Checklist OPR - 3/13CHECKLIST ENTRY – 3/13 (Strict Trading Plan)
This indicator displays a **visual checklist in the bottom-right corner** to validate trade entries based on a disciplined plan.
**Entry Rule**:
→ **At least 3 out of 13 confirmations** must be manually checked.
**13 Confirmations**:
• Flux follow-through (H1, H4, D)
• OPR breakout
• OPR retest / reintegration
• Weightless bubble
• Polarity zone (M15 / H1 / H4 / D / W)
• Fibonacci level 0.5 / 0.382 / 0.618
• RSI divergence
• RSI divergence + noise breakout
**Real-Time Display**:
- Green checkmark = Validated
- Gray circle = Not validated
- Final status:
→ **ENTRY AUTHORIZED** (green) if ≥3
→ **OUT OF PLAN** (red) otherwise
**Customizable**:
- Adjust threshold (default: 3) in settings
- Check/uncheck live via indicator inputs
**How to Use**:
1. Open indicator settings
2. Check the criteria met on the chart
3. Status updates instantly
Perfect for disciplined traders.
**No entry without 3 confirmations.**
Indicatori e strategie
Kalman Adaptive Score Overlay [BackQuant]Kalman Adaptive Score Overlay
A powerful indicator that uses adaptive scoring to assess market conditions and trends, utilizing advanced filtering techniques to smooth price data, enhance trend-following precision, and predict future price movements based on past data. It is ideal for traders who need a dynamic and responsive trend analysis tool that adjusts to market fluctuations.
What is Adaptive Scoring?
Adaptive scoring is a technique that adjusts the weight or importance of certain price movements over time based on an ongoing assessment of market behavior. This indicator uses dynamic scoring to assess the strength and direction of price movements, providing insight into whether a trend is likely to continue or reverse. The score is recalculated continuously to reflect the most up-to-date market conditions, offering a responsive approach to trend-following.
How It Works
The core of this indicator is built on advanced filtering methods that smooth price data, adjusting the response to recent price changes. The filtering mechanism incorporates a Kalman filter to reduce noise and improve the accuracy of price signals. Combined with adaptive scoring, this creates a robust framework that automatically adjusts to both short-term fluctuations and long-term trends.
The indicator also uses a dynamic trend-following component that updates its analysis based on the direction of the market, with the option to visualize it through colored candles. When a strong trend is identified, the candles are painted to reflect the prevailing trend, helping traders quickly identify whether the market is in a bullish or bearish state.
Why Adaptive Scoring Is Important
Dynamic Response: Adaptive scoring allows the indicator to respond to changing market conditions. By adjusting its sensitivity to price fluctuations, it ensures that trends are captured accurately, without being overly influenced by short-term noise.
Trend Precision: By combining Kalman filtering with adaptive scoring, the indicator offers a precise and smooth trend-following mechanism. It helps traders stay aligned with the market direction and avoid false signals.
Versatility: The indicator works across multiple timeframes, making it adaptable to different trading strategies, from scalping to long-term trend-following.
Confidence in Market Moves: The adaptive scoring component provides traders with confidence in the strength of the trend, helping them determine when to enter or exit positions with greater certainty.
How Traders Use It
Trend-Following Strategy: Traders can use this indicator to confirm trends and refine their entries and exits. The colored candles and adaptive scoring offer a visual cue of trend strength and direction, making it easier to follow the prevailing market movement.
Multi-Timeframe Analysis: The script supports multi-timeframe analysis, allowing traders to analyze trends and scores across different timeframes (e.g., 1m, 5m, 15m, 30m, 1h, 4h, 12h). This is useful for traders who want to confirm trends on both short and long-term charts before making a trade.
Refining Entry Points: By utilizing the adaptive scoring, traders can identify potential entry points where the score indicates a high probability of trend continuation. Higher scores signal stronger trends, guiding decision-making.
Managing Risk: Traders can use the adaptive scoring system to assess trend stability and adjust their risk management strategies accordingly. For example, higher confidence in the trend allows for larger positions, while lower confidence may require smaller, more cautious trades.
Key Features and Benefits
Kalman Filter for Noise Reduction: The Kalman filter helps to smooth out market noise and allows for a clearer understanding of the underlying price movements. This is particularly useful in volatile markets where short-term fluctuations can cloud trend analysis.
Adaptive Scoring for Flexibility: Adaptive scoring ensures that the indicator remains responsive to changing market conditions. It automatically adjusts to the strength of price movements, enabling better detection of trends and reversals.
Visual Trend Signals: The indicator provides visual signals through candle coloring, making it easier to identify whether the market is in a bullish, neutral, or bearish phase.
Multi-Timeframe Display: The indicator’s multi-timeframe feature allows traders to see the trend and adaptive score on different timeframes simultaneously, providing a comprehensive view of the market.
Customizable Settings: Traders can customize the indicator’s settings, such as the filter parameters, scoring thresholds, and visualization options, tailoring it to their specific trading style and strategy.
Why This is Important for Traders
Improved Decision Making: The adaptive nature of the scoring system allows traders to make more informed decisions based on real-time market data, without being influenced by past volatility.
Market Clarity: By smoothing out price movements and scoring trends adaptively, the indicator provides a clearer picture of market behavior, which is essential for effective trend-following and timing entries and exits.
Increased Confidence in Signals: Adaptive scoring ensures that signals are based on the current market structure, reducing the likelihood of false positives. This boosts traders' confidence when acting on signals.
Conclusion
The Kalman Adaptive Score Overlay offers a dynamic and responsive trend-following tool that integrates Kalman filtering with adaptive scoring. By adjusting to market fluctuations in real time, it allows traders to identify and follow trends with greater precision. Whether you are trading on short or long timeframes, this tool helps you stay aligned with market momentum, ensuring that your entries and exits are based on the most up-to-date and reliable data available.
Cross-Sectional Relative MomentumDEVELOPED BY A FORMER GOLDMAN SACHS TRADER
Overview
The Cross-Sectional Momentum / Relative Value System measures and ranks assets against each other in real time to identify leaders (assets showing relative strength) and laggards (assets underperforming their cluster). It provides an institutional-style snapshot of relative momentum across a defined universe — highlighting where capital is flowing and where mean-reversion potential is building.
