Average Trading Range info box (today and historical)One small informational box, in the upper right of your chart to provide trading range information.
Line one (historical) tells you the trading range over a configurable period of time as a $ amount and as a %.
The second line (today) tells you where these values are today and the final line tells you as a %, where the values are today as a percentage of the configurable first line (14 days etc).
The third line changes color when you are 75% of the way to the historical value and red when you are at over 100% of the historical value.
Big DC scripts
Chu kỳ
Metaltek5_EMA'sThis M5_EMA's script plots the 1,2,3,5,13,50,200,800 EMA's in bright and bold contrasting colors for easy viewing. Each plot can be toggled on/off individually. It can also be run in both the lower indicator and upper overlay sections of the chart.
QTheory [SSMT]QTheory –
This indicator is built on Quarterly Theory (developed by Daye)
🔹 Quarterly Theory
Markets often unfold in repeating quarterly cycles (Q1–Q4) across multiple timeframes — yearly, monthly, weekly, daily, 90-minute, and even micro cycles. By dividing price action into these quarters, traders can better anticipate structural shifts, accumulation/distribution phases, and liquidity runs.
🔹 Sequential SMT (SSMT)
Sequential SMT extends standard SMT (Smart Money Technique) by comparing multiple assets (such as FX majors) to identify divergences across quarters.
🔹 Features of QTheory
Automatic detection of quarterly cycles across multiple timeframes.
Visual cycle boxes & customizable dividers.
Integrated SSMT signals with divergence line visualization.
DFR (Defining Range) with Fibonacci levels.
Support for up to 5 comparison assets, with inversion options.
Auto-cycle selection for seamless multi-timeframe adaptation.
Extensive customization for colors, opacity, and signal display.
🔹 How it works
QTheory divides price data into consistent “quarters” across multiple timeframes. Within each cycle, it tracks highs, lows, and divergences, then overlays this information as boxes, dividers, and optional signals on your chart. Traders can use these visual cues to better align entries and exits with institutional market behavior patterns.
🔹 How to use it
Enable the desired cycle type (e.g., weekly, daily, 90-minute) from the settings.
Toggle boxes, dividers, and signals depending on your trading style.
Use SSMT divergences and DFR Fibs to anticipate a reversal
Compare against other assets (e.g., DXY or correlated pairs) to refine confluence.
Enable "Show Weekends" for Crypto.
⚠️ Disclaimer: This tool is for educational purposes only. It does not constitute financial advice. Always perform your own analysis and risk management.
Time Window Highlight📌 What this script does
Time Window Highlight highlights a specific intraday time window directly on your chart using a background color and optional vertical lines.
It was built for traders who focus on behavior around the US market open, where volatility, positioning, and false initial moves often occur.
The script does not generate signals.
It provides visual structure and timing clarity.
⸻
⏰ Default Use Case
By default, the window is set to:
• 15:40 – 16:00 (Europe/Rome time)
This time range is commonly used to observe:
• post-open fake moves
• early reversals
• stabilization after initial volatility
All times are fully customizable.
⸻
🎛️ Features
• ✅ Custom start & end time (hours and minutes)
• ✅ Background highlight for the active window
• ✅ Optional vertical start & end lines
• ✅ Option to include the full end candle
• ✅ Option to shift the end line to the end of the end candle
• ✅ Optional weekday filter (Monday–Friday only)
• ✅ Clean chart logic (historical background, live-day focus)
⸻
🧠 Designed Philosophy
This script was intentionally built to:
• avoid repainting
• avoid signals or bias
• avoid over-engineering
It is meant to support discretion, not replace it.
Use it to:
• stay patient outside your key window
• focus only when your session begins
• avoid forcing trades at random times
⸻
⚠️ Important Notes
• The script uses the chart’s timezone
→ Make sure your chart is set to Europe/Rome (or your preferred timezone).
• Background coloring works on full candles only (TradingView limitation).
• Vertical lines are time-anchored and align precisely with the session window.
⸻
🧪 Recommended Timeframes
• 1m / 2m / 5m (intraday)
• Not intended for daily or higher timeframes
⸻
❗ Disclaimer
This script is a visual aid only.
It does not provide buy or sell signals and should be used as part of a broader trading plan.
Key High/Low liquidity @sheershThe Key High/Low ICT by @sheersh169sharma indicator is designed to identify key liquidity levels across multiple timeframes and custom trading sessions. It provides precise visualization of historical highs and lows to assist in technical analysis.
## Key Features
* Multi-Timeframe Support: Automatically plots Previous Day, Week, 4-Hour, and 1-Hour levels.
* Custom Sessions: Supports up to 6 independently configurable time windows.
* Precise Anchoring: Lines originate exactly from the time the high or low formed.
* Mitigation Logic: Options to terminate lines upon price interaction or extend them indefinitely.
