Initially broke below ORB Low
- After N bars, price closes back inside range
- Must close above (ORB Low + Buffer)
Automatic Reversal Entry:
When failure detected, system automatically:
Generates reversal entry at current close
Sets stop loss beyond recent extreme + small buffer
Projects 3 targets based on ORB range multiples
Target Calculations:
For failed bullish breakout (now SHORT):
Entry = Close (when failure confirmed)
Stop = Recent High + (ATR × 0.10)
T1 = ORB High - (ORB Range × 0.5) // 50% retracement
T2 = ORB High - (ORB Range × 1.0) // Full retracement
T3 = ORB High - (ORB Range × 1.5) // Beyond opposite boundary
Trade Lifecycle Management:
The system tracks reversal trades in real-time through multiple states:
State 0: No trade
State 1: Breakout active (monitoring for failure)
State 2: Breakout failed (not used currently)
State 3: Reversal entry taken
State 4: Target 1 hit
State 5: Target 2 hit
State 6: Target 3 hit
State 7: Stopped out
State 8: Complete
Real-Time Tracking:
MFE (Maximum Favorable Excursion): Best price achieved
MAE (Maximum Adverse Excursion): Worst price against position
Dynamic Lines & Labels: Visual updates as trade progresses
Color Coding: Green for hit targets, gray for stopped trades
Visual Feedback:
Entry line (solid when active, dotted when stopped)
Stop loss line (red dashed)
Target lines (green when hit, gray when stopped)
Labels update in real-time with status
This complete lifecycle tracking provides educational insight into trade development and risk/reward realization.
Educational Context: Failed breakouts are a recognized pattern in technical analysis. The theory is that trapped traders may need to exit, creating momentum in the opposite direction. However, not all failed breakouts result in profitable reversals.
6. EXTENSION TARGETS
System projects Fibonacci-based extension levels beyond ORB boundaries.
Bullish Extensions (Above ORB High):
1.272× (ORB High + ORB Range × 0.272)
1.5× (ORB High + ORB Range × 0.5)
1.618× (ORB High + ORB Range × 0.618)
2.0× (ORB High + ORB Range × 1.0)
2.618× (ORB High + ORB Range × 1.618)
3.0× (ORB High + ORB Range × 2.0)
Bearish Extensions (Below ORB Low):
Same multipliers applied below ORB Low
Visual Representation:
Dotted lines until reached
Solid lines after price touches level
Color coding (green for bullish, red for bearish)
These serve as potential profit targets and key reference levels.
7. DAY TYPE CLASSIFICATION
System attempts to classify trading day based on price movement relative to Initial Balance.
Classification Logic:
IB Extension = (Current Price - IB Boundary) / IB Range
Day Types:
Trend Day: Extension ≥ 1.5× IB Range
- Strong directional movement
- Price extends significantly beyond IB
Normal Day: Extension between 0.5× and 1.5×
- Moderate movement
- Some extension but not extreme
Rotation Day: Price stays within IB
- Range-bound conditions
- Limited directional conviction
Historical Context:
Day type classification comes from market profile analysis, suggesting different trading approaches for different conditions. However, classification is backward-looking and may change throughout the session.
8. VWAP INTEGRATION
Volume-Weighted Average Price included as institutional reference level.
Calculation:
VWAP = Σ(Typical Price × Volume) / Σ(Volume)
Typical Price = (High + Low + Close) / 3
Standard Deviation Bands:
Band 1: VWAP ± 1.0 σ
Band 2: VWAP ± 2.0 σ
Usage:
Alignment with VWAP may indicate institutional support
Distance from VWAP factored into ML probability scoring
Bands suggest potential overbought/oversold extremes
Note: VWAP is widely used by institutional traders as a benchmark, but this does not guarantee its predictive value.
9. GAP ANALYSIS
Tracks overnight gaps and fill statistics.
Gap Detection:
Gap Size = Open - Previous Close
Classification:
Gap Up: Gap > ATR × 0.1
Gap Down: Gap < -ATR × 0.1
No Gap: Otherwise
Gap Fill Tracking:
Monitors if price returns to previous close
Calculates fill rate over time
Displays previous close as reference level
Historical Context:
Market folklore suggests "gaps get filled," though statistical evidence varies by market and timeframe.
10. MOMENTUM CANDLE VISUALIZATION
Optional colored boxes around candles showing position relative to ORB.
Color Coding:
Blue: Inside ORB range
Green: Above ORB High (bullish momentum)
Red: Below ORB Low (bearish momentum)
Bright Green: Breakout bar
Orange: Failed breakout bar
Gray: Stopped out bar
Lime: Target hit bar
Provides quick visual context of price location and key events.
DISPLAY MODES
Three complexity levels to suit different user preferences:
SIMPLE MODE
Minimal display focusing on essentials:
✓ Primary ORB levels (High, Low, Mid)
✓ Basic breakout signals
✓ Essential dashboard metrics
✗ No session ORBs
✗ No IB analysis
✗ No extensions
Best for: Clean charts, beginners, focus on core ORB only
STANDARD MODE
Balanced feature set:
✓ Primary ORB levels
✓ Initial Balance with extensions
✓ Session ORBs (Asian, London, NY)
✓ VWAP with bands
✓ Breakout and reversal signals
✓ Gap analysis
✗ Detailed statistics
Best for: Most traders, good balance of information and clarity
ADVANCED MODE
Full feature set:
✓ All Standard features
✓ ORB extensions (1.272×, 1.5×, 1.618×, 2.0×, etc.)