How It Works
The system continuously evaluates a cluster of correlated assets — such as FX pairs, equity indices, or commodities — and computes each instrument's standardized forecast value (typically scaled between −20 and +20). This creates a dispersion map of momentum within the group: When dispersion expands (the gap between leaders and laggards widens), it signals a momentum regime: markets are trending and leadership is clear. When dispersion compresses, it indicates convergence and an increased likelihood of mean-reversion. Each asset is then tagged dynamically as Leader or Laggard, based on its position within the cluster's distribution. This ranking helps you visualise market structure — which assets are driving the move and which are trailing.
Use Cases
Rotational Strategies: Shift exposure toward top-ranked assets (leaders) while fading underperformers (laggards)
Leadership Transitions: Detect when leadership flips (e.g., GBPUSD moving from laggard to leader), signalling rotation or regime change
Portfolio Diversification: Balance exposures by ensuring allocation across uncorrelated or complementary clusters
Confirmation Tool: Combine with regime or volatility systems to determine when relative momentum is statistically significant (momentum phase) or mean-reverting (consolidation phase)
Interpretation Example
Example Output:
Leader Assets: GBPCHF (+8.8), GBPUSD (+2.7) — Laggard Assets: EURUSD (−2.9), USDCAD (−3.6)
Meaning:
This configuration suggests GBP-linked strength relative to USD-linked weakness — a cross-pair rotation opportunity
"Ranks assets by strength and timing — revealing where leadership, rotation, and mean-reversion are statistically emerging."
T3 MACDThis indicator utilizes the Till3 Moving Average and is created in the form of a Moving Average Convergence Divergence (MACD). Compared to the traditional MACD, it reduces noise, allowing for more reliable trend assessment.
2025-11-04
TRADE ORBIT:- MACD-V HISTOGRAM FLIP AND MACD- CROSS OVER SY 2&3✅ DESCRIPTION
This indicator is an enhanced MACD-V (ATR-normalized MACD) system that integrates Higher-Timeframe confirmation, level filtering, and histogram zero-line signals for improved trend and momentum recognition.
🔹 Core Logic
MACD-V normalizes the traditional MACD using ATR to create a volatility-adjusted oscillator.
This helps compare momentum across markets and conditions more consistently.
🔹 Key Features
✅ MACD-V Calculation
• Uses (EMA Fast – EMA Slow) / ATR × 100
• Produces macd, signal, and histogram lines
✅ Higher Time-Frame (HTF) Filtering
• Multiplies current timeframe by a user-controlled factor
• HTF MACD-V + signal values are fetched safely (no repainting)
• Only HTF crossovers that satisfy level requirements are considered
✅ Level-Filtered Signals
• Bullish valid only when MACD-V ≥ +50
• Bearish valid only when MACD-V ≤ –50
This ensures higher conviction and trend strength before signaling.
✅ Histogram Zero-Line Signals
• Histogram crossing above 0 → BUY
• Histogram crossing below 0 → SELL
• Visual triangles mark direction
✅ Background Highlighting
• Blue = HLTF-Bullish cross (+50 filter)
• Black = HTF-Bearish cross (–50 filter)
✅ Visual Overbought/Oversold Levels
• Horizontal reference bounds (±150 default)
✅ Alerts (No Expression Errors)
Four ready-to-use alerts with literal text:
HTF MACD-V Bull + Level
HTF MACD-V Bear + Level
Histogram Zero BUY
Histogram Zero SELL
No string-error or concatenation issues.
🔹 Recommended Use
• Identify strong momentum aligned with a higher timeframe
• Confirm trends with +50 / –50 filters
• Monitor early shifts via histogram zero crossings
Best for swing traders, position traders, and multi-timeframe analysts.
Conditions DashboardDEVELOPED BY A FORMER GOLDMAN SACHS TRADER
Overview
The Conditions Dashboard acts as the framework's situational awareness layer — translating raw indicator outputs into cohesive market "states."
How It Works
At its core, State Detection evaluates a structured matrix of technical and statistical indicators (e.g., EMAs, volatility, skewness, ADX, momentum accelerators). Each component feeds a binary or scaled state — such as Long, Short, Bull, Bear-Continue, or Contracting. Two synchronized tables form the visual interface: the Indicator State Table displays active sub-systems showing each indicator's current state, and the Timeframe Alignment Table aggregates EMAC and trend state readings across multiple timeframes.
Use Cases
Multi-timeframe confirmation: enter trades only when short- and medium-term states align
Conflict detection: stand aside when lower- and higher-timeframe signals diverge
Momentum monitoring: use the Forecast/Accel and Momentum State rows to identify strengthening vs. weakening phases
Visual diagnostics: embed the table on live charts to instantly understand current structure
Strategic scaling: combine with the Combined Forecast or Trend Exhaustion Systems
Interpretation Example
Example Output:
All timeframes: Bull-Continue
Meaning:
Strong aligned uptrend; maintain or scale into longs. Mixed states indicate transition phase; reduce exposure and monitor for volatility compression
Combined Forecast SystemDEVELOPED BY A FORMER GOLDMAN SACHS TRADER
Overview
The Combined Forecast System is the backbone of the framework — a single model that merges multiple independent forecast engines into one conviction score.
How It Works
It continuously aggregates signals derived from trend, momentum, mean-reversion, and volatility features, normalizing each into a standardized range (−20 to +20). The output is both a numerical forecast and a market state (bullish/bearish, strengthening/weakening).
Use Cases
Gauge the overall directional conviction of the market
Adjust exposure dynamically (e.g., 50% position when forecast = +10, full position at +20)
Identify regime shifts as forecasts transition between states
Use as a top-level filter for discretionary or automated trading strategies
Interpretation Example
Example Output:
Forecast = +15 → "Bullish Strengthening"
Meaning:
Suggests accelerating upward momentum; scale into longs, tighten short exposure
7D Historical Volatility (Regimes + Stats) - ChrrizzyHere’s what that indicator does—at a glance:
### Core idea
It computes **7-day Historical Volatility (HV)** from **daily** log returns (annualized), then shows:
* the **HV line** and its **30-day average**,
* colored **volatility regimes** (Low / Normal / High / Extreme) with thresholds you set,
* a compact **status panel** (top-right, nudged left) with current stats and time-in-zone.