## Configuration Guide
### Standard Timeframes
Users can toggle and customize the following levels:
* Previous Day High/Low
* Previous Week High/Low
* Previous 4-Hour High/Low
* Previous 1-Hour High/Low
Each level allows for customization of visibility, color, and line style (Solid, Dashed, Dotted).
### Custom Sessions
The indicator supports 6 distinct custom sessions, ideal for defining specific market hours (e.g., Asia, London, New York).
Setup Instructions:
1. Navigate to the desired Session group in settings (e.g., Session 1).
2. Enable the session.
3. Define the time range in HHMM-HHMM format (e.g., 0930-1600).
4. Assign custom labels for identification.
5. Select line colors and styles.
### Extension Logic
The "Extend until Mitigated Only" setting controls how lines are drawn:
* Disabled (Default): Lines extend from the custom timeframe to the current chart bar.
* Enabled: Lines terminate strictly at the point where price touches the level.
### Visual Settings
* Line Width: Adjusts the thickness of all indicator lines globally.
* Labels: Text labels are positioned to the right of the lines to maintain chart clarity.
BTC Halving VWAP [Cycle Analysis]█ OVERVIEW
This indicator plots Anchored Volume Weighted Average Prices (VWAPs) from each Bitcoin halving date, revealing the "fair value" of each market cycle.
The key insight: When price closes below the current cycle's VWAP on the monthly chart (after 1+ year into the cycle), it historically signals the end of the bull market and continuation toward the previous halving's VWAP.
█ HALVING DATES
• H1: November 28, 2012 (Block 210,000)
• H2: July 9, 2016 (Block 420,000)
• H3: May 11, 2020 (Block 630,000)
• H4: April 19, 2024 (Block 840,000)
█ FEATURES
◽ Anchored VWAPs — VWAP lines calculated from each halving date
◽ Consolidation Bands — Adjustable percentage bands around each VWAP (default ±15%)
◽ Cycle Top Detection — Tracks the highest high before VWAP breakdown
◽ Breakdown Signals — Visual markers when price breaks below cycle VWAP (bearish confirmation)
◽ Interactive Dashboard — Shows cycle progress, VWAP levels, and historical comparison
◽ Alerts — Configurable alerts for VWAP crossovers and breakdowns
█ HOW TO USE
1. Apply to BTCUSD on the Monthly timeframe for best results
2. Watch the H4 VWAP (gold line) — this is the current cycle's fair value
3. When price is ABOVE the VWAP → Bullish bias
4. When price is BELOW the VWAP → Bearish bias, expect move to previous cycle VWAP
5. The ▼ signal marks confirmed cycle tops (VWAP breakdown after 1+ year)
█ DASHBOARD GUIDE
• Price — Current price and gain from halving
• Day — Days since halving and cycle progress %
• VWAP Levels — Current VWAP values with status (ABOVE/BELOW/CONSOL)
• Cycle Tops — Historical days to cycle top for H2 and H3
• Next Halving — Estimated date and countdown
█ SETTINGS
Display:
• Toggle dashboard, consolidation bands, vertical lines, cycle tops, breakdown signals
VWAPs:
• Show/hide individual halving VWAPs (H1-H4)
Settings:
• Dashboard text size
• Consolidation band percentage
• Cycle top label size
█ ALERTS
• VWAP Breakdown — Price breaks below any halving VWAP
• VWAP Reclaim — Price reclaims a halving VWAP
• Consolidation Zone — Price enters consolidation around VWAP
█ NOTES
• Best used on Monthly (1M) timeframe for cycle analysis
• Weekly timeframe also works for more granular view
• H1 VWAP disabled by default (requires data from 2012)
• Cycle top locks when price closes below VWAP after 365+ days into the cycle
Smart S/R Levels [Stansbooth]
Introducing the Ultimate Support & Resistance Indicator for Live Market Analysis!
Unlock the power of real-time market insights with our cutting-edge Support & Resistance Indicator! Designed for traders who demand precision and clarity, this tool automatically plots key support and resistance levels on your chart, ensuring you never miss crucial price action points.
🚀 Key Features:
Real-Time Tracking: Accurately identifies and updates support & resistance levels as market conditions evolve.
Easy-to-Use: Simple integration into your TradingView charts with no complicated setup.
Customizable Alerts : Get notified when the price approaches key levels for actionable trading opportunities.
Accurate & Reliable : Built using advanced algorithms for pinpoint precision in real-time market conditions.
Time-Saving: Automatically draws support and resistance lines, so you can focus on strategy and execution.
Whether you’re a day trader, swing trader, or a long-term investor, this indicator is designed to give you the edge by highlighting the most important levels for price reversals and breakouts.
Start trading smarter today with the Support & Resistance Indicator —your ultimate market companion!
