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.
经济周期
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.
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.
Breakout Pro (B:Pro) v4.0Breakout PRO (B:Pro) v4.0 is a multi-filter breakout and trend suite designed for discretionary trading on any symbol and timeframe. It combines a custom EMA cloud, volatility and momentum filters, higher-timeframe trend, and quality scoring into one tool, instead of using multiple separate indicators.
Core concept
The script builds a three-layer EMA cloud around price. The relative position of fast, mid, and slow EMAs plus an ATR padding defines:
Bull regime: stacked EMAs with cloud acting as dynamic support
Bear regime: stacked EMAs with cloud acting as dynamic resistance
Neutral regime: mixed EMAs, cloud fades to neutral color
This cloud defines the main trend and the breakout levels (cloud upper / cloud lower).
A higher-timeframe 200 EMA (configurable timeframe) adds a long-term bias filter.
Support, resistance and structure
Last confirmed swing high and swing low are detected with pivot logic and plotted as dotted support / resistance lines.
These levels are invalidated with a small ATR buffer when price clearly breaks them.
Optional long-term EMA targets (T1 and T2, default 233 and 377) are plotted on the price scale as potential mean-reversion or trend-continuation targets.
Filters used in entries
Long and short breakout signals are only shown when multiple conditions agree. You can enable or disable each filter:
Volume: current volume vs volume SMA
MACD: direction and histogram momentum
RSI: classic OB/OS, with sentiment-adjusted levels
Stoch RSI: direction of K vs D in valid zones
Bollinger Bands + Keltner Channel: squeeze and BB breakouts
VWAP: price relative to VWAP
ADX: trend strength threshold
OBV and Ichimoku: optional extra trend confirmation
A separate Market Sentiment input (Standard, Bullish, Bearish, Consolidation) shifts RSI zones, ADX threshold, and volume requirements so the same logic adapts to different environments.
Signals and exits
The main entry logic:
Long signal: bull EMA stack, breakout above the last pivot resistance and above the upper cloud, plus all enabled long filters are satisfied.
Short signal: mirror conditions below support and below the lower cloud.
Trade state is tracked inside the script:
ATR-based stop level is set on entry using mode-dependent ATR multipliers.
Optional maximum trade duration (different for Short, Mid and Long modes).
Exit markers are plotted when stops are hit, the cloud / EMA stack flips against the trade, MACD or RSI contradict the position, or the time limit is exceeded.
Additional icons mark:
Strong breakouts / breakdowns with large ATR and volume
Squeeze releases after a volatility contraction
EMA cross signals
Continuation and potential reversal zones inside the cloud
Optional RSI divergence arrows based on a separate RSI tuned per trade mode.
Quality and safety scoring
For every entry the script computes:
Safety score (1–3): based mainly on volume, ADX trend strength, and alignment with the cloud regime.
Quality score (1–3): based on BB breakout, MACD and RSI agreement, and whether the signal matches the selected market sentiment.
You can:
Show small S/Q labels next to the entry signal
Use the fixed panel in the bottom-left corner to view the last 5 trade events (opens, closes, crosses) with their S and Q values.
Inputs and layout options
Key inputs:
Trade Mode: Short (e.g. 30 min), Mid (e.g. 4h), Long (e.g. 1D+). Adjusts EMA lengths, ATR settings and the RSI length used for divergences.
Market Sentiment: adjusts filters as described above.
Per-filter toggles for volume, MACD, RSI, Stoch RSI, BB, Ichimoku, ADX, OBV, VWAP, HTF levels.
Panel size: Desktop, Phone, or None for the signal history table.
Side labels: Desktop (full text labels on the price scale) or Phone (compact labels without text) for better compatibility on small screens.
Usage notes
This is a technical analysis tool, not a trading system or financial advice. Signals are calculated on closed data without intentional look-ahead, but values on the current forming bar can still change until the bar closes. Use the script as a structured framework for trend, breakout and confluence analysis, and always confirm signals with your own risk management and testing.