### Calculations
* **HV (7D)**: `stdev(log(close/close ), 7) * sqrt(365) * 100`, always from **daily data** via `request.security`, so it’s consistent on any chart timeframe.
* **Regimes** (defaults):
Low < 25% • Normal 25–50% • High 50–70% • Extreme > 70% (all editable).
* **30-day avg**: SMA of HV.
* **Time in zone (% over window)**: SMA of boolean flags (e.g., in Low=1 else 0) over `statsWin` days (default 300).
* **Rolling median HV**: 50th percentile over `statsWin`.
### What you see on the chart
* **HV line** (bold) + **30-day HV** (lighter).
* **Horizontal dashed lines** at your regime thresholds.
* **Background shading** that changes with the current regime (green/blue/orange/red).
### Panel (top-right)
Shows:
* BTC Price (daily close)
* Current HV
* 30-day Avg HV
* Median HV (over window)
* Current **Regime**
* A two-line summary: **% of time spent** in Low / Normal / High / Extreme over the chosen window.
The panel is shifted slightly left using a hidden spacer column; tweak the **“Panel right padding (chars)”** input to move it.
### Alerts (ready to use)
* **HV crossed up Low**
* **HV crossed down Low**
* **HV crossed up High**
* **HV crossed up Extreme**
### Inputs you can tune
* `HV Lookback (days)` (default 7)
* `Average HV (days)` (default 30)
* Thresholds: Low/High/Extreme
* `Stats Window (days)` (default 300)
* Panel padding, toggle table/zones on/off.
### How to use it
* **Context**: quickly see if BTC is in **compressed** (Low) or **stressed** (High/Extreme) volatility.
* **Regime cross alerts**: get notified when volatility **expands** from Low (potential breakout conditions) or pushes into High/Extreme (risk increases).
* **Stats/median**: compare today’s HV to its typical level over your lookback window.
If you want, I can add an **HV percentile rank** (e.g., “Current HV is at the 38th percentile over 300d”) or mirror the **low-vol breakout signal** from Script A into this panel.
MTF - Zones Scanner⚡ MTF Zones Scanner
- Smarter Multi-Timeframe Trading — Simplified.
💼 Ever wondered what tools Prop Desk Traders use?
You’ve just landed in the right place.
MTF Zones Scanner brings you the same level of structural clarity used in proprietary trading setups — combining multi-timeframe confluence and multiple reversal signal alignment in one elegant package.
📊 Spot market structure, zone strength, and breakout opportunities across multiple symbols — instantly.
Built for traders who demand clarity, context, and confidence — without unnecessary complexity.
🌍 One Dashboard. All Signals.
🔁 Multi-Timeframe Zone Mapping — View higher-timeframe zones directly on your working chart.
🧭 Smart Symbol Groups — Seamlessly monitor all 500 Nifty stocks, organized for maximum scanning efficiency.
⚙️ Continuous Background Monitoring — Even while you focus on one chart, the script quietly tracks every stock for possible breakouts or breakdowns.
🧩 Dynamic Confluence Engine — Detects when short- and long-term structures align for stronger setups.
🧠 Intelligent Scoring Model — Each symbol is automatically ranked by structural strength, momentum, and probability.
🚨 Group-Based Alerts — One alert fires when any stock in your selected group triggers a high-confidence breakout.
🕹️ Key Benefits
✅ Monitors the entire Nifty 500 universe automatically — no chart-hopping required.
✅ Instantly highlights stocks nearing key demand or supply zones.
✅ Adds higher-timeframe confirmation for cleaner entries & exits.
✅ Optimized for intraday and swing trading.
✅ Fully visual, customizable, and resource-efficient.
🧭 At a Glance
🔹 On-chart Zone Overlays highlight actionable areas.
🔹 Real-time Ranking Table shows your strongest setups.
🔹 Clear status icons:
🟢 Potential Buy Zone
🟣 Potential Sell Zone
⚪ Consolidation Watch
🟡 Breakout Detected
🔔 Unified Alert System
Forget juggling multiple alerts or scripts.
Whenever any stock in your chosen group confirms a breakout or breakdown with a strong score, you’ll instantly get:
TATASTEEL on 15 min → 🟢 Demand Breakout Detected
You don’t need to set 500 alerts — just 34 simple group alerts to cover the entire Nifty 500 universe.
The system handles everything else silently in the background.
Fully compatible with TradingView’s “Any alert() function call” — precise, real-time, and noise-free.
🧱 Built for Power Users
🕒 Works across all intraday & swing timeframes.
⚙️ Adjustable sensitivity, zone depth, and confluence strength.
🧩 Pre-loaded with the complete Nifty 500 list.
💻 Powered by Pine v6 for stable, efficient background scanning.
💡 Not from India? No Problem.
The indicator can be customized to scan any set of stocks — from any country or market worldwide.
Just get in touch with us, and we’ll build a custom version tailored to your needs.
💡 Who It’s For
Sector & positional traders managing wide watchlists.
Intraday traders looking for quick, high-confidence confirmations.
Analysts seeking multi-timeframe confluence across diverse markets.
✨ Why It Stands Out
🧭 Context + Clarity + Consolidation
Don’t react — anticipate.
MTF Zones Scanner constantly interprets market structure so you can focus on decisive, high-probability setups across every stock you follow.
A professional-grade, Prop-Desk-style multi-timeframe scanner that filters noise, reveals structure, and surfaces opportunities — automatically.
🛡️ Proprietary Technology Notice
The analytical framework of MTF Zones Scanner is proprietary and confidential.
It blends multiple quantitative and contextual models into a single actionable output — keeping your edge intact.
🎁 Get Connected for 1-Month Free Trial →
Experience the power of real-time, all-market awareness.
🔗 Start Your Free Trial Today — and Trade Smarter Now.
Reveral Candles# Reversal Structure & Pinbar Fusion Engine — by Seal
This indicator provides precise detection of market reversal structures by mathematically merging price candles to identify true pinbar-based reversal events.
Instead of relying on visual candlestick patterns, this tool applies strict wick/body geometry, range validation, and multi-bar fusion logic to confirm genuine shifts in market control.