✓ Complete statistics dashboard
✓ Detailed performance metrics
✓ All visual enhancements
Best for: Experienced users, research, full analysis
DASHBOARD INTERPRETATION
Main Dashboard Sections:
ORB Status:
Status: Complete / Building / Waiting
Range: Actual range size in price units
Trade State:
State: Current trade status (see 8 states above)
Vol: Volume confirmation (Confirmed / Low)
Targets (when reversal active):
T1, T2, T3: Hit / Pending / Stopped
Color: Green = hit, Gray = pending or stopped
ML Section (when enabled):
ML: ON Pass / ON Reject / OFF
pC/pF: Probability scores as percentages
Setup:
Action: LONG / SHORT / REVERSAL / FADE / WAIT
Grade: A+ to D based on confidence
Status: ACTIVE / STOPPED / T1 HIT / etc.
Conf: Confidence percentage
Context:
Bias: Overall market direction assessment
VWAP: Above / Below / At VWAP
Gap: Gap type and fill status
Statistics (Advanced Mode):
Bull WR: Bullish breakout win rate
Bear WR: Bearish breakout win rate
Rev WR: Reversal trade win rate
Rev Count: Total reversals taken
Narrative Dashboard:
Plain-language interpretation:
Phase: Building ORB / Trading Phase / Pre-market
Status: Current market state in plain English
ML: Probability scores
Setup: Trade recommendation with grade
All metrics based on historical simulation, not live trading results.
USAGE GUIDELINES - EDUCATIONAL EXAMPLES
Getting Started:
Step 1: Chart Setup
Add indicator to chart
Select appropriate timeframe (1-5 min recommended for ORB trading)
Choose display mode (start with Standard)
Step 2: Opening Range Formation
During first 30 minutes (9:30-10:00 ET default)
Watch ORB High/Low levels form
Note range size relative to ATR
Step 3: Breakout Monitoring
After ORB complete, watch for breakout candidates
Check ML scores if enabled
Verify volume confirmation
Step 4: Signal Evaluation
Consider confidence grade
Review trade state and targets
Evaluate risk/reward ratio
Interpreting ML Scores:
Example 1: High Probability Breakout
Breakout: Bullish
pContinue: 72%
pFail: 18%
ML Status: Pass
Grade: A
Interpretation:
- High continuation probability
- Low failure probability
- Passes ML filter
- May warrant consideration
Example 2: Rejected Breakout
Breakout: Bearish
pContinue: 48%
pFail: 52%
ML Status: Reject
Grade: D
Interpretation:
- Low continuation probability
- High failure probability
- ML filter blocks signal
- Small 'X' marker shows rejection
Note: ML scores are mathematical outputs based on historical data. They do not guarantee outcomes.
Reversal Trade Example:
Scenario:
9:45 AM: Bullish breakout above ORB High
9:46 AM: Price extends to +0.8× ORB range
9:48 AM: Price reverses, closes back below ORB High
9:49 AM: Failure confirmed (3 bars inside range)
System Response:
- Marks failed breakout with 'FAIL' label
- Generates SHORT reversal entry
- Sets stop above recent high
- Projects 3 targets
- Trade State → 3 (Reversal Active)
- Entry line and targets display
Potential Outcomes:
- Stop hit → State 7 (Stopped), lines gray out
- T1 hit → State 4, T1 line turns green
- T2 hit → State 5, T2 line turns green
- T3 hit → State 6, T3 line turns green
All tracked in real-time with visual updates.
Risk Management Considerations:
Position Sizing Example:
Account: $25,000
Risk per trade: 1% = $250
Stop distance: 1.5 ATR = $150 per share
Position size: $250 / $150 = 1.67 shares (round to 1)
Stop Loss Guidelines:
Breakout trades: ORB midpoint or opposite boundary
Reversal trades: System-provided stop (recent extreme + buffer)
Never widen system stops
Target Management:
Consider scaling out at T1, T2, T3
Trail stops after T1 reached
Full exit if stopped
These are educational examples, not recommendations. Users must develop their own risk management based on personal tolerance and account size.
OPTIMIZATION SUGGESTIONS
For Stock Indices (ES, NQ):
Suggested Settings:
ORB Timeframe: 30 minutes
Confirmation: Close
Volume Filter: ON (1.5×)
ML Filter: ON
Display Mode: Standard
Rationale:
30-min ORB standard for equity indices
Close confirmation balances speed and reliability
Volume important for institutional participation
ML helps filter noise
Historical Observation:
Indices often respect ORB levels during regular hours.