Wyckoff NTA InstitutionalWyckoff NTA - Institutional Context Engine
by NexTrade Academy
Wyckoff NTA is an advanced market analysis script developed by NexTrade Academy, designed to identify and quantify the true institutional market context, based on the classic Wyckoff methodology adapted into a modern algorithmic framework.
This script is NOT a signal system and does not aim to provide exact entry or exit points. Its purpose is to act as a context engine, helping traders understand WHEN the market is operable and IN WHICH DIRECTION it makes sense to look for opportunities.
What does Wyckoff NTA do?
Wyckoff NTA analyzes price, volume, and volatility behavior to:
• Identify institutional Wyckoff phases
Accumulation, Distribution, Markup, Markdown, Reaccumulation, Redistribution
• Detect key institutional intent events
Spring, Upthrust, Sign of Strength, Sign of Weakness
• Calculate a Wyckoff Dynamic Score (0-100) that measures the operability of the current market context
• Provide a clean, objective reading of market bias with minimal visual noise
Wyckoff Dynamic Score (0-100)
The dynamic score summarizes the quality of the current market context:
• Below 40: Non-operable context
• 40 to 60: Weak context (A+ setups only)
• 60 to 80: Operable context
• Above 80: Strong institutional context
This score does not trigger trades. It enables or blocks decisions.
Visualization Modes
Wyckoff NTA includes three modes designed for different use cases:
• DESK: Professional execution (minimal, no noise)
• PRO: Active trading with visual context
• EDU: Educational and learning-focused analysis
NexTrade Academy Philosophy
The market does not move because of indicators. It moves due to institutional intent.
Wyckoff NTA is designed for traders who prioritize context, probability, and discipline, and integrates naturally with execution systems such as NTC (NexTrade Concept).
Important Notice
This script does not guarantee results, is not an automated system, and does not constitute investment advice. It should be used strictly as a contextual analysis tool, always alongside a defined trading plan and proper risk management.
Recommended Use
Use Wyckoff NTA to:
• Define overall market context
• Confirm the operable directional bias
• Execute trades only when setups align with that context
Developed by NexTrade Academy
Institutional Trading · Market Structure · Context First
Weekly Daily DividersSimple indicator that plots both Weekly Dividers at 18:00 New York time as Daily Dividers at 00:00 New York time
Volume DI Diff + ADX Coloreado por AOInterpretationIf +DI > -DI (positive DI+ - DI- difference) → Upward trend pressure (bullish signal).
If -DI > +DI (negative DI+ - DI- difference) → Downward trend pressure (bearish signal).
Crossovers between +DI and -DI generate buy/sell signals, often filtered by ADX for reliability.
This setup is widely used in technical analysis to identify trending markets and avoid whipsaws in ranging conditions. It's part of the broader Average Directional Movement System (ADX/DMI).
Key ComponentsADX line: Measures overall trend strength (non-directional).
+DI line: Strength of upward movement.
-DI line: Strength of downward movement.
Trend direction is determined by which DI line is dominant:+DI > -DI: Bullish trend (upward pressure).
-DI > +DI: Bearish trend (downward pressure).
Crossovers between +DI and -DI can signal potential trend changes, but they are most reliable when ADX confirms sufficient strength.ADX Trend Strength Levels (Common Interpretations)ADX Value
Trend Strength
Recommendation
0–20
Weak or no trend (ranging/sideways market)
Avoid trend-following strategies; consider range-bound or oscillator-based trades.
20–25
Emerging or moderate trend (gray zone)
Monitor for confirmation; potential start of trend.
25–50
Strong trend
Ideal for trend-following strategies (e.g., moving averages, breakouts).
50–75
Very strong trend
High momentum; good for riding trends, but watch for exhaustion.
75–100
Extremely strong trend (rare)
Often overextended; risk of reversal or correction.
Rising ADX: Trend is strengthening.
Falling ADX: Trend is weakening (even if still high).
Universal No Wick StrategyThe strategy assumes that strong directional intent is best expressed by no-wick candles (full-body candles with no rejection on one side), but only when they appear in alignment with the prevailing market structure. Trades are taken exclusively in the direction of the active structure and are invalidated immediately on structural change.