### Included Models
• Single-bar Pinbars (strict 2/3 wick rule)
• 2-bar Fusion Reversals
• Bullish / Bearish Engulfing (full reclaim of prior open)
• Piercing / Dark Cloud (mid-body reclaim logic)
• 3-bar Fractal Reversal Pinbars
• “Left-Pivot-Right” structure
• Sweep + reclaim + dominant wick confirmation
This approach highlights failed breakouts, liquidity sweeps, absorption, and reversal momentum, giving traders a cleaner view of price behavior around key turning points.
Colors, labels and wick-ratio thresholds are user-configurable.
Designed for traders who read market intent, not just candle shapes.
---
## Indicator Settings Overview
### Detection Modes
• Strict Pinbar Detector
• 2-Bar Fusion Reversal
• 3-Bar Fractal Pinbar
### Geometry Rules
• Wick ≥ selected fraction of total range (default 66%)
• Opposite-side wick + body ≤ remaining fraction
• Sweep of prior candle high/low required (2-bar logic)
• Structural pivot required (3-bar fusion logic)
### Validation Filters
• Minimum candle-range filter
• True reclaim requirement (engulfing & piercing logic)
• Avoids false signals during low-volatility noise
### Appearance
• Bullish/Bearish colors selectable
• Pinbar arrows & labels
• Option to enable/disable each reversal type
• Optimized for clarity across timeframes
---
## Recommended Use
• Works on all assets & timeframes
• Best in volatile environments
• Ideal for price-action / SMC / liquidity traders
• Complements OB / FVG / Supply-Demand frameworks
---
## Notes
• Not lagging — structural logic, not smoothing
• Pinbars verified by energy geometry, not visual guesswork
• Multi-bar fusion removes noise and exposes true intent
• Highlights traps, stop-hunts, reclaim shifts
Ornstein-Uhlenbeck Trend Channel [BOSWaves]Ornstein-Uhlenbeck Trend Channel - Adaptive Mean Reversion with Dynamic Equilibrium Geometry
Overview
The Ornstein-Uhlenbeck Trend Channel introduces an advanced equilibrium-mapping framework that blends statistical mean reversion with adaptive trend geometry. Traditional channels and regression bands react linearly to volatility, often failing to capture the natural rhythm of price equilibrium. This model evolves that concept through a dynamic reversion engine, where equilibrium adapts continuously to volatility, trend slope, and structural bias - forming a living channel that bends, expands, and contracts in real time.
The result is a smooth, equilibrium-driven representation of market balance - not just trend direction. Instead of static bands or abrupt slope shifts, traders see fluid, volatility-aware motion that mirrors the natural pull-and-release dynamic of market behavior. Each channel visualizes the probabilistic boundaries of fair value, showing where price tends to revert and where it accelerates away from its statistical mean.
Unlike conventional envelopes or Bollinger-type constructs, the Ornstein-Uhlenbeck framework is volatility-reactive and equilibrium-sensitive, providing traders with a contextual map of where price is likely to stabilize, extend, or exhaust.
Theoretical Foundation
The Ornstein-Uhlenbeck Trend Channel is inspired by stochastic mean-reversion processes - mathematical models used to describe systems that oscillate around a drifting equilibrium. While linear regression channels assume constant variance, financial markets operate under variable volatility and shifting equilibrium points. The OU process accounts for this by treating price as a mean-seeking motion governed by volatility and trend persistence.
At its core are three interacting components:
Equilibrium Mean (μ) : Represents the evolving balance point of price, adjusting to directional bias and volatility.
Reversion Rate (θ) : Defines how strongly price is pulled back toward equilibrium after deviation, capturing the self-correcting nature of market structure.
Volatility Coefficient (σ) : Controls how far and how quickly price can diverge from equilibrium before mean reversion pressure increases.
By embedding this stochastic model inside a volatility-adjusted framework, the system accurately scales across different markets and conditions - maintaining meaningful equilibrium geometry across crypto, forex, indices, or commodities. This design gives traders a mathematically grounded yet visually intuitive interpretation of dynamic balance in live market motion.
How It Works
The Ornstein-Uhlenbeck Trend Channel is constructed through a structured multi-stage process that merges stochastic logic with volatility mechanics:
Equilibrium Estimation Core : The indicator begins by identifying the evolving mean using adaptive smoothing influenced by trend direction and volatility. This becomes the live centerline - the statistical anchor around which price naturally oscillates.
Volatility Normalization Layer : ATR or rolling deviation is used to calculate volatility intensity. The output scales the channel width dynamically, ensuring that boundaries reflect current variance rather than static thresholds.
Directional Bias Engine : EMA slope and trend confirmation logic determine whether equilibrium should tilt upward or downward. This creates asymmetrical channel motion that bends with the prevailing trend rather than staying horizontal.
Channel Boundary Construction : Upper and lower bands are plotted at volatility-proportional distances from the mean. These envelopes form the “statistical pressure zones” that indicate where mean reversion or acceleration may occur.
Signal and Lifecycle Control : Channel breaches, mean crossovers, and slope flips mark statistically significant events - exhaustion, continuation, or rebalancing. Older equilibrium zones gradually fade, ensuring a clear, context-aware visual field.
Through these layers, the channel forms a continuously updating equilibrium corridor that adapts in real time - breathing with the market’s volatility and rhythm.
Interpretation
The Ornstein-Uhlenbeck Trend Channel reframes how traders interpret balance and momentum. Instead of viewing price as directional movement alone, it visualizes the constant tension between trending force and equilibrium pull.
Uptrend Phases : The equilibrium mean tilts upward, with price oscillating around or slightly above the midline. Upper band touches signal momentum extension; lower touches reflect healthy reversion.
Downtrend Phases : The mean slopes downward, with upper-band interactions marking resistance zones and lower bands acting as reversion boundaries.
Equilibrium Transitions : Flat mean sections indicate balance or distribution phases. Breaks from these neutral zones often precede directional expansion.
Overextension Events : When price closes beyond an outer boundary, it marks statistically significant disequilibrium - an early warning of exhaustion or volatility reset.
Visually, the OU channel translates volatility and equilibrium into structured geometry, giving traders a statistical lens on trend quality, reversion probability, and volatility stress points.
Strategy Integration
The Ornstein-Uhlenbeck Trend Channel integrates seamlessly into both mean-reversion and trend-continuation systems:
Trend Alignment : Use mean slope direction to confirm higher-timeframe bias before entering continuation setups.