For Individual Stocks:
Suggested Settings:
ORB Timeframe: 5-15 minutes
Confirmation: Close or Body
Volume Filter: ON (1.8-2.0×)
RTH Only: ON
Failed Breakouts: ON
Rationale:
Shorter ORB may be appropriate for volatile stocks
Volume critical to filter low-liquidity moves
RTH avoids pre-market noise
Failed breakouts common in stocks
For Forex:
Suggested Settings:
ORB Timeframe: 60 minutes
Session ORBs: ON (Asian, London)
Volume Filter: OFF or low threshold
24-hour mode: ON
Rationale:
Forex trades 24 hours, need session awareness
Volume data less reliable in forex
Longer ORB for slower forex movement
For Crypto:
Suggested Settings:
ORB Timeframe: 30-60 minutes
Confirmation: Body (more conservative)
Volume Filter: ON (2.0×+)
Display Mode: Advanced
Rationale:
High volatility requires conservative confirmation
Volume crucial to distinguish real moves from noise
24-hour market benefits from multiple session ORBs
ML COEFFICIENT TUNING
Users can optimize ML model coefficients through backtesting.
Approach:
Data Collection: Review rejected breakouts - were they correct to reject?
Pattern Analysis: Which features correlate with success/failure?
Coefficient Adjustment: Increase weights for predictive features
Threshold Tuning: Adjust minimum pContinue and maximum pFail
Validation: Test on out-of-sample data
Example Optimization:
If finding:
High-volume breakouts consistently succeed
Low-volume breakouts often fail
Action:
Increase pCont w(Volume Ratio) from 0.60 to 0.80
Increase pFail w(Volume Ratio) magnitude (more negative)
If finding:
VWAP alignment highly predictive
Gap direction not helpful
Action:
Increase pCont w(VWAP Distance×Dir) from 0.50 to 0.70
Decrease pCont w(Gap×Dir) toward 0.0
Important: Optimization should be done on historical data and validated on out-of-sample periods. Overfitting to past data does not guarantee future performance.
STATISTICS & PERFORMANCE TRACKING
System maintains comprehensive statistics:
Breakout Statistics:
Total Days: Number of trading days analyzed
Bull Breakouts: Total bullish breakouts
Bull Wins: Breakouts that reached 2.0× extension
Bull Win Rate: Percentage that succeeded
Bear Breakouts: Total bearish breakouts
Bear Wins: Breakouts that reached 2.0× extension
Bear Win Rate: Percentage that succeeded
Reversal Statistics:
Reversals Taken: Total failed breakouts traded
T1 Hit: Number reaching first target
T2 Hit: Number reaching second target
T3 Hit: Number reaching third target
Stopped: Number stopped out
Reversal Win Rate: Percentage reaching at least T1
Day Type Statistics:
Trend Days: Days with 1.5×+ IB extension
Normal Days: Days with 0.5-1.5× extension
Rotation Days: Days staying within IB
Extension Statistics:
Average Extension: Mean extension level reached
Max Extension: Largest extension observed
Gap Statistics:
Total Gaps: Number of significant gaps
Gaps Filled: Number that filled during session
Gap Fill Rate: Percentage filled
Note: All statistics based on indicator's internal simulation logic, not actual trading results. Past statistics do not predict future outcomes.
ALERTS
Customizable alert system for key events:
Available Alerts:
Breakout Alert:
Trigger: Initial breakout above/below ORB
Message: Direction, price, volume status, ML scores, grade
Frequency: Once per bar
Failed Breakout Alert:
Trigger: Breakout failure detected
Message: Reversal setup with entry, stop, and 3 targets
Frequency: Once per bar
Extension Alert:
Trigger: Price reaches extension level
Message: Extension multiple and price level
Frequency: Once per bar per level
IB Break Alert:
Trigger: Price breaks Initial Balance
Message: Potential trend day warning
Frequency: Once per bar
Reversal Stopped Alert:
Trigger: Reversal trade hits stop loss
Message: Stop level and original entry
Frequency: Once per bar
Target Hit Alert:
Trigger: T1, T2, or T3 reached
Message: Which target and price level
Frequency: Once per bar
Users can enable/disable alerts individually based on preferences.
VISUAL CUSTOMIZATION
Extensive visual options:
Color Schemes:
All colors fully customizable:
ORB High, Low, Mid colors
Extension colors (bull/bear)
IB colors
VWAP colors
Momentum box colors
Session ORB colors
Display Options:
Line widths (1-5 pixels)
Box transparencies (50-95%)
Fill transparencies (80-98%)
Momentum box transparency
Label Behavior:
Label Modes:
All: Always show all labels
Adaptive: Fade labels far from price
Minimal: Only show labels very close to price
Label Proximity:
Adjustable threshold (1.0-5.0× ATR)
Labels beyond threshold fade or hide
Reduces clutter on wide-range charts
Gradient Fills:
Optional gradient zones between levels:
ORB High to Mid (bullish gradient)
ORB Mid to Low (bearish gradient)
Creates visual "heatmap" of tension
FREQUENTLY ASKED QUESTIONS
Q: What timeframe should I use?
A: ORB methodology is typically applied to intraday charts. Suggestions:
1-5 min: Active trading, multiple setups per day
5-15 min: Balanced view, clearer signals
15-30 min: Higher timeframe confirmation
The indicator works on any timeframe, but ORB is traditionally an intraday concept.
Q: Do I need the ML filter enabled?
A: This is a user choice:
ML Enabled:
Fewer signals
Potentially higher quality (filters low-probability)
Requires coefficient optimization
More complex
ML Disabled:
More signals
Simpler operation
Traditional ORB approach
May include lower-quality breakouts
Consider paper trading both approaches to determine preference.