Key Components
1. Trend Filter
Two selectable methods:
Market Structure (default): Uses swing highs/lows to define bullish or bearish structure.
EMA Filter: Trades only above/below a configurable EMA.
Only one directional bias is allowed at any time (LONG-only or SHORT-only).
2. Market Structure Engine
ZigZag-based swing detection.
Automatic classification of:
Higher Highs (HH), Higher Lows (HL)
Lower Highs (LH), Lower Lows (LL)
Detects and visualizes:
Change of Character (ChoCH) – trend shift
Break of Structure (BOS) – trend continuation
Any ChoCH immediately cancels opposing pending orders.
3. No-Wick Candle Logic
Bullish no-wick: open = low, close > open
Bearish no-wick: open = high, close < open
Signals are only valid if:
They align with current structure
No position or conflicting pending order exists
Optional candle coloring and compensation lines for visual clarity.
4. HTF Candle Start Confluence
Optional detection of no-wick candles at:
30-minute
1-hour
4-hour candle opens
Visual markers prioritize higher timeframes.
Alerts available for each HTF start condition.
5. Trade Execution & Risk Management
Limit entries at candle open.
Stop Loss:
ATR-based, configurable multiplier.
Take Profit:
Defined as a multiple of SL (R-based).
Orders are automatically canceled if:
Not filled within a defined number of candles.
Market structure changes (ChoCH).
Supports fixed contract sizing.
6. Session Filter
Optional trading session restriction.
Fully configurable session time and timezone.
Visual background highlighting for active sessions.
7. Visual & Informational Tools
Entry and Stop Loss zones plotted as boxes.
Historical entry, SL, and TP lines.
Real-time info table displaying:
Current structure
Allowed trade direction
HTF candle start
Position and pending orders
Active SL and TP levels
8. Alerts
ChoCH (bullish / bearish)
BOS (bullish / bearish)
No-wick signals at 30M, 1H, and 4H candle starts
Intended Use
This strategy is designed for traders who:
Focus on market structure and clean price action
Prefer high-precision entries over frequency
Want strict directional discipline
Value HTF timing and session-based filtering
It is suitable for backtesting, systematic discretionary trading, and automation-focused strategy development.
ORB Pro: Sniper Edition [Hybrid Scanner + Smart Ranking]الوصف (Description):
🚀 ORB Pro: Sniper Edition – The Ultimate Day Trading System
The ORB Pro: Sniper Edition is not just an indicator; it is a complete algorithmic trading system designed for scalpers and day traders who trade the Opening Range Breakout (ORB) strategy.
This edition features a revolutionary "Hybrid Scanner" with "Smart Opportunity Ranking" logic that prioritizes fresh signals over old ones, ensuring you never miss a breakout.
🔥 Key Features:
Hybrid Scanner System:
Manual Mode: Monitor your own top 5 favorite stocks.
Auto Scanner Mode: Automatically scans a pre-defined list of Top 20 High-Momentum Stocks (TSLA, NVDA, AMD, COIN, MSTR, etc.) inside the code.
🧠 Sniper Ranking Logic (The Game Changer): Unlike standard scanners that show static lists, this system sorts stocks dynamically in the table based on opportunity:
🥇 Priority 1: Fresh Breakouts (RUN 🚀) that haven't hit targets yet (The Entry Zone).
🥈 Priority 2: Winning Trades (WIN ✅) that already hit targets.
🥉 Priority 3: Weak or Stopped out trades.
Advanced Strategy Logic:
Fibonacci Targets: Precision exits at 1.618, 2.0, 2.618, and 3.618 extensions.
Smart Reversal: Detects "Fakeouts" and flips the signal immediately (e.g., from CALL to PUT) to catch institutional traps.
Trend Filtering: Uses EMA 50 to filter out low-probability trades.
Risk Management:
Auto Breakeven: Moves stop-loss to entry after Target 1.
Trailing Stop: Dynamic stop-loss that follows the price action.
⚙️ How to Use:
Add the indicator to a 5-minute chart.