Reversion Entries : Target rejections from outer bands when supported by volume or divergence, capturing snapbacks toward equilibrium.
Volatility Breakout Mapping : Monitor boundary expansions to identify transition from compression to expansion phases.
Liquidity Zone Confirmation : Combine with BOS or order-block indicators to validate structural zones against equilibrium positioning.
Momentum Filtering : Align with oscillators or volume profiles to isolate equilibrium-based pullbacks with statistical context.
Technical Implementation Details
Core Engine : Stochastic Ornstein-Uhlenbeck process for continuous mean recalibration.
Volatility Framework : ATR- and deviation-based scaling for dynamic channel expansion.
Directional Logic : EMA-slope driven bias for adaptive mean tilt.
Channel Composition : Independent upper and lower envelopes with smoothing and transparency control.
Signal Structure : Alerts for mean crossovers and boundary breaches.
Performance Profile : Lightweight, multi-timeframe compatible implementation optimized for real-time responsiveness.
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Reactive equilibrium tracking for short-term scalping and microstructure analysis.
15 - 60 min : Medium-range setups for volatility-phase transitions and intraday structure.
4H - Daily : Macro equilibrium mapping for identifying exhaustion, distribution, or reaccumulation zones.
Suggested Configuration:
Mean Length : 20 - 50
Volatility Multiplier : 1.5× - 2.5×
Reversion Sensitivity : 0.4 - 0.8
Smoothing : 2 - 5
Parameter tuning should reflect asset liquidity, volatility, and desired reversion frequency.
Performance Characteristics
High Effectiveness:
Trending environments with cyclical pullbacks and volatility oscillation.
Markets exhibiting consistent equilibrium-return behavior (indices, majors, high-cap crypto).
Reduced Effectiveness:
Low-volatility consolidations with minimal variance.
Random walk markets lacking definable equilibrium anchors.
Integration Guidelines
Confluence Framework : Pair with BOSWaves structural tools or momentum oscillators for context validation.
Directional Control : Follow mean slope alignment for directional conviction before acting on channel extremes.
Risk Calibration : Use outer band violations for controlled contrarian entries or trailing stop management.
Multi-Timeframe Synergy : Derive macro equilibrium zones on higher timeframes and refine entries on lower levels.
Disclaimer
The Ornstein-Uhlenbeck Trend Channel is a professional-grade equilibrium and volatility framework. It is not predictive or profit-assured; performance depends on parameter calibration, volatility regime, and disciplined execution. BOSWaves recommends using it as part of a comprehensive analytical stack combining structure, liquidity, and momentum context.
Trend ExhaustionDEVELOPED BY A FORMER GOLDMAN SACHS TRADER
Overview
The Trend Exhaustion System measures how far a trend has progressed through its statistical life cycle and estimates the probability it will continue versus reverse. Unlike conventional momentum indicators, it applies survival-analysis techniques to quantify the remaining lifespan of an active trend — offering a probabilistic gauge of exhaustion rather than a visual guess.
How it works
From the moment a trend begins, the system tracks its age, median historical duration, quartile position, and current survival probability. These metrics are updated dynamically each bar to show whether the trend is still in its statistically healthy phase or approaching exhaustion. By analysing thousands of historical trend samples, the model builds a probability curve showing how likely similar moves were to persist at each age. This transforms trend following from a binary decision into a probabilistic framework — allowing conviction and sizing to decay gradually as a move matures.
Use Cases
Exposure Management: Reduce position size as trends approach their historical median life
Reversal Anticipation: Identify zones where the probability of continuation has dropped sharply before price reversal occurs
Signal Combination: Pair with the Combined Forecast System — e.g., high forecast strength + young trend = high conviction; aged trend + decaying survival = reduced sizing
Risk Control: Integrate with trailing-stop or scaling logic in systematic portfolios to manage exit timing objectively
Interpretation Example
Example Output:
Short trend, age 28 bars, survival probability 22%
Meaning:
The short move is statistically late-stage; continuation odds are low — consider scaling out, tightening stops, or preparing for a reversal
"Quantifies how much life is left in a trend — transforming intuition into measurable probability."
3 Min Scalping MSE (No Repeat Signals) Aazam JaniThis indicator is designed for 3-minute scalping setups that combine EMA alignment to generate high-probability Buy and Sell signals — while preventing duplicate entries until the opposite signal appears.
Gabriel__ionescuSwing line for Swing Traders, follow the trend and open only when the price retest the line
Oversold Screener · Webhook v3.3#Oversold Screener · Webhook v3.3
US Equities · 15-minute signals · AVWAP entries A–F · Optional CVD gate
## TL;DR
This indicator finds short-term, emotion-driven selloffs in large, liquid US stocks and pings your webhook with a compact alert (symbol + 15-minute close time).
It anchors an Event-AVWAP at the first qualified 15-minute bar after the selloff and proposes disciplined “right-side” entries (A–F) as price mean-reverts back through statistically defined bands. Optional macro fuses and CVD filters help avoid catching knives.
---
## What it does
1. Universe filter (off-chart): You run this on constituents of S&P 500 / Nasdaq-100 / Nasdaq Golden Dragon (or your curated list of healthy companies).
2. Signal (Step-2): On the 15-minute timeframe—including extended hours—the script flags an “oversold event” when:
• Depth: Today’s drawdown vs yesterday’s RTH reference (min of yesterday’s VWAP and Close) is large.
• Relative: The stock underperforms both its market benchmark (e.g., SPY/QQQ) and its sector ETF over the same 16/32×15m windows.
• Macro fuses: If any of the following exceed thresholds, the signal is suppressed: VIX spike, market 16/32×15m selloff, sector 16/32×15m selloff.
• RSI guard: 1-hour RSI is below a configurable level (default 30).
• Cooldown: De-dupes repeated events; you won’t be spammed by the same name intraday.
3. Execution geometry: At the event bar’s close the indicator anchors an AVWAP calculated natively in 15m space and draws ±1σ/±2σ/±3σ bands from a rolling variance of typical price.
4. Entry proposals: It labels A–F entries when price regains key bands after first probing the lower ones (see below). Optional 15m CVD confirmation can be required.