Q: How should I interpret pContinue and pFail?
A: These are probability estimates from the logistic regression model:
pContinue 70% / pFail 25%: Model suggests favorable continuation odds
pContinue 45% / pFail 55%: Model suggests breakout likely to fail
pContinue 60% / pFail 35%: Borderline, depends on thresholds
Remember: These are mathematical outputs based on historical feature relationships. They are not certainties.
Q: Should I always take reversal trades?
A: Reversal trades are optional setups. Considerations:
Potential Advantages:
Trapped traders may need to exit
Clear stop loss levels
Defined targets
Potential Risks:
Counter-trend trading
Original breakout may resume
Requires quick reaction
Users should evaluate reversal setups like any other trade based on personal strategy and risk tolerance.
Q: What if ORB range is very small?
A: Small ranges may indicate:
Low volatility session opening
Potential for expansion later
Less reliable breakout levels
Considerations:
Larger ranges often more significant
Small ranges may need wider stops relative to range
ORB Range/ATR ratio helps normalize
The ML model includes this via the ORB Range/ATR feature.
Q: Can I use this on stocks, forex, crypto?
A: System is adaptable:
Stocks: Designed primarily for stock indices and equities. Use RTH mode.
Forex: Enable session ORBs. Volume filter less relevant. Adjust for 24-hour nature.
Crypto: Very volatile. Consider conservative confirmation method (Body). Higher volume thresholds.
Each market has unique characteristics. Extensive testing recommended.
Q: How do I optimize ML coefficients?
A: Systematic approach:
Collect data on 50-100+ breakouts
Note which succeeded/failed
Analyze feature values for each
Identify correlations
Adjust coefficients to emphasize predictive features
Validate on different time period
Iterate
Alternatively, use regression analysis on historical breakout data if you have programming skills.
Q: What does "Stopped Out" mean for reversals?
A: Reversal trade hit its stop loss:
Price moved against reversal position
Original breakout may have resumed
Trade closed at loss
Lines and labels gray out
Trade State → 7
This is part of normal trading - not all reversals succeed.
Q: Can I change ORB timeframe intraday?
A: ORB timeframe setting affects the next day's ORB. Current day's ORB remains fixed. To see different ORB sizes, you would need to change setting and wait for next session.
Q: Why do rejected breakouts show an 'X'?
A: When "Mark Rejected Breakout Candidates" enabled:
Small 'X' appears when ML filter rejects a breakout
Shows where system prevented a signal
Useful for model calibration
Helps evaluate if ML making good decisions
You can disable this marker if it creates clutter.
ADVANCED CONCEPTS
1. Adaptive vs. Static ORB:
Traditional ORB uses fixed time windows. This system adds adaptability through:
ML probability scoring (adapts to current conditions)
Multiple session ORBs (adapts to global markets)
Failed breakout detection (adapts when setup fails)
Real-time trade management (adapts as trade develops)
This creates a more dynamic approach than simple static levels.
2. Confluence Scoring:
System internally calculates confluence (agreement of factors):
Breakout direction
Volume confirmation
VWAP alignment
ML probability scores
Gap direction
Momentum strength
Higher confluence typically results in higher grade (A+, A, B+, etc.).
3. Trade State Machine:
The 8-state system provides complete trade lifecycle:
State 0: Waiting → No setup
State 1: Breakout → Monitoring for failure
State 2: Failed → (transition state)
State 3: Reversal Active → In counter-trend position
State 4: T1 Hit → First target reached
State 5: T2 Hit → Second target reached
State 6: T3 Hit → Third target reached (full success)
State 7: Stopped → Hit stop loss
State 8: Complete → Trade resolved
Each state has specific visual properties and logic.
4. Real-Time Performance Attribution:
MFE/MAE tracking provides insight:
Maximum Favorable Excursion (MFE):
Best price achieved during trade
Shows potential if optimal exit used
Educational metric for exit strategy analysis
Maximum Adverse Excursion (MAE):
Worst price against position
Shows drawdown during trade
Helps evaluate stop placement
These appear in Narrative Dashboard during active reversals.
THEORETICAL FOUNDATIONS
Why Opening Range Matters:
Several theories support ORB methodology:
1. Information Incorporation:
Opening period represents initial consensus on overnight news and pre-market sentiment. Range boundaries may reflect this information.
2. Order Flow:
Institutional traders often execute during opening period, establishing supply/demand zones.
3. Behavioral Finance:
Traders psychologically anchor to opening range levels. Self-fulfilling prophecy may strengthen these levels.
4. Market Microstructure:
Opening auction establishes price discovery. Breaks beyond may indicate new information or momentum.
Academic Note: While ORB is widely used, academic evidence on its effectiveness varies. Like all technical analysis, it should be evaluated empirically for each specific application.
Machine Learning in Trading:
This system uses supervised learning (logistic regression):
Advantages:
Interpretable (can see feature weights)
Fast calculation
Probabilistic output
Well-understood mathematically
Limitations:
Assumes linear relationships
Requires feature engineering
Needs periodic retraining
Not adaptive to regime changes automatically
More sophisticated ML (neural networks, ensemble methods) could potentially improve performance but at cost of interpretability and speed.
Failed Breakouts & Market Psychology:
Failed breakout trading exploits several concepts:
1. Stop Hunting:
Large players may push price to trigger stops, then reverse.