Go to Settings > Table System > Select "Auto Scanner".
Watch the table: Focus on the top rows showing "RUN 🚀". These are your live entry signals!
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🚀 مؤشر القناص: ORB Pro Sniper Edition – نظام المضاربة اللحظية المتكامل
يعتبر هذا المؤشر نظاماً آلياً متطوراً للمضاربين اللحظيين (Scalpers/Day Traders) يعتمد على استراتيجية كسر نطاق الافتتاح (ORB) الشهيرة، ولكنه معزز بخوارزميات ذكية لتصفية الفرص.
يتميز هذا الإصدار بوجود "ماسح هجين" (Hybrid Scanner) ونظام "تصنيف ذكي" يعطيك الزبدة ويعرض لك الفرص الحية فور حدوثها.
🔥 أهم المميزات:
نظام الماسح الهجين (Hybrid Scanner):
الوضع اليدوي (Manual): لمراقبة قائمتك الخاصة (5 أسهم تختارها أنت).
الماسح الآلي (Auto Scanner): يقوم المؤشر بمسح فوري لقائمة مدمجة تضم أقوى 20 سهم سيولة ومضاربة في السوق الأمريكي (مثل TSLA, NVDA, MSTR, COIN, وغيرها).
🧠 خوارزمية "القناص" للترتيب (Sniper Ranking): الجدول لا يعرض الأسهم عشوائياً، بل يركز على الفرصة الحالية:
🥇 الأولوية القصوى: للأسهم التي أعطت إشارة دخول (RUN 🚀) ولم تحقق الهدف بعد (هذه هي منطقة الدخول الذهبية).
🥈 الأولوية الثانية: للأسهم التي حققت أهدافها (WIN ✅).
🥉 الأولوية الأخيرة: للأسهم المتذبذبة أو الخاسرة.
دقة فنية عالية:
أهداف فيبوناتشي: تحديد آلي لأهداف جني الأرباح (1.618، 2.0، 2.618).
كشف الانعكاس (Reversal): يكتشف الاختراقات الكاذبة (Fakeouts) ويقلب الإشارة فوراً للدخول مع صناع السوق.
فلتر الترند: يستخدم متوسط 50 لمنع الدخول عكس الاتجاه العام.
إدارة المخاطر:
تأمين الصفقة (Breakeven): يرفع الوقف لسعر الدخول تلقائياً بعد تحقق الهدف الأول.
الوقف المتحرك: يلاحق الأرباح للحفاظ عليها.
⚙️ طريقة الاستخدام:
ضع المؤشر على فريم 5 دقائق.
من الإعدادات، اختر نظام الجدول "Auto Scanner".
راقب الجدول: ركز نظرك على الأسهم التي تظهر في أعلى القائمة بحالة "RUN 🚀".
⚠️ Disclaimer / إخلاء مسؤولية: This tool is for educational and analytical purposes only. Trading involves significant risk. Always manage your risk properly. هذه الأداة للأغراض التعليمية والتحليلية فقط. التداول ينطوي على مخاطر عالية.
Market Structure HighLow + Liquidity [MaB]📊 Market Structure HighLow + Liquidity A comprehensive indicator combining precision market structure analysis with real-time liquidity zone detection, built on a custom finite-state machine architecture.
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🎯 KEY FEATURES
• Automatic Swing Detection Identifies structural High/Low points using a dual-confirmation system (minimum candles + pullback percentage)
• Smart Trend Tracking Automatically switches between Uptrend (Higher Highs & Higher Lows) and Downtrend (Lower Highs & Lower Lows)
• Breakout Alerts Visual markers for confirmed breakouts (Br↑ / Br↓) with configurable threshold
• Sequential Labeling Clear numbered labels (L1, H2, L3, H4...) showing the exact market structure progression
• Color-Coded Structure Lines
• Green: Uptrend continuation legs
• Red: Downtrend continuation legs
• Gray: Trend inversion points
• Imbalance Zones (FVG) Automatically detects Fair Value Gaps that form during impulsive moves between validated swing points
• Inducement Zones Identifies potential liquidity traps - FVGs that form before breakout confirmation, often used as stop-hunt areas
• Dynamic Zone Management Zones automatically close when price touches them, with configurable retracement sensitivity
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🔬 TECHNICAL ARCHITECTURE
This indicator does NOT rely on TradingView's built-in ta.pivothigh() / ta.pivotlow() functions.