IDX_BBCAPT Bank Central Asia Tbk (BCA) is the largest private bank in Indonesia by assets and market value, headquartered in Jakarta. Founded on February 21, 1957, BCA offers a comprehensive range of financial services to individuals, SMEs, and corporations.
Trend Warning / Direction (EMA20/50)This indicator visualizes trend changes and consolidation phases using the 20 EMA and 50 EMA.
🔹 Trend Signals
• Green triangle (▲): EMA 20 crosses above EMA 50 → bullish trend signal
• Red triangle (▼): EMA 20 crosses below EMA 50 → bearish trend signal
• Crosses are confirmed on candle close to avoid false signals.
🔹 EMA Distance Warning
The indicator highlights low-momentum / squeeze zones when the distance between EMA 20 and EMA 50 falls below a configurable threshold.
• Yellow triangle with number:
Displays the current EMA distance in percent (without the % symbol).
• The warning threshold can be configured individually for each timeframe:
• 1m, 5m, 15m, 30m
• 1h, 4h, 8h
• 1D, 1W
• The active chart timeframe automatically determines which threshold is applied.
🔹 Customization
• Enable or disable EMA distance warnings via settings
• Adjust distance thresholds per timeframe
• Option to limit warning labels to one per bar
• Works on all markets and timeframes
🔹 Use Cases
• Trend identification
• Momentum exhaustion and consolidation detection
• Early warning before potential breakouts
• Trade confirmation in combination with other indicators
This indicator is non-repainting, lightweight, and designed for clean, actionable chart signals.
20-50 EMA Bear / Bull TrendThis indicator identifies uptrends and downtrends based on confirmed EMA crossovers between the 20 EMA and 50 EMA, using candle close confirmation only to avoid false intrabar signals.
• Green up arrow (↑): EMA 20 crosses above EMA 50 → bullish signal / start of an uptrend
• Red down arrow (↓): EMA 20 crosses below EMA 50 → bearish signal / start of a downtrend
The signals are plotted directly on the chart and can be used to create separate TradingView alerts for bullish and bearish crosses.
Key features:
• Visual identification of uptrends and downtrends
• EMA 20 & EMA 50 plotted on the chart
• Signals confirmed on candle close (non-repainting)
• Clear arrow-based signals instead of text labels
• Selectable alert conditions for bullish and bearish crosses
• Optional support for “Any alert() function call”
This indicator works on all timeframes and is suitable for trend detection, momentum shifts, and trade confirmation.
ZenAlgo - Coin XA multi input Z Score framework that compares the behavior of a selected symbol against several market wide aggregates: total crypto market metrics, alternative asset baskets, stablecoin dominance, Bitcoin, and risk composites. The script processes each data stream into comparable normalized values, evaluates their relationships, and derives a set of bias states, alerts, and real time conditions.
Data Preparation and Normalization
The indicator starts by gathering multiple reference series:
The chart ticker.
A basket representing non Bitcoin crypto assets.
Bitcoin market data.
Several total market variations (full, without Bitcoin, and additional categories).
A stablecoin dominance series.
A macro risk composite.
A daily anchored average used for context.
Each series is transformed into a normalized value using a lookback window. This produces multiple comparable Z Scores that reflect how far each series currently sits from its typical range. Smoothing is optionally applied to macro based values to reduce noise. These normalized values allow consistent comparisons across unrelated instruments.
This works because Z Score based normalization removes scale differences and makes directional deviations directly comparable across many independent metrics, which is necessary when the script later evaluates their relationships.
Cross and Momentum Detection
The script then evaluates structural interactions between the normalized series:
Whether one group rises above or falls below another.
Whether any of the series crosses over or under another.
Whether each series is currently advancing or declining.
Whether price is above or below the daily anchored average.
Whether stablecoin dominance is rising or falling.
Whether a sharp directional change occurs within a single bar.
Whether a multi threshold movement happens within a defined number of bars.
These checks capture relative strength shifts across the market. For example, an increase in the ticker combined with a decline in dominance suggests capital rotation toward the ticker, while the opposite suggests defensive flows. Using normalized changes allows these comparisons to be scale independent.
Combined Bias Logic
The indicator then evaluates a hierarchy of conditions that combine normalized relationships, momentum, and sharp movement checks. Each condition corresponds to a specific market state. The script tests the conditions in a defined order because later conditions depend on earlier structural checks.
Examples of combined evaluations include:
Cases where the ticker and alternative asset basket rise together while dominance declines.
Cases where both the ticker and alternatives fall together under a rising dominance series.
Conditions where several aggregates cross above or below dominance simultaneously.
Cases where multiple aggregates show coordinated sharp rises or sharp declines.
Situations where stablecoin dominance rises during weakness of other groups.
Situations where stablecoins fall while the ticker strengthens.
Conditions where the ticker rapidly moves through several thresholds in a short period.