2. False Breakouts:
Insufficient conviction leads to failed breakout and quick reversal.
3. Trapped Traders:
Those who entered breakout now forced to exit, creating momentum opposite direction.
4. Mean Reversion:
After failed directional attempt, price may revert to range or beyond.
These are theoretical frameworks, not guaranteed patterns.
BEST PRACTICES - EDUCATIONAL SUGGESTIONS
1. Paper Trade Extensively:
Before live trading:
Test on historical data
Forward test in real-time (paper)
Evaluate statistics over 50+ occurrences
Understand system behavior in different conditions
2. Start with Simple Mode:
Initial learning:
Use Simple or Standard mode
Focus on primary ORB only
Master basic breakout interpretation
Add features incrementally
3. Optimize ML Coefficients:
If using ML filter:
Backtest on your specific instrument
Note which features predictive
Adjust coefficients systematically
Validate on out-of-sample data
Re-optimize periodically
4. Respect Risk Management:
Always:
Define maximum risk per trade (1-2% recommended)
Use system-provided stops
Size positions appropriately
Never override stops wider
Keep statistics of your actual trading
b]5. Understand Context:
Consider:
Is it a trending or ranging market?
What's the day type developing?
Is volume confirming moves?
Are you aligned with VWAP?
What's the overall market condition?
Context may inform which setups to emphasize.
6. Journal Results:
Track:
Which setup types work best for you
Your execution quality
Emotional responses to different scenarios
Missed opportunities and why
Losses and lessons
Systematic journaling improves over time.
FINAL EDUCATIONAL SUMMARY
ORB Fusion ML combines traditional Opening Range Breakout methodology with modern
enhancements:
✓ ML Probability Scoring: Filters breakouts using logistic regression
✓ Failed Breakout Detection: Automatic reversal trade generation
✓ Complete Trade Management: Real-time tracking with visual updates
✓ Multi-Session Support: Asian, London, NY ORBs for global markets
✓ Institutional Reference: VWAP and Initial Balance integration
✓ Comprehensive Statistics: Track performance across breakout types
✓ Full Customization: Three display modes, extensive visual options
✓ Educational Transparency: Dashboard shows all relevant metrics
This is an educational tool demonstrating advanced ORB concepts.
Critical Reminders:
The system:
✓ Identifies potential ORB breakout and reversal setups
✓ Provides ML-based probability estimates
✓ Tracks trades through complete lifecycle
✓ Offers comprehensive performance statistics
Users must understand:
✓ No system guarantees profitable results
✓ Past performance does not predict future results
✓ All indicators require proper risk management
✓ Paper trading essential before live trading
✓ Market conditions change unpredictably
✓ This is educational software, not financial advice
Success requires: Proper education, disciplined risk management, realistic expectations, personal responsibility for all trading decisions, and understanding that indicators are tools, not crystal balls.
For Educational Use Only - ORB Fusion ML Development Staff
⚠️ FINAL DISCLAIMER
This indicator and documentation are provided strictly for educational and informational purposes.
NOT FINANCIAL ADVICE: Nothing in this guide constitutes financial advice, investment advice, trading advice, or any recommendation to buy or sell any security or engage in any trading strategy.
NO GUARANTEES: No representation is made that any account will or is likely to achieve profits or losses similar to those shown. The statistics, probabilities, and examples are from historical backtesting and do not represent actual trading results.
SUBSTANTIAL RISK: Trading involves substantial risk of loss and is not suitable for every investor. The high degree of leverage can work against you as well as for you.
YOUR RESPONSIBILITY: You are solely responsible for your own trading decisions. You should conduct your own research, perform your own analysis, paper trade extensively, and consult with qualified financial advisors before making any trading decisions.
NO LIABILITY: The developers, contributors, and distributors of this indicator disclaim all liability for any losses or damages, direct or indirect, that may result from use of this indicator or reliance on any information provided.
PAPER TRADE FIRST: Users are strongly encouraged to thoroughly test this indicator in a paper trading environment before risking any real capital.
By using this indicator, you acknowledge that you have read this disclaimer, understand the substantial risks involved in trading, and agree that you are solely responsible for your own trading decisions and their outcomes.
Educational Software Only | Trade at Your Own Risk | Not Financial Advice
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
First presented FVG (w/stats) w/statistical hourly ranges & biasOverview
This indicator identifies the first Fair Value Gap (FVG) that forms during each hourly session and provides comprehensive statistical analysis based on 12 years of historical NASDAQ (NQ) data. It combines price action analysis with probability-based statistics to help traders make informed decisions.