Instead, it implements a custom finite-state machine (FSM) that manages multiple monitoring states, alternating dynamically between Uptrend and Downtrend modes based on confirmed breakouts.
Core Components:
• State Machine Engine Multiple internal states handle candidate detection, validation, and confirmation phases. The system transitions between states based on price action triggers and confirmation criteria.
• Dual-Confirmation System Each swing point must satisfy two independent filters before validation:
o Time-based filter (minimum candles)
o Price-based filter (minimum retracement %)
• Directional Breakout Logic Separate breakout detection routines for uptrend continuation, downtrend continuation, and trend inversion scenarios. Each triggers specific state transitions.
• FVG Classification Engine Automatically distinguishes between Imbalance zones (post-confirmation FVGs) and Inducement zones (pre-confirmation FVGs) based on breakout timing context.
• Dynamic Zone Lifecycle Zones are created, monitored, and closed through a managed lifecycle with configurable touch sensitivity.
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⚙️ CONFIGURABLE PARAMETERS
Market Structure
• Analysis Start Date: Define when to begin structure analysis
• Min Confirmation Candles: Required candles for validation (default: 3)
• Pullback Percentage: Minimum retracement for confirmation (default: 10%)
• Breakout Threshold: Percentage beyond structure for breakout (default: 1%)
Liquidity
• Show Zones: Toggle visibility of imbalance and inducement zones
• Zone Colors: Customize colors for Supply/Demand imbalances and inducements
• Zone Retracement %: How deep price must enter zone to consider it touched (0-100%)
• Inactive Zones Transparency: Visual distinction for closed zones
Display
• Show Market Structure Table: Toggle info panel
• Replay Mode: Optimize for TradingView Replay feature
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🎨 ZONE COLOR CODING
• 🔴 Imbalance Supply (Red): Bearish FVG - potential resistance/short entry
• 🟢 Imbalance Demand (Green): Bullish FVG - potential support/long entry
• 🟠 Inducement Supply (Orange): Pre-breakout bearish FVG - possible stop-hunt zone
• 🔵 Inducement Demand (Blue): Pre-breakout bullish FVG - possible stop-hunt zone
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💡 HOW IT WORKS
1. Initializes state machine in UPTREND mode, searching for first swing Low
2. Tracks price movement and triggers candidate states upon potential reversals
3. Validates candidates through dual-confirmation (time + price filters)
4. Upon confirmation, scans price range for FVG patterns (3-candle gaps)
5. Classifies detected FVGs based on breakout timing (Inducement vs Imbalance)
6. Monitors breakout levels - triggers state transitions on confirmed breaks
7. Alternates between Uptrend/Downtrend modes based on breakout direction
8. Manages zone lifecycle - closes zones when price retraces into them
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🔧 BEST USED FOR
• Identifying key support/resistance levels with liquidity context
• Spotting potential reversal zones (imbalances)
• Avoiding stop-hunt traps (inducement awareness)
• Trend direction confirmation
• Breakout trading setups with confluence
• Multi-timeframe structure and liquidity analysis
• Understanding where institutional orders may be resting
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⚠️ NOTES
• Works best on higher timeframes (1H+) for cleaner structure
• Inducement zones often convert to Imbalance zones after breakout confirmation
• Zone Retracement % allows fine-tuning: 0% = first touch, 25% = quarter penetration, 100% = full traversal
• Inactive zones remain visible (faded) to show historical liquidity levels
• Use Replay Mode when backtesting to prevent buffer overflow errors
Crypto Market Sessions (Indian Time)Crypto Market Sessions (Indian Time) is a simple and clean indicator
designed for crypto traders who want to track major global market
sessions based on Indian Standard Time (UTC+05:30).