The script assigns a bias label that corresponds to the earliest satisfied condition. This design ensures that highly distinctive and rare states take priority over broader or more common states. The reasoning behind this is that specific coordinated market moves provide clearer view than general divergence or simple momentum alone.
Crash and Pump Amplification
The script includes a section that detects extreme scenarios by combining several coordinated factors:
Very negative or very positive normalized values across multiple aggregates.
Sharp bar by bar declines or rises across key series.
Simultaneous movement in the risk composite and dominance.
These checks amplify certain bias states when market conditions show synchronized extreme movement. This provides additional clarity when multiple parts of the market behave in the same direction beyond typical deviation. The logic relies only on the relationships of the normalized values and their changes.
Fast Movement Detection
Two additional mechanisms evaluate movements over a short multi bar window.
A fast ticker move is detected when the current normalized ticker value differs from one several bars ago by multiple threshold increments.
A fast stablecoin rise or fall is detected using a step based method. The script checks for progression through sequential levels across the window while verifying whether the ticker moves in agreement or disagreement with the direction.
These mechanisms are intended to identify sudden acceleration or deceleration that standard normalized changes may not fully capture.
Season Scale
The script calculates a quantitative scale from minus 100 to plus 100 by evaluating several binary conditions:
Whether the ticker is above or below the alternative basket.
Whether the alternative basket is above or below dominance.
Whether the ticker and alternative basket are rising or falling.
Whether dominance is rising or falling.
Optionally whether price is above or below the anchored average.
Each condition contributes positively or negatively. The weighted combination produces the season value which is rounded. The naming of the state (Full Bull, Neutral, Full Bear etc.) is derived from where the score falls on the range.
This works because combining several directional tests across related groups provides a compressed singular measure of market structure.
Divergence Detection
The script includes divergence logic for Bitcoin, the alternative asset basket, and the chart ticker. It evaluates pivot highs and lows in price and compares them with pivot highs and lows in their respective normalized values. The script checks for pairs of pivot points where price moves in one direction while the normalized oscillator moves in the opposite. Both regular and hidden forms are evaluated.
This works because divergences highlight points where price and its normalized deviation disagree which often marks a structural imbalance.
Table Output
If enabled, the indicator displays a table showing the current normalized values of all monitored series along with color backgrounds reflecting structural relationships identified earlier. This supports interpretation without opening additional charts.
Visual Lines and Background
The script draws horizontal reference lines for several normalized levels using a fading mechanism if ghost mode is enabled. The background color changes according to the main season logic and intensifies with market wide deviations. Optional pulse effects are triggered when the bias state changes.
This works because visual context helps understand how extreme the current market state is relative to its typical historical range.
Alerts
The indicator creates alerts for all important structural states:
Bias state changes.
Fast ticker moves.
Fast stablecoin rises or falls.
Divergence based triggers.
Cross conditions corresponding to notable structural transitions.
These alerts correspond exactly to the logical conditions already described.
Added Value Compared to Free Alternatives
It evaluates many separate market wide aggregates simultaneously rather than relying on a single comparison.
It uses a consistent normalized framework so unrelated metrics become comparable.
It identifies multi series coordinated shifts which many simpler indicators cannot detect.
It provides a full deterministic bias state hierarchy that removes interpretation ambiguity.
It includes fast movement evaluation through multi level and multi bar logic.
It combines multiple categories of divergences with normalized values rather than only price based oscillators.
It provides a unified season value derived from several independent binary conditions.
Limitations and Situations Where It May Fall Short
Normalized values depend on the chosen lookback window and may behave differently under unusual volatility regimes.
If reference data feeds are incomplete or delayed the relationships may briefly reflect distorted values.
Extreme single bar events can cause temporary exaggeration of normalized values before stabilization.
Divergence detection depends on identifying pivots which may repaint until the pivot is confirmed.
Bias states rely on hierarchical evaluation so rare but extreme conditions will override more common states by design.
Sudden changes in stablecoin supply or methodology on the data source may influence stable dominance readings.
How to Interpret the Values
Positive normalized values indicate movement above the typical range while negative values indicate movement below the typical range.
The relationships between the ticker, the alternative asset basket, dominance, and the risk composite define the structural meaning of each bias.
The season value near plus 100 means most bull related conditions are simultaneously satisfied while near minus 100 means most bear related conditions are satisfied.
Sharp rise or fall conditions indicate abrupt movement beyond the usual deviation.
Cross conditions indicate structural transitions such as the ticker moving above or below another aggregate.
Divergences indicate inconsistency between price action and normalized deviation.
Best Practices for Practical Use
Use the bias state as a structural context rather than a direct entry or exit trigger.
Observe whether multiple aggregates align in the same direction since the script is designed around confirming coordinated behavior.
Combine the season value with the main bias state to evaluate whether short term view agree with broader conditions.
Use fast movement alerts for monitoring sudden volatility or intraday acceleration.
Use divergence conditions to identify potential exhaustion points when the main bias does not align with price behavior.