⚠️ IMPORTANT - Compatibility
Market: This indicator is designed exclusively for NASDAQ futures (NQ/MNQ)
Timeframe: Statistical data is based on FVGs formed on the 5-minute timeframe
FVG Detection: Works on any timeframe, but use 5-minute for accuracy matching the statistical analysis
All hardcoded statistics are derived from 12 years of NQ historical data
What It Does
1. FVG Detection & Visualization
Automatically detects the first FVG (bullish or bearish) that forms each hour
Draws colored boxes around FVGs:
Blue boxes = Bullish FVG (gap up)
Red boxes = Bearish FVG (gap down)
FVG boxes extend to the end of the hour
Optional midpoint lines show the center of each FVG
Uses volume imbalance logic (outside prints) to refine FVG boundaries
2. Hourly Reference Lines
Vertical Delimiter: Marks the start of each hour
Hourly Open Line: Shows where the current hour opened
Expected Range Lines: Projects the anticipated high/low based on historical data
Choose between Mean (average) or Median (middle value) statistics
Upper range line (teal/green)
Lower range line (red)
All lines span exactly one hour from the moment it opens
Optional labels show price values at line ends
3. Real-Time Statistics Table
The table displays live data for the current hour only:
Hour: Current hour in 12-hour format (AM/PM)
FVG Status: Shows if a Bull FVG, Bear FVG, or no FVG has formed yet
Green background = Bullish FVG detected
Red background = Bearish FVG detected
1st 15min: Direction of the first 15 minutes (Bullish/Bearish/Neutral/Pending)
Continuation %: Historical probability that the hour continues in the first 15-minute direction
Color-coded: Green for bullish, red for bearish
Avg Range %: Expected percentage range for the current hour (based on 12-year mean)
FVG Effect %: Historical probability that FVG direction predicts hourly close direction
Shows BISI→Bull % for bullish FVGs
Shows SIBI→Bear % for bearish FVGs
Blank if no FVG has formed yet
Time Left: Countdown timer showing MM:SS remaining in the hour (updates in real-time)
Hourly Bias: Historical directional tendency (bullish % or bearish %)
H Open: Current hour's opening price
Exp Range: Projected price range (Low - High) based on historical average
Customization Options
Detection Settings:
Lower Timeframe Selection (15S, 1min, 5min) - controls FVG detection granularity
Display Settings:
FVG box colors (bullish/bearish)
Midpoint lines (show/hide, color, style)
Table Settings:
Position (9 locations: corners, edges, center)
Text size (Tiny, Small, Normal, Large)
Hourly Lines:
Toggle each line type on/off
Hour delimiter (color, width)
Open line (color, width, style)
Range lines (color, width, style)
Choose Mean or Median statistics for range calculation
Show/hide labels with customizable text size
How to Use
Apply to NQ futures chart (NQ1! or MNQ1!)
Set chart to 5-minute timeframe for optimal FVG detection matching the statistical data
Watch for the first FVG to form each hour
Reference the table for probability-based decision support:
High continuation % = strong directional bias
FVG Effect % shows reliability of the FVG signal
Time Left helps manage entries/exits within the hour
Use range lines as potential targets or reversal zones
Statistical Foundation
All statistics are derived from:
12 years of NASDAQ (NQ) historical data
Hourly analysis of FVG formation patterns
First 15-minute directional analysis
Mean and Median calculations for range expectations
Data encompasses 2,400+ samples per hour
Best Practices
✅ Use on NQ/MNQ futures only
✅ Best on 5-minute charts (matches statistical data)
✅ Combine FVG signals with continuation probabilities
✅ Use range lines as potential profit targets
✅ Watch the countdown timer for hour-end setups
❌ Do not use on other markets (statistics won't apply)
❌ Avoid using during low-liquidity hours (5PM ET has minimal data)
Technical Notes
Timezone: America/New_York (EST/EDT)
Weekend filtering: Automatically hides data during market closure
Updates in real-time on live bars
Maximum 500 boxes/lines for performance
FVG detection includes volume imbalance (body gap) refinement
Credits
Statistical analysis based on 12 years of NASDAQ historical data. FVG detection methodology follows ICT concepts with volume imbalance refinement.
Disclaimer: This indicator provides statistical analysis based on historical data. Past performance does not guarantee future results. Always use proper risk management.
Would you like me to adjust any section or add/remove anything?6-9 Session & Levels - Customizable Range Analysis Indicator
Description:
This indicator provides comprehensive session-based range analysis designed for intraday traders. It calculates and displays key levels based on a customizable session period (default 6:00-9:00 AM ET).
Core Features:
Sespastedthis is a summary for another indicator- i was hoping for something more like this in terms of content etc22:23Architected comprehensive indicator summary matching professional documentation style.The user wants me to rewrite the summary for their FVG indicator in a similar style to the example provided. The example is more structured, detailed, and professional. Let me create a comprehensive summary that follows that format:
Clear title
Description/Overview
Core Features (broken down into sections)
Input Settings Explained (detailed breakdown of all customization options)
How It Works section
Use Case
Note/Disclaimer
Let me make it thorough and match the style while being accurate to their indicator's functionality.Here's a detailed summary in that format:
Every Hour 1st FVG with Statistical Analysis - NASDAQ Hourly Trading Intelligence
Description:
This indicator identifies the first Fair Value Gap (FVG) that forms during each hourly session and provides comprehensive probability-based statistical analysis derived from 12 years of NASDAQ (NQ) historical data. It combines real-time FVG detection with hardcoded statistical probabilities to help intraday traders make informed decisions based on historical patterns and hourly price action dynamics.
IMPORTANT: This indicator is specifically calibrated for NASDAQ futures (NQ/MNQ) only. All statistical data is derived from 12 years of NQ historical analysis with FVGs detected on the 5-minute timeframe. Using this indicator on other markets will produce invalid statistical results.