This indicator highlights the start and end of the following sessions:
• Asia Session
• UK / Europe Session
• USA Session
Each session start and end is marked with a vertical line and label,
making it easy to identify session breaks, market transitions,
and potential volatility periods.
Key Features:
• Indian Standard Time (IST) based session calculation
• Works on all crypto pairs and timeframes
• Clearly marks session start and end points
• No repainting
• Lightweight and easy to use
• Suitable for intraday and swing traders
This indicator does not use any future data and works in real time,
making it safe for live trading and analysis.
If you want any updates, improvements, or custom changes, you can contact me through my TradingView profile .
50-Point Psych Levels (Multiples of 50)50-Point Psychological Levels (Multiples of 50)
This indicator plots static psychological price levels at fixed point intervals (default every 50 points) across the chart. These levels are commonly watched by traders as natural areas of reaction, balance, support, and resistance, especially on index futures such as NQ, ES, YM, and RTY.
The script automatically centers the levels around the current market price and draws them across a configurable range above and below price. All levels extend across the entire chart and are drawn once only, keeping the display clean and preventing redraw lag.
Key Features
Plots horizontal levels at fixed point spacing (default: 50 points)
Automatically anchors around the latest price
Configurable range above and below price
Customizable line color, width, and style
Lightweight, non-repainting, static reference levels
Best Use Cases
Identifying psychological support and resistance
Confluence with VWAP, EMA structure, ORB levels, and volume
Futures trading (NQ, ES, YM, RTY), indexes, and large-tick instruments
[Algo/Fract] Quant+Built for traders ready to Level Up.
Combine algorithmic strength tracking with fractal structure to deliver quant-style clarity on a live chart.
You trade with intuition. Quant trades with Data.
Together, you read the Unseen.
Quant+ is the second component of the AlgoFract Quant Suite.
Features included are:
Quant Cycles & Ghost Cycle (QC)
Custom Volume Spread (VS)
Volume Flow (VF)
Gain Access at: www.algofract.com
or by visiting our Whop Marketplace: whop.com
One-Sided Hodrick-Prescott FilterTechnical & Mathematical Architecture
This indicator represents a significant departure from standard Moving Averages or traditional Hodrick-Prescott (HP) filter implementations found on Trading View. It utilizes a State-Space Model approach to decompose time-series data into trend and cyclical components, solved recursively via a Kalman Filter (Forward Pass) and a Rauch-Tung-Striebel (RTS) Smoother (Backward Pass). Furthermore, it introduces a proprietary Maximum Likelihood Estimation (MLE) loop to adapt the smoothing parameter (λ) dynamically in response to market regimes.
1.1 The State-Space Formulation
The standard HP filter minimizes a specific loss function involving the sum of squared deviations and the sum of squared second differences. While typically solved via batch matrix inversion, this script reformulates the problem as a Local Linear Trend (LLT) model, a stochastic structural model defined by:
Measurement Equation:
y = μ + ε
(Where ε is normally distributed noise)
State Transition Equations:
μ = μ + β + η
β = β + ζ
Where μ represents the stochastic level (trend) and β represents the stochastic slope (drift). The crucial link to the HP filter is the signal-to-noise ratio. By setting the variance of η to 0 (smooth trend) and defining λ as the ratio of measurement variance to slope variance, the Kalman Filter solution converges exactly to the One-Sided HP Filter.
1.2 The Forward Pass: Kalman Filter
The script executes a recursive estimation loop for real-time (causal) filtering:
Prediction Step: Projects the state mean and error covariance forward based on the transition matrix.
Innovation: Calculates the measurement residual (v = y - predicted y).
Update Step: Computes the Kalman Gain. The posterior state is updated based on how much the prediction missed the actual price.
Stability: The covariance update utilizes the Joseph Form subtraction to ensure the covariance matrix remains positive semi-definite, preventing numerical instability inherent in high-precision floating-point calculations over long durations.
1.3 Adaptive λ via Maximum Likelihood
Standard filters use a static λ (e.g., 1600 for quarterly data), which fails in crypto/FX markets exhibiting changing volatility. This script implements an Adaptive ML Loop.