5. Alerts: When the event closes, TradingView raises a single alert with a tiny JSON payload so your downstream AI/service can do the news check and decide.
---
## Why this approach works
• Depth vs yesterday’s RTH reference targets “fresh” dislocations rather than slow trends.
• Relative filters ensure the stock fell much more than both the market and its sector, isolating idiosyncratic panic.
• AVWAP from the event bar approximates the market’s true average position after the shock; band reclaims are robust right-side confirmations.
• Optional CVD (delta volume) catches sell-side exhaustion and buy-side emergence without requiring a full order-book feed.
• Macro fuses (VIX / market / sector) avoid swimming against systemic stress.
---
## Inputs (key)
Bench ETF / Sector ETF
Choose your market (SPY or QQQ) and sector ETF (XLK/XLF/XLY… or KWEB/CQQQ for China tech ADRs).
Depth & relative settings (15-minute space)
• Depth vs prior-day RTH reference: percentage thresholds for 16 and 32 bars.
• Relative to market & sector: underperformance thresholds over 16 and 32 bars.
Macro circuit breakers
• VIX max change (e.g., +8%/+12% over the session)
• Market max 16/32×15m selloff (e.g., −1.5% / −2.5%)
• Sector max 16/32×15m selloff (e.g., −2.0% / −3.0%)
If any one exceeds the limit, the signal is suppressed.
Momentum guard
• RSI(1h) < 30 (configurable).
AVWAP band engine (15m native)
• Bands: ±1σ / ±2σ / ±3σ with EMA smoothing and optional σ cap.
• Settling bars after anchor (default 1–3) to reduce immediate whipsaws.
Entry toggles
• Enable/disable A, B, C, D, E, F individually.
• Optional CVD gate (on/off), lookback window and reversal thresholds.
Housekeeping
• Debounce per ticker and per entry type.
• Entry window length (default 1 week) and per-type cap (show top 3 per event).
• Webhook on/off.
---
## Entries (A–F)
These are right-side confirmations; each requires first touching the prerequisite lower band before reclaiming a higher one.
A Touch ≤ −2σ, then cross up through −1σ (classic exhaustion → relief).
B Touch ≤ −1σ, then reclaim AVWAP (crowd average changes hands).
C Break −1σ up, retest near −1σ within N bars, then bounce (retest confirmation).
D After compression (low ATR%), reclaim AVWAP (coiled spring).
E Touch ≤ −2σ, then reclaim AVWAP after a base (deeper flush → stronger reclaim).
F Touch ≤ −3σ, then cross up through −1σ (capitulation → violent mean reversion).
Optional CVD gate (15m): require sell-pressure exhaustion and a CVD turn-up before validating entries. Defaults are conservative so that A/F remain the highest-quality.
---
## Alert payload (minimal by design)
On event close, one alert is fired with a tiny JSON:
{
"event": "step2_signal",
"symbol": "TSLA",
"ts_15m_ms": 1730879700000
}
Use “Once per bar close” and the 15-minute chart. Your webhook receiver can enrich with fundamentals/news and decide Allow / Hold / Reject, then monitor A–F entries for execution.
---
## How to use
1. Run on your 15-minute chart with extended session enabled.
2. Create one alert per chart (or use TradingView’s multi-chart / watchlist alerts if you have Pro+).
3. Your backend ingests the minimal payload, fetches news and fundamentals, and returns a decision.
4. For Allowed names, watch the on-chart A–F labels; scale in across levels, scale out into upper HVNs/POC or AVWAP give-back.
---
## Defaults that work well
• RSI(1h) < 30
• Depth vs yesterday’s RTH ref: ≤ −4% (16 bars), ≤ −6% (32 bars)
• Relative to market/sector: ≤ −3% (16 bars), ≤ −4% (32 bars)
• Macro fuses: VIX day change ≤ +10%; market ≤ −2.0% / −3.0%; sector ≤ −2.5% / −3.5%
• AVWAP bands: EMA(σ)=3; σ cap off; settle ≥ 1 bar
• CVD gate off initially; enable after you’re comfortable with its behavior.
---
## Notes & limitations
• Indicator, not a strategy: it proposes event points and entries; position sizing and exits are up to you.
• Designed for US equities with ample liquidity; thin names will be noisy.
• Repainting: AVWAP and bands are anchored and do not repaint; entries are evaluated on bar close.
• To keep charts readable, we limit entry labels to the first three occurrences per type within the one-week window.
---
## What’s new in v3.3
• 15-minute event engine (always 15m, independent of the chart you view).
• Depth measured vs yesterday’s RTH VWAP/CLOSE (the lower of the two).
• Removed structure-health (SMA50 coverage) and MA50/200 position checks.
• Macro circuit breakers: VIX + market + sector thresholds; any one trips a fuse.
• RSI guard moved to 1-hour.
• AVWAP bands include ±3σ and new Entry F (−3σ → −1σ reclaim).
• Optional 15m CVD gate for entries.
• Minimal webhook payload for fast downstream AI checks.
• Debounce + entry-window caps to prevent over-labeling and to focus the week after the event.
• Numerous performance and stability tweaks in the 15m security sandbox.
---
## Disclaimer
This is a research tool. It does not constitute investment advice. Test in Replay first, start with small size, and respect your risk.
Swing Point BulbThe Swing Point Bulb indicator identifies key swing reversal points in price movement by using a two-tier adaptive wave algorithm.
It marks areas on the chart where market momentum has likely reached exhaustion (overbought or oversold conditions), signaling potential trend reversals or continuation pivots.
The tool automatically plots color-coded bulbs at critical swing highs and lows:
🟡 Minor Bulbs – short-term swings or micro pullbacks
🔴 Major High Bulbs – potential tops, overbought or distribution zones
🟢 Major Low Bulbs – potential bottoms, oversold or accumulation zones
This design allows traders to visualize market rhythm and turning points clearly without clutter or lag.
How to Use
Identify Swing Zones
Watch for new bulbs forming at highs or lows — they mark potential reversal zones.
Red bulbs → Watch for short or take-profit setups.
Green bulbs → Watch for long or buy setups.
Yellow bulbs → Confirm minor pullbacks within ongoing trends.
Confirm with Market Context
Use these bulbs together with volume, RSI, or structure breaks to confirm momentum exhaustion.