Reference the table and background colors for a quick visual overview of how several groups relate in the current moment.
ADX&DIThis is an enhanced version of the classic ADX and Directional Movement Index (DMI). It is designed to filter out ranging markets and visually highlight trend strength.
Key Features:
Dual Threshold System:
Level 1 (Default 20): Signals the start of a trend. The background fill appears with high transparency.
Level 2 (Default 25): Signals a strong trend. The background fill becomes more opaque/solid to indicate momentum.
Visual Clarity: The area between DI+ and DI- is only filled when the ADX is above your defined thresholds. This helps you ignore noise in low-volatility environments.
Clean Settings: The logic is optimized so you can easily adjust colors and transparency directly in the "Style" tab without cluttered input menus.
HMA1//@version=5
strategy("黄金 HMA + SuperTrend 趋势增强策略", overlay=true, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=10)
// --- 1. 输入参数 ---
// HMA 参数
hmaLen = input.int(55, "HMA 长度", minval=1, group="HMA 设置")
// SuperTrend 参数
stFactor = input.float(3.0, "SuperTrend 乘数", step=0.1, group="SuperTrend 设置")
stPeriod = input.int(10, "SuperTrend ATR 周期", group="SuperTrend 设置")
// 离场设置
useAtrSl = input.bool(true, "启用 ATR 动态止损", group="风险管理")
atrSlMult = input.float(2.0, "止损 ATR 倍数", step=0.1, group="风险管理")
// --- 2. 指标计算 ---
// 计算 HMA
hmaValue = ta.hma(close, hmaLen)
// 计算 SuperTrend
= ta.supertrend(stFactor, stPeriod)
// 计算 ATR（用于止损）
atr = ta.atr(14)
// --- 3. 绘图 ---
plot(hmaValue, "HMA 趋势线", color=hmaValue > hmaValue ? color.green : color.red, linewidth=2)
plot(stValue, "SuperTrend 线", color=stDirection < 0 ? color.new(color.teal, 0) : color.new(color.maroon, 0), linewidth=2)
// --- 4. 交易逻辑 ---
// 做多条件：
// 1. 价格在 HMA 之上 且 HMA 正在向上拐头
// 2. SuperTrend 变为看涨方向 (stDirection < 0)
longCondition = close > hmaValue and hmaValue > hmaValue and stDirection < 0
// 做空条件：
// 1. 价格在 HMA 之下 且 HMA 正在向下拐头
// 2. SuperTrend 变为看跌方向 (stDirection > 0)
shortCondition = close < hmaValue and hmaValue < hmaValue and stDirection > 0
// --- 5. 执行与止损逻辑 ---
var float longStop = na
var float shortStop = na
// 入场逻辑
if (longCondition)
longStop := close - (atr * atrSlMult)
strategy.entry("Long", strategy.long, comment="HMA+ST 多")
if (shortCondition)
shortStop := close + (atr * atrSlMult)
strategy.entry("Short", strategy.short, comment="HMA+ST 空")
// 离场逻辑：当 SuperTrend 反转或触及 ATR 止损时离场
if (strategy.position_size > 0)
strategy.exit("Exit Long", "Long", stop=longStop, limit=na, when=stDirection > 0, comment="多单离场")
if (strategy.position_size < 0)
strategy.exit("Exit Short", "Short", stop=shortStop, limit=na, when=stDirection < 0, comment="空单离场")
// 填充背景色以示趋势
fill(plot(stValue), plot(open > close ? open : close), color = stDirection < 0 ? color.new(color.green, 90) : color.new(color.red, 90))
ETHThe Indicator is using the combination of below indicators:
Relative Strength Index (RSI): A momentum oscillator used to identify overbought (above 70) or oversold (below 30) conditions, which can signal potential price reversals.
Moving Averages (MA & EMA): These smooth out price data to help identify the direction of the overall trend. Crossovers between different period MAs (e.g., a short-term MA crossing above a long-term MA) can generate buy or sell signals.
Moving Average Convergence Divergence (MACD): A trend-following momentum indicator that shows the relationship between two moving averages. A bullish crossover (MACD line above signal line) suggests upward momentum, while a bearish crossover (MACD line below signal line) indicates downward momentum.
Bollinger Bands: This volatility indicator consists of a middle band (moving average) and two outer bands based on standard deviation. Price touching the upper band may signal overbought conditions, while touching the lower band may signal oversold conditions or a potential bounce.
Volume Indicators (e.g., On-Balance Volume - OBV): Volume confirms the strength of a price movement. A price increase with high volume suggests strong buying pressure, validating the trend.
Ethereum Long/Short Ratio: This sentiment indicator compares the number of traders holding long positions versus short positions. A high ratio might indicate excessive bullish sentiment, potentially preceding a market correction.