The Kalman Filter assumes innovations are normally distributed with a specific theoretical variance (S). We compute a running variance ratio test:
Ratio = Actual Innovation Variance / Theoretical Variance
Ratio > 1: The model is "surprised" by volatility. The filter is under-fitting. The script dynamically decreases λ to increase responsiveness (reduce lag).
Ratio < 1: The model is over-fitting noise. The script increases λ to enforce a smoother trend.
This allows the filter to function as a low-lag trend follower during impulses and a robust noise filter during consolidation, automatically.
1.4 The Backward Pass: Rauch-Tung-Striebel (RTS) Smoother
This is the most complex feature of the script. While the Forward Pass provides the optimal estimate based on past data, the Backward Pass computes the optimal estimate based on all data.
The RTS algorithm runs purely on historical arrays stored in memory:
It iterates backward from the last bar to the past. It computes a "Smoother Gain" matrix based on future information. It updates the past estimates to correct them based on what happened afterwards. This results in a Minimum Mean Squared Error (MMSE) estimator. Note: This smoothed line is for analytical hindsight and back testing theoretical limits; it is distinct from the real-time filtered line used for live signaling.
Usage Guide:
This indicator is designed for precision trend following and mean-reversion trading. It separates the market price into a Trend Component (Signal) and a Cycle Component (Noise/Oscillation).
The Two Trend Lines:
The Filtered Trend (Real-Time): This is the filled/shaded line on your chart. It calculates the trend using only past data. It does not repaint. Use this for entering and exiting live trades.
Green Fill: Price is above the trend (Bullish bias).
Red Fill: Price is below the trend (Bearish bias).
The Smoothed Trend (Hindsight): (Optional, enabled via settings). This is the "God mode" line. It uses future data to show you exactly where the trend was.
WARNING: This line repaints. Do not trade the tip of this line. Its purpose is to show you the ideal path for training your eye or optimizing parameters.
Mean Reversion Signals:
The script calculates the "Cycle," which is the percentage deviation of price from the HP Trend.
Bands: The Upper and Lower bands represent the Cycle Threshold.
Long Signal (L): Triggered when the Cycle is Oversold (below lower band) AND begins to turn up, while the Filtered Drift (slope) is positive. This suggests a "dip buy" in an uptrend.
Short Signal (S): Triggered when the Cycle is Overbought (above upper band) AND begins to turn down, while the Filtered Drift is negative. This suggests selling a rally in a downtrend.
Adaptive Lambda Panel:
Enable the "Lambda Panel" to see the engine under the hood.
Rising Lambda (Blue): The market is noisy or consolidating. The filter is becoming "stiffer" to ignore the chop.
Falling Lambda (Orange): The market is trending impulsively. The filter is becoming "looser" to track the price closely and reduce lag.
Strategy: You can use low Lambda values as a confirmation of high-volatility breakout regimes.
Performance Table:
A dashboard in the bottom right corner displays the efficiency of the Kalman Filter:
MSE Filtered vs. Smoothed: Shows the Mean Squared Error of the real-time prediction vs. the hindsight-optimal smooth.
Improvement %: A higher percentage indicates that the RTS Smoother is extracting significantly more noise than the real-time filter (common in choppy markets).
Kalman Gains (K1, K2): These display the current weight the filter assigns to new price data for updating the Level and Slope respectively.
Summary of Settings
Base Lambda: The starting stiffness. Higher = smoother (long-term trend). Lower = responsive (short-term trend).
Adaptation Speed: Recommended between 0.01 and 0.05. Controls how fast λ reacts to volatility shocks.
Smoother Lookback: How far back (in bars) the RTS algorithm re-optimizes the historical line.
Best Practice: Use the Filtered Trend for execution. Use the Smoothed Trend to analyze past price action and determine if your Base Lambda setting is appropriate for the asset's volatility profile.
PFA Regime & Structure EnginePFA बाज़ार दर्शन™ is a proprietary market regime and structure indicator designed to provide traders with a comprehensive view of market dynamics. Unlike traditional indicators that focus solely on price direction, this tool evaluates both momentum and structural context to determine the underlying market condition.