Stronger reactions occur when major bulbs align with key support or resistance areas.
Trading Approach
Enter in the direction of the reversal bulb only after confirmation from price action.
Manage risk below/above the most recent opposite bulb.
Combine higher-timeframe major bulbs with lower-timeframe minor bulbs for best results.
Combined VWAP Doji & RSI Volume StrategyCombine strategy of VWAP DOJI and RSI volume 60-40 crossover buy sell signal
Machine Learning Moving Average [BackQuant]Machine Learning Moving Average
A powerful tool combining clustering, pseudo-machine learning, and adaptive prediction, enabling traders to understand and react to price behavior across multiple market regimes (Bullish, Neutral, Bearish). This script uses a dynamic clustering approach based on percentile thresholds and calculates an adaptive moving average, ideal for forecasting price movements with enhanced confidence levels.
What is Percentile Clustering?
Percentile clustering is a method that sorts and categorizes data into distinct groups based on its statistical distribution. In this script, the clustering process relies on the percentile values of a composite feature (based on technical indicators like RSI, CCI, ATR, etc.). By identifying key thresholds (lower and upper percentiles), the script assigns each data point (price movement) to a cluster (Bullish, Neutral, or Bearish), based on its proximity to these thresholds.
This approach mimics aspects of machine learning, where we “train” the model on past price behavior to predict future movements. The key difference is that this is not true machine learning; rather, it uses data-driven statistical techniques to "cluster" the market into patterns.
Why Percentile Clustering is Useful
Clustering price data into meaningful patterns (Bullish, Neutral, Bearish) helps traders visualize how price behavior can be grouped over time.
By leveraging past price behavior and technical indicators, percentile clustering adapts dynamically to evolving market conditions.
It helps you understand whether price behavior today aligns with past bullish or bearish trends, improving market context.
Clusters can be used to predict upcoming market conditions by identifying regimes with high confidence, improving entry/exit timing.
What This Script Does
Clustering Based on Percentiles : The script uses historical price data and various technical features to compute a "composite feature" for each bar. This feature is then sorted and clustered based on predefined percentile thresholds (e.g., 10th percentile for lower, 90th percentile for upper).
Cluster-Based Prediction : Once clustered, the script uses a weighted average, cluster momentum, or regime transition model to predict future price behavior over a specified number of bars.
Dynamic Moving Average : The script calculates a machine-learning-inspired moving average (MLMA) based on the current cluster, adjusting its behavior according to the cluster regime (Bullish, Neutral, Bearish).
Adaptive Confidence Levels : Confidence in the predicted return is calculated based on the distance between the current value and the other clusters. The further it is from the next closest cluster, the higher the confidence.
Visual Cluster Mapping : The script visually highlights different clusters on the chart with distinct colors for Bullish, Neutral, and Bearish regimes, and plots the MLMA line.
Prediction Output : It projects the predicted price based on the selected method and shows both predicted price and confidence percentage for each prediction horizon.
Trend Identification : Using the clustering output, the script colors the bars based on the current cluster to reflect whether the market is trending Bullish (green), Bearish (red), or is Neutral (gray).
How Traders Use It
Predicting Price Movements : The script provides traders with an idea of where prices might go based on past market behavior. Traders can use this forecast for short-term and long-term predictions, guiding their trades.
Clustering for Regime Analysis : Traders can identify whether the market is in a Bullish, Neutral, or Bearish regime, using that information to adjust trading strategies.
Adaptive Moving Average for Trend Following : The adaptive moving average can be used as a trend-following indicator, helping traders stay in the market when it’s aligned with the current trend (Bullish or Bearish).
Entry/Exit Strategy : By understanding the current cluster and its associated trend, traders can time entries and exits with higher precision, taking advantage of favorable conditions when the confidence in the predicted price is high.
Confidence for Risk Management : The confidence level associated with the predicted returns allows traders to manage risk better. Higher confidence levels indicate stronger market conditions, which can lead to higher position sizes.
Pseudo Machine Learning Aspect
While the script does not use conventional machine learning models (e.g., neural networks or decision trees), it mimics certain aspects of machine learning in its approach. By using clustering and the dynamic adjustment of a moving average, the model learns from historical data to adjust predictions for future price behavior. The "learning" comes from how the script uses past price data (and technical indicators) to create patterns (clusters) and predict future market movements based on those patterns.
Why This Is Important for Traders
Understanding market regimes helps to adjust trading strategies in a way that adapts to current market conditions.
Forecasting price behavior provides an additional edge, enabling traders to time entries and exits based on predicted price movements.
By leveraging the clustering technique, traders can separate noise from signal, improving the reliability of trading signals.
The combination of clustering and predictive modeling in one tool reduces the complexity for traders, allowing them to focus on actionable insights rather than manual analysis.
How to Interpret the Output
Bullish (Green) Zone : When the price behavior clusters into the Bullish zone, expect upward price movement. The MLMA line will help confirm if the trend remains upward.
Bearish (Red) Zone : When the price behavior clusters into the Bearish zone, expect downward price movement. The MLMA line will assist in tracking any downward trends.
Neutral (Gray) Zone : A neutral market condition signals indecision or range-bound behavior. The MLMA line can help track any potential breakouts or trend reversals.
Predicted Price : The projected price is shown on the chart, based on the cluster's predicted behavior. This provides a useful reference for where the price might move in the near future.
Prediction Confidence : The confidence percentage helps you gauge the reliability of the predicted price. A higher percentage indicates stronger market confidence in the forecasted move.
Tips for Use
Combining with Other Indicators : Use the output of this indicator in combination with your existing strategy (e.g., RSI, MACD, or moving averages) to enhance signal accuracy.
Position Sizing with Confidence : Increase position size when the prediction confidence is high, and decrease size when it’s low, based on the confidence interval.
Regime-Based Strategy : Consider developing a multi-strategy approach where you use this tool for Bullish or Bearish regimes and a separate strategy for Neutral markets.
Optimization : Adjust the lookback period and percentile settings to optimize the clustering algorithm based on your asset’s characteristics.