Goldbach Timing Model This indicator is designed as a simple visual framework rather than a rigid signal system. It highlights time-based structure and key alignment zones to help identify when price behavior is more likely to be active or responsive. The logic is intentionally flexible, allowing the user to apply their own discretion instead of relying on strict conditions. Its primary value is visual clarity and context, not automatic entries or exits.
GS Tactical Overlay (SMC + Squeeze)designed to sit atop the 6 pillar commander. it will tell you signs for puts and calls
Navidad SharksThis indicator is NOT a signal system.
It is not designed for blind BUY/SELL execution. If you trade it like signals, you will most likely lose consistency.
What is it then?
It is a visual execution tool built around the Sharks Value Zones methodology.
The indicator helps you:
Define a value range
Wait for a valid breakout
Visualize risk (STOP) and reward (1:1) in a structured way
The indicator does not make decisions for you — it gives structure.
The trader still decides.
⚠️ Important for new users
This is NOT an automated signal tool
It only makes sense if you learn the Sharks Value Zones system inside the Sharks community
Entering trades just because a BUY or SELL label appears is not the method
This indicator provides levels and structure, not trade instructions.
🦈 Sharks Mindset
Professional traders don’t chase signals.
They repeat clear structures, disciplined execution, and controlled risk.
This indicator exists to:
bring order to your chart
remove emotional guessing
help you execute with consistency
✅ What the indicator draws
Base range / Value Zone based on the selected market session
Breakout direction (BUY or SELL) after the range
STOP zone (risk) and 1:1 target zone (reward)
Additional markers:
80% TP → price reached 80% of the target
TP ✅ / STOP ❌ → trade resolution
🧩 Inputs explained (simple)
Market
Select the session you want to trade (NY, Europe, Crypto, etc.).
This defines when the value range is calculated.
Anchor boxes from range start (bars)
How many candles the boxes extend to the right.
Higher value = longer visual boxes.
BUY/SELL label offset
Moves the BUY/SELL label left or right (visual only).
TP/STOP label offset
Moves TP / STOP / 80% labels (visual only).
ENTRY TICKS (number of breakout ticks)
Filters weak breakouts.
0 = instant breakout (more signals, more sensitivity)
3–5 ticks recommended for Forex
Indices and crypto may require higher values depending on volatility
Use 2nd opportunity
If the first trade hits STOP, the system may allow a second structured attempt on the opposite break (if enabled).
This is part of the Sharks methodology, not revenge trading.
🧠 How to use it correctly
Learn the Sharks Value Zones system
Use the indicator as a map, not a signal
Combine structure + context + risk management
==========================================
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.
Monthly High/Low - [JTCAPITAL]Monthly High/Low Probability Table - is a modified way to use historical monthly high and low tracking combined with probabilistic analysis for bullish and bearish months to detect potential patterns in monthly price behavior.
The indicator works by calculating in the following steps:
Variable Declaration
Persistent variables ( var ) are used to store monthly highs, lows, open and close prices, and the days on which highs and lows occurred. Separate arrays track bullish and bearish month statistics for highs and lows ( highBull, lowBull, highBear, lowBear ). Counters ( bullCount, bearCount ) store the number of bullish and bearish months recorded.
New Month Detection
The script detects the start of a new month by comparing the current bar’s month to the previous bar’s month. If a new month is detected, the script proceeds to update statistics for the previous month.
Monthly High/Low Recording and Classification
At the start of each new month, the previous month’s high, low, open, and close are evaluated:
If monthClose > monthOpen , the month is classified as bullish.
If monthClose < monthOpen , the month is classified as bearish.
The arrays ( highBull, lowBull, highBear, lowBear ) are updated at the respective high and low days of the month by incrementing counts, which allows the script to keep track of the frequency of monthly highs and lows occurring on specific days.
Monthly High/Low Tracking
During the month, the script continuously updates monthHigh and monthLow if the current bar’s high exceeds monthHigh or the low is below monthLow . The days on which these highs and lows occur are recorded ( highDay and lowDay ). The monthClose variable is continuously updated to the latest closing price.
Probability Calculation
Once monthly data is accumulated, the script calculates probabilities for each day of the month:
bullHighProb and bullLowProb represent the probability (in percentage) that a bullish month’s high or low occurred on a given day.
bearHighProb and bearLowProb represent the probability for bearish months.
These probabilities are calculated by dividing the count of high or low occurrences on each day by the total number of bullish or bearish months, then multiplying by 100. This probabilistic approach allows traders to see recurring patterns for highs and lows across multiple months.
Gradient Coloring Function
The helper function gradientRelative computes a color gradient between lowColor and highColor based on the relative probability value. Higher probabilities are colored closer to highColor , and lower probabilities closer to lowColor . This visual representation allows for quick identification of the most probable days for highs and lows in bullish or bearish months.