It calculates a Regime Score (0–100) by combining momentum energy from MACD pivots, fast and slow structural pivots, and market stress factors. Based on this score, the market is classified into actionable regimes such as Trend Dominant, Selective Phase, or Capital Protection.
The indicator features a live dashboard showing the current regime and score, along with visual structural zones directly on the chart. It acts as an early-warning system for potential market transitions, helping traders manage risk, identify high-probability trend phases, and make informed position-sizing decisions.
Disclaimer: PFA बाज़ार दर्शन™ is for analytical and educational purposes only. It does not provide buy/sell signals or guarantee future performance. Users should combine it with their own trading strategy, risk management, and confirmation tools.
Premium Volume Divergence Signals [Stansbooth]Advanced Divergence Indicator
This indicator is designed to uncover the hidden relationship between price action and momentum. By accurately detecting when price and momentum move in different directions, it highlights bullish and bearish divergences at critical market points — often before reversals or strong continuations occur.
🔹 Key Features:
Precise detection of Regular and Hidden Divergence
Helps identify early market reversals
Clean, clear, and easy-to-read visual signals
Works across Forex, Crypto, and Stock markets
Suitable for all timeframes and trading styles
This indicator empowers traders to make smarter entries, confident exits, and better risk management decisions. Instead of chasing the market, it allows you to anticipate price movement with confidence.
Trade smarter, not harder — let divergence reveal the real market strength.
PFA_Cumulative VolumeComplex Technical Summary – PFA_Cumulative Volume Indicator
The PFA_Cumulative Volume indicator implements a session-normalized volume aggregation framework that conditionally resets at each daily time boundary, thereby isolating intraday participation dynamics from multi-day carryover noise. By cumulatively summing raw traded volume from the session open, the script constructs a real-time proxy for directional conviction and liquidity absorption across the trading day.
In parallel, the indicator captures the immediate microstructure context by explicitly retaining the volume of the last two completed candles, enabling short-horizon comparative analysis of participation decay, acceleration, or stalling. This dual-layer design—macro session accumulation coupled with micro candle-level volume comparison—allows traders to infer whether price movement is being structurally supported by expanding market involvement or merely drifting due to transient order flow.
The visualization layer, implemented via a dynamically updated table overlay, prioritizes informational density over graphical plots. By segregating cumulative session volume, last-candle volume, and second-last-candle volume into discrete cells, the indicator facilitates rapid regime assessment without distorting price charts. Functionally, the tool does not assert directional bias; instead, it acts as a participation integrity monitor, highlighting divergence between price action and underlying volume commitment, which is critical for detecting distribution, exhaustion, or false continuation scenarios.
In essence, the indicator operationalizes volume as a state variable rather than a trigger, framing trades around the sustainability of market effort rather than isolated price events.
PFA_ATR Locha:Clean Volatility RegimeCondensed Abstract (Advanced)
ATR Locha functions as a non-directional volatility-regime discriminator, operationalizing ATR normalized by price to detect latent shifts in market stress dynamics. By stratifying volatility into compression, equilibrium, and expansion states, it isolates pre-trend instability and post-trend exhaustion without invoking directional bias. The indicator is structurally anticipatory rather than predictive, serving as a probabilistic risk-state lens that contextualizes price behavior, enhances temporal positioning, and mitigates regime-mismatch errors when integrated with structural or trend-confirmatory frameworks.
PFA_ATR LochaCondensed Abstract (Advanced)
ATR Locha functions as a non-directional volatility-regime discriminator, operationalizing ATR normalized by price to detect latent shifts in market stress dynamics. By stratifying volatility into compression, equilibrium, and expansion states, it isolates pre-trend instability and post-trend exhaustion without invoking directional bias. The indicator is structurally anticipatory rather than predictive, serving as a probabilistic risk-state lens that contextualizes price behavior, enhances temporal positioning, and mitigates regime-mismatch errors when integrated with structural or trend-confirmatory frameworks.