Core Features:
FVG Detection & Visualization
Automatically detects and displays the first Fair Value Gap (bullish or bearish) that forms within each hourly session
Color-coded boxes mark FVG zones: Blue for bullish FVGs (gap up), Red for bearish FVGs (gap down)
FVG boxes extend precisely to the end of the hour boundary
Optional midpoint lines show the center point of each FVG
Uses volume imbalance logic (outside prints) to refine FVG boundaries beyond simple wick-to-wick gaps
Supports both chart timeframe detection and lower timeframe detection via request.security_lower_tf
Hourly Reference Lines
Vertical Hour Delimiter: Marks the exact start of each new hour with an extendable vertical line
Hourly Open Line: Displays the opening price of the current hour
Expected Range Lines: Projects anticipated high and low levels based on 12 years of statistical data
Choose between Mean (average) or Median (middle value) calculations
Upper range line shows expected high
Lower range line shows expected low
All lines span exactly one hour from open to close
Optional labels display exact price values at the end of each line
Real-Time Statistics Table
Displays comprehensive live data for the current hour only:
Hour: Current hour in 12-hour format (e.g., "9AM", "2PM")
FVG Status: Shows detection state with color coding
"None Yet" (white background) - No FVG detected
"Bull FVG" (green background) - Bullish FVG identified
"Bear FVG" (red background) - Bearish FVG identified
1st 15min: Direction of first 15 minutes (Bullish/Bearish/Neutral/Pending)
Continuation %: Historical probability that the hour closes in the direction of the first 15 minutes
Green background with up arrow (↑) for bullish continuation probability
Red background with down arrow (↓) for bearish continuation probability
Avg Range %: Expected percentage range for the current hour based on 12-year mean
FVG Effect %: Historical effectiveness of FVG directional prediction
Shows "BISI→Bull %" for bullish FVGs (gap up predicting bullish hourly close)
Shows "SIBI→Bear %" for bearish FVGs (gap down predicting bearish hourly close)
Displays blank if no FVG has formed yet
Time Left: Real-time countdown timer showing minutes and seconds remaining in the hour (MM:SS format)
Hourly Bias: Historical directional tendency showing bullish or bearish percentage bias
H Open: Current hour's opening price
Exp Range: Projected price range showing "Low - High" based on selected statistic (mean or median)
Input Settings Explained:
Detection Settings
Lower Timeframe: Select the base timeframe for FVG detection
Options: 15S (15 seconds), 1 (1 minute), 5 (5 minutes)
Recommendation: Use 5-minute to match the statistical data sample
The indicator uses this timeframe to scan for FVG patterns even when viewing higher timeframes
Display Settings
Bullish FVG Color: Set the color and transparency for bullish (upward) FVG boxes
Bearish FVG Color: Set the color and transparency for bearish (downward) FVG boxes
Show Midpoint Lines: Toggle horizontal lines at the center of each FVG box
Midpoint Line Color: Customize the midpoint line color
Midpoint Line Style: Choose between Solid, Dotted, or Dashed line styles
Table Settings
Table Position: Choose from 9 locations:
Top: Left, Center, Right
Middle: Left, Center, Right
Bottom: Left, Center, Right
Table Text Size: Select from Tiny, Small, Normal, or Large for readability on different screen sizes
Hourly Lines Settings
Show Hourly Lines: Master toggle for all hourly reference lines
Show Hour Delimiter: Toggle the vertical line marking each hour's start
Delimiter Color: Customize color and transparency
Delimiter Width: Set line thickness (1-5)
Show Hourly Open: Toggle the horizontal line at the hour's opening price
Open Line Color: Customize color
Open Line Width: Set thickness (1-5)
Open Line Style: Choose Solid, Dashed, or Dotted
Show Range Lines: Toggle the expected high/low projection lines
Range Statistic: Choose "Mean" (12-year average) or "Median" (12-year middle value)
Range High Color: Customize upper range line color and transparency
Range Low Color: Customize lower range line color and transparency
Range Line Width: Set thickness (1-5)
Range Line Style: Choose Solid, Dashed, or Dotted
Show Line Labels: Toggle price labels at the end of all horizontal lines
Label Text Size: Choose Tiny, Small, or Normal
How It Works:
FVG Detection Logic:
The indicator scans price action on the selected lower timeframe (default: 1-minute) looking for Fair Value Gaps using a 3-candle pattern:
Bullish FVG: Formed when candle 's high is below candle 's low, creating an upward gap
Bearish FVG: Formed when candle 's low is above candle 's high, creating a downward gap
The detection is refined using volume imbalance logic by checking for body gaps (outside prints) on both sides of the middle candle. This narrows the FVG zone to areas where bodies don't touch, indicating stronger imbalances.
Only the first FVG that forms during each hour is displayed. If a bullish FVG forms first, it takes priority. The FVG box is drawn from the formation time through to the end of the hour.