Dynamic Updates
As new bars are processed, the table is updated in real-time with new probabilities reflecting the most recent month’s data. This dynamic behavior ensures that the table remains accurate and responsive to the latest market information.
Buy and Sell Conditions:
This indicator does not provide direct buy or sell signals. Instead, it provides probabilistic information about historical patterns for bullish and bearish months. Traders can use the table to:
Identify days in the month where highs or lows are statistically more likely to occur.
Combine with other trend-following or reversal strategies to optimize entry and exit points.
For example, if a trader notices that bullish month highs frequently occur around day 15, they may plan trades around that period when other indicators align.
Features and Parameters:
Dynamic Probability Table : Updates in real-time as new monthly data becomes available.
Historical Pattern Tracking : Maintains arrays for highs and lows in bullish and bearish months.
Gradient Visualization : Uses color interpolation to quickly highlight higher probability days.
Specifications:
Monthly High/Low Tracking
Tracks the highest and lowest prices within each month. This is the foundation of the probability calculations. It allows traders to understand when significant price events historically occur.
Bullish/Bearish Month Classification
Each month is classified based on the relationship between monthClose and monthOpen . This provides context for the high/low occurrences: whether they happened in bullish or bearish months.
High/Low Occurrence Arrays
Four arrays ( highBull, lowBull, highBear, lowBear ) store the count of high and low occurrences for each day of the month. These arrays are the core of the statistical analysis.
Probability Calculation
Divides the count of occurrences for each day by the total number of months in that category (bullish/bearish). Multiplying by 100 converts this to a percentage probability, giving traders a numerical sense of recurrence.
Real-Time Updates
The table and probabilities are recalculated and refreshed with each new bar. This ensures that traders have the most current information available without manual recalculation.
User-Centric Visualization
By showing probabilities for both bullish and bearish months separately, traders gain a deeper understanding of market tendencies and recurring monthly patterns, which can be leveraged for improved timing and strategy alignment.
Important:
There is a misalign in percentages due to not all months having the same amount of days.
BK AK-Zenith💥 Introducing BK AK-ZENITH — Adaptive Rhythm RSI for Peak/Valley Warfare 💥
This is not another generic RSI. This is ZENITH: it measures where momentum is on the scale, then tells you when it’s hitting extremes, when it’s turning, and when price is lying through its teeth with divergence.
At its core, ZENITH does one thing ruthlessly well:
it matches the oscillator’s period to the market’s current rhythm—adaptive when the market is fast, adaptive when the market is slow—so your signals stop being “late because the settings were wrong.”
🎖 Full Credit — Respect the Origin (AlgoAlpha)
The core RSI architecture in this form belongs to AlgoAlpha—one of the best introducers and coders on TradingView. They originated this adaptive/Rhythm-RSI framework and the way it’s presented and engineered.
BK AK-ZENITH is my enhancement layer on top of AlgoAlpha’s foundation.
I kept the spine intact, and I added tactical systems: clearer Peak/Valley warfare logic, pivot governance (anti-spam), divergence strike markers, momentum flip confirmation, and a war-room readout—so it trades like a weapon, not a toy.
Respect where it started: AlgoAlpha built the engine. I tuned it for battlefield use.
🧠 What Exactly is BK AK-ZENITH?
BK AK-ZENITH is an Adaptive Period RSI (or fixed if you choose), designed to read momentum like a range of intent rather than a single overbought/oversold gimmick.
Core Systems Inside ZENITH
✅ Adaptive Period RSI (Rhythm Engine)
Automatically adjusts its internal RSI length to match current market cadence.
(Optional fixed length mode if you want static.)
✅ Optional HMA Smoothing
Cleaner shape without turning it into a laggy moving average.
✅ Peak / Valley Zones (default 80/20)
Hard boundaries that define “true extremes” so you stop treating every wiggle like a signal.
✅ Pivot-Based BUY/SELL Triangles + Cooldown
Signals are governed by pivots and a cooldown so it doesn’t machine-gun trash.
✅ Momentum Flip Diamonds (◇)
Shows when the oscillator’s slope flips—clean confirmation for “engine change.”
✅ Divergence Lightning (⚡)
Exposes when price is performing confidence while momentum is quietly breaking.
✅ War-Room Table / Meter
Bias, zone, reading, and adaptive period printed so you don’t “interpret”—you execute.
✅ Alerts Suite
Pivots, divergences, zone entries—so the chart calls you, not your emotions.
🎯 How to use it (execution rules)
1) Zones = permission
Valley (≤ Valley level): demand territory. Stalk reversal structure; stop chasing breakdown candles.
Peak (≥ Peak level): supply territory. Harvest, tighten, stop adding risk at the top.
2) Pivot triangles = the shot clock
Your ▲/▼ signals are pivot-confirmed with a cooldown. That’s intentional.
This is designed to force patience and prevent overtrading.