Conclusion
The Machine Learning Moving Average offers a novel approach to price prediction by leveraging percentile clustering and a dynamically adapting moving average. While not a traditional machine learning model, this tool mimics the adaptive behavior of machine learning by adjusting to evolving market conditions, helping traders predict price movements and identify trends with improved confidence and accuracy.
Reversal & Follow The Trend Signal for XAUUSD [aganac3]A hybrid trend–reversal & trend-continuation system for Gold (XAUUSD, 5-minute) that merges two engines:
1. FTT (Follow-The-Trend / Trend Continuation logic) from the Reversal & Follow The Trend family.
2. Zone Oscillator Filter, an internal momentum filter confirming whether the market’s underlying force supports a Buy or Sell setup.
The purpose is to detect high-probability reversal or continuation entries, filter out low-momentum noise, and provide clear visual HUD, TP/SL levels, and alert messages ready for automation or manual trading.
⚙️ Core Components and Features
1. Helper & Input Parameters
RSI / EMA / ATR system: defines short-term bias and volatility context.
1. Sensitivity modes:
Aggressive – fast signals, looser filters
Normal – balanced setup
Conservative – slower, high-confidence signals
2. Higher Timeframe (HTF) confirmation: secondary EMA trend from the 30-minute chart.
3. Signal Cooldown: prevents consecutive entries within X bars to avoid over-trading.
4. Flexible alert options: choose Both, Buy Only, Sell Only, or None.
⚙️Market Structure & Zone Logic
The script constantly scans for demand and supply zones:
Demand Zone: price sits in the lower 35% of the recent 35-bar range.
Supply Zone: price sits in the upper 35% of the same range.
This defines potential reversal zones, later combined with RSI, momentum, and candle pattern conditions.
⚙️Momentum, Volume & Pattern Engine
1. RSI Slope + Rate of Change: creates a composite “pressure” signal to read buying/selling acceleration.
2. Volume & ATR spikes: confirm when volatility and participation rise sharply.
3. Candle patterns:
Bullish engulfing / pin bar → potential upward reversal
Bearish engulfing / pin bar → potential downward reversal
All these elements contribute to the Confidence Score (0–100%) for each direction.
⚙️Adaptive Confidence System
The script calculates a weighted confidence blend of:
1.RSI displacement
2.Zone location (Demand/Supply)
3.ATR activity
4.Distance from EMA
5.Momentum bursts
6.HTF trend alignment
It produces:
Bullish Probability
Bearish Probability
Both normalized via a sigmoid curve (0–100%).
The highest probability defines the current market bias and feeds into the HUD display and signal logic.
⚙️Zone Oscillator Filter (Internal Indicator #2)
This module acts as an FTT-momentum validator:
1. Measures how far price is from the EMA, normalized by ATR.
-Smoothed with a small EMA (smoothLen = 3).
-Defines three states:
BUY Zone: oscillator ≥ +0.5 → bullish momentum confirmed.
SELL Zone: oscillator ≤ –0.5 → bearish momentum confirmed.
Neutral: between thresholds.
Only signals that agree with this filter are allowed to print on chart (for example, a BUY signal only appears when the Zone Osc confirms a bullish area).
⚙️HUD (Head-Up Display)
⚙️Signal Generation Logic
1. BUY / SELL – Reversal Mode
Triggered when:
-Probability ≥ threshold (default 70%)
-Zone alignment (Demand for BUY, Supply for SELL)
-Valid candle pattern + volume/ATR spike
-Directional confirmation (close > open for BUY etc.)
-Reversal-Gate condition: price deviated by ≥ 1.2× ATR from EMA (anti-false-signal gate)
-HTF agrees (no conflict with higher-timeframe trend)
2.FTT (Follow-The-Trend) Mode
Triggered when:
-Trend direction confirmed on both M5 & HTF
-Pullback within ATR range (0.6×) and rebound confirmed by pressure or pattern
-Minimum confirmation count achieved (default 2)
3. Zone Osc Filter
Even after all above, signals are suppressed unless the Zone Oscillator agrees with direction (i.e. only show BUY inside BUY Zone, SELL inside SELL Zone).
4. Cooldown Enforcement
After any valid signal, system pauses new entries until cooldown bars elapse.
⚙️TP/SL Management System based on ATR
⚙️Alert System
🎯 How to Interpret
1. Check the HUD first:
Confidence > 70% → potential entry zone.
Zone Osc = BUY ZONE → only look for BUY REV/FTT.
Zone Osc = SELL ZONE → only look for SELL REV/FTT.
2. Wait for valid signal marker (triangle for REV, cross for FTT).
3. Observe TP/SL lines for realistic trade targets.
4. Respect Cooldown Timer to avoid overlapping entries.
Omega Trend IndicatorIdentifying market trends is crucial for success in trading and investing. A trend is the general direction—upward (bullish), downward (bearish), or sideways (flat)—that the price of an asset or the overall market takes over a period of time.
The Omega Trend Indicator is a very simple (Keep it simple!) instrument to help you avoid longing in bearish trends and shorting in bullish trends - and to identify potential ranging markets.
The System is simple and easy to understand, it consists of a fast and slow EMA that is used in institutional trading.
Rules:
Pick your Anchor Timeframes, for example DAILY.
When Price is above RED = look for longs.
When Price is below RED = look for shorts.
The slower EMA GREEN provides additional HTF trend confirmation. Big trends happen when the EMAs stack, that means:
Big bullish moves = Price > RED > GREEN
Big bearish moves = Price < RED < GREEN
The area between RED and GREEN can be considered as a potentially RANGING market. In such a case, Lower Timeframes provice opportunities within that range. Apply the same rules (look for Timeframes with correctly stacked EMAs).
Good luck.
hbd.mozanitstones - GoldThis PineScript indicator code aims to create an advanced composite trading system and generates buy/sell signals by combining multiple technical analyses. Essentially, the system utilizes a composite scoring mechanism using trend filters based on moving averages (EMA 50 and EMA 200) and various oscillators (such as RSI, MACD, and Stochastic) to support buy and sell decisions. It also integrates advanced confirmation tools such as the Multi-Timeframe (MTF) EMA filter, along with additional filters such as SuperTrend, Bollinger Bandwidth, and Volume Ratio. The code's key feature is that it generates final signals that meet both traditional signal conditions and the minimum number of confirmations achieved by weighting these various indicators, thus increasing signal reliability.