Statistical Analysis:
All probability statistics are hardcoded from 12 years (2,400+ samples per hour) of NASDAQ futures analysis:
First 15-Minute Direction: At 15 minutes into each hour, the indicator determines if price closed above, below, or equal to the hour's opening price
Continuation Probability: Historical analysis shows the likelihood that the hour closes in the same direction as the first 15 minutes
Example: If 9AM's first 15 minutes are bullish, there's a 60.1% chance the entire 9AM hour closes bullish (lowest continuation hour)
4PM shows the highest continuation at 86.1% for bullish first 15 minutes
FVG Effectiveness: Tracks how often the first FVG's direction correctly predicts the hourly close direction
BISI (Bullish Imbalance/Sell-side Inefficiency) → Bullish close probability
SIBI (Bearish Imbalance/Buy-side Inefficiency) → Bearish close probability
Range Expectations: Mean and median values represent typical price movement percentage for each hour
9AM and 10AM show the largest ranges (~0.6%)
5PM shows minimal range (~0.06%) due to low liquidity
Hourly Reference Lines:
When each new hour begins:
Vertical delimiter marks the hour's start
Hourly open line plots at the first bar's opening price
Range projection lines calculate expected high/low:
Upper Range = Hourly Open + (Range% / 100 × Hourly Open)
Lower Range = Hourly Open - (Range% / 100 × Hourly Open)
Lines extend exactly to the hour's end time
Labels appear at line endpoints showing exact prices
Real-Time Updates:
FVG Status: Updates immediately when the first FVG forms
First 15min Direction: Locked in at the 15-minute mark
Countdown Timer: Uses timenow to update every second
Table Statistics: Refresh on every bar close
Timezone Handling:
All times are in America/New_York (Eastern Time)
Automatically filters weekend periods (Saturday and Sunday before 6PM)
Hour detection accounts for daylight saving time changes
Use Cases:
Intraday Trading Strategy Development:
FVG Entry Signals: Use the first hourly FVG as a directional bias
Bullish FVG + High continuation % = Strong long setup
Bearish FVG + High continuation % = Strong short setup
First 15-Minute Breakout: Combine first 15-min direction with continuation probabilities
Wait for first 15 minutes to complete
If continuation % is above 70%, trade in that direction
Example: 4PM bullish first 15 min = 86.1% chance hour closes bullish
Range Targeting: Use expected high/low lines as profit targets or reversal zones
Price approaching mean high = potential resistance
Price approaching mean low = potential support
Compare mean vs median for different risk tolerance (median is more conservative)
Hour Selection: Focus trading on hours with:
High FVG effectiveness (11AM: 81.5% BISI→Bull)
High continuation rates (4PM: 86.1% bull continuation)
Avoid low-continuation hours like 9AM (60.1%)
Time Management: Use the countdown timer to:
Enter early in the hour when FVG forms
Exit before hour-end if no follow-through
Avoid late-hour entries with <15 minutes remaining
Statistical Edge Identification:
Compare current hour's FVG against historical effectiveness
Identify when first 15-min direction contradicts FVG direction (conflict = caution)
Use hourly bias to confirm or contradict FVG signals
Monitor if price stays within expected range or breaks out (outlier moves)
Risk Management:
Expected range lines provide logical stop-loss placement
FVG Effect % helps size positions (higher % = larger position)
Time Left countdown aids in time-based stop management
Avoid trading hours with neutral bias or low continuation rates
Statistical Foundation:
All embedded statistics are derived from:
12 years of NASDAQ futures (NQ) continuous contract data
5-minute timeframe FVG detection methodology
24 hours per day analysis (excluding weekends)
2,400+ samples per hour for robust statistical validity
America/New_York timezone for session alignment
Data includes:
Hourly range analysis (mean, median, standard deviation)
First 15-minute directional analysis
FVG formation frequency and effectiveness
Continuation probability matrices
Bullish/bearish bias percentages
Best Practices:
✅ Do:
Use exclusively on NASDAQ futures (NQ1! or MNQ1!)
Apply on 5-minute charts for optimal FVG detection matching statistical samples
Wait for first 15 minutes to complete before acting on continuation probabilities
Combine FVG signals with continuation % and FVG Effect % for confluence
Use expected range lines as initial profit targets
Monitor the countdown timer for time-based trade management
Focus on hours with high statistical edges (4PM, 11AM, 10AM)
❌ Don't:
Use on other markets (ES, RTY, YM, stocks, forex, crypto) - statistics will be invalid
Rely solely on FVG without confirming with continuation probabilities
Trade during low-liquidity hours (5PM shows only 0.06% average range)
Ignore the first 15-minute direction when it conflicts with FVG direction
Apply to timeframes significantly different from 5-minute for FVG detection
Use median range expectations aggressively (they're conservative)
Technical Implementation Notes:
Timezone: Fixed to America/New_York with automatic DST adjustment
Weekend Filtering: Automatically hides data Saturday and Sunday before 6PM ET
Performance: Maximum 500 boxes and 500 lines for optimal chart rendering
Update Frequency: Table updates on every bar close; timer updates every second using timenow
FVG Priority: Bullish FVGs take precedence when both form simultaneously
Lower Timeframe Detection: Uses request.security_lower_tf for accurate sub-chart-timeframe FVG detection
Precision: All price labels use format.mintick for appropriate decimal precision
Big thanks to @Trades-Dont-Lie for the FPFVG code in his excellent indicator that I've used here
History Trading SessionsThis indicator helps visually structure the trading day by highlighting custom time zones on the chart.
It is designed for historical analysis, trading discipline, and clear separation between analysis time, active trading, and no-trade periods.
Recommended to use on 4h and below time frames.