3) Divergence = truth serum
When price makes the “confident” high/high or low/low but ZENITH disagrees, you’re seeing internal change before the crowd does.
Treat divergence as warning + timing context, not a gambling button.
4) Meter/Table = discipline
If you can’t summarize the state in one glance, you’ll overtrade. ZENITH prints the state so your brain stops inventing stories.
🔧 Settings that actually matter
Adaptive Period ON (default): the whole point of ZENITH
Peak/Valley levels: how strict extremes must be
Pivot strength + Cooldown: your anti-spam governor
Divergence pivot length: controls how “major” divergence must be
The “AK” in the name is an acknowledgment of my mentor A.K. His standards—patience, precision, clarity, emotional control—are why this tool is built with governors instead of hype.
And above all: all praise to Gd—the true source of wisdom, restraint, and right timing.
👑 King Solomon Lens — ZENITH Discernment
Solomon asked Gd for something most people never ask for: not wealth, not victory—discernment. The ability to separate what looks true from what is true.
That is exactly what momentum work is supposed to do.
1) Honest weights, honest measures.
In Solomon’s world, crooked scales were an abomination because they disguised reality. In trading, the crooked scale is your own excitement: you see one green candle and call it strength. ZENITH forces an honest measure—0 to 100—so you deal in degree, not drama. A Peak is not “bullish.” A Peak is “momentum priced in.” A Valley is not “bearish.” A Valley is “selling pressure reaching exhaustion.”
2) Wisdom adapts to seasons.
Solomon’s order wasn’t chaos—there was a time to build, a time to harvest, a time to wait. Markets have seasons too: trend seasons, chop seasons, compression seasons, expansion seasons. Fixed-length RSI pretends every season is the same. ZENITH does not. It listens for rhythm and adjusts its internal timing so your read stays relevant to today’s market tempo—not last month’s.
3) The sword test: revealing what’s hidden.
Solomon’s most famous judgment wasn’t about theatrics—it was about revealing the truth beneath appearances. Divergence is that same test in markets: price can perform strength while the engine quietly weakens, or perform weakness while momentum secretly repairs. The ⚡ is not a prophecy. It’s a revelation: “what you see on price is not the full story.”
That’s ZENITH discipline: measure → discern → execute.
And may Gd bless your judgment to act only when the measure is clean.
⚔️ Final
BK AK-ZENITH is a momentum fire-control system: adaptive rhythm + extreme zones + pivot timing + divergence truth.
Use it to stop feeling trades and start weighing them. Praise to Gd always. 🙏
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.
Nifty Hierarchical Macro GuardOverview
The Nifty Hierarchical Macro Guard is a "Market Compass" indicator specifically designed for Indian equity traders. It locks its logic to the Nifty 50 Index (NSE:NIFTY) and applies a strict hierarchy of trend analysis. The goal is simple: prioritize the long-term trend (Monthly/Weekly) to decide if you should even be in the market, then use the short-term trend (Daily) for precise exit timing.
This script ensures you never ignore a macro "crash" signal while trying to trade minor daily fluctuations.
The Color Hierarchy (Priority Logic)
The indicator uses a "Top-Down" filter. Higher timeframe signals override lower timeframe signals:
Level 1: Monthly (Ultra-Macro) — Deep Maroon
Condition: Nifty 10 EMA is below the 20 EMA on the Monthly chart.
Action: This is the highest priority. The background will turn Deep Maroon, overriding all other colors. This is your "Forget Trading" signal. The long-term structural trend is broken.
Level 2: Weekly (Macro Warning) — Dark Red
Condition: Monthly is Bullish, but Nifty 10 EMA is below the 20 EMA on the Weekly chart.
Action: The background turns Dark Red. This indicates a significant macro correction. You should stay out of fresh positions and protect capital.
Level 3: Daily (Tactical) — Light Red / Light Green
Condition: Both Monthly and Weekly are Bullish (Green).
Action: The background will now react to the Daily 10/20 EMA cross.
Light Green: Nifty is healthy; safe for fresh positions.
Light Red: Tactical exit signal. Nifty is seeing short-term weakness; exit positions quickly.
Key Features
Symbol Locked: No matter what stock you are viewing (Reliance, HDFC, Midcaps), the background only reacts to NSE:NIFTY.
Clean Interface: No messy lines or labels on the price chart. The information is conveyed purely through background color shifts.
Customizable: Change the MA types (EMA/SMA) and lengths (e.g., 10/20 or 20/50) in the settings.
Macro Dashboard: A small, transparent table in the top-right corner displays exactly which timeframe is currently controlling the background color.
How to Use for Nifty Strategy
Stay Out: If the chart is Deep Maroon or Dark Red, do not look for "buying the dip." Wait for the macro health to return.
Take Exits: If the background is Light Green and suddenly turns Light Red, it means the Daily Daily 10/20 cross has happened. Exit your Nifty-sensitive positions immediately.
