Daily/Weekly FVG by KrisThis indicator is a Multi-Timeframe (MTF) tool designed to automatically identify and project Fair Value Gaps (Imbalances) from Daily and Weekly timeframes onto your current chart. It helps traders locate higher-timeframe Areas of Interest (POI) and liquidity voids without manually switching charts.
How it works:
The script utilizes `request.security` to fetch High and Low data from Daily and Weekly timeframes. It identifies a Fair Value Gap (FVG) based on the 3-candle formation logic where price moves inefficiently, leaving a gap between the wicks.
- Bullish FVG: Identified when the current Daily/Weekly Low is greater than the High of the candle from 2 periods ago.
- Bearish FVG: Identified when the current Daily/Weekly High is lower than the Low of the candle from 2 periods ago.
The indicator draws a box extending to the right to visualize the zone, along with a dotted midline which often acts as a sensitive support/resistance level.
Unique Feature: Smart Mitigation (Auto-Hide)
To keep your chart clean and focused on relevant data, the script includes a "Full Fill" logic. It continuously monitors price action relative to existing FVG boxes.
- If price completely crosses through a box (fully fills the gap), the indicator considers it "mitigated" and automatically hides the box and its midline (sets transparency to 100%).
- This ensures you only see "fresh" or unfilled gaps that are still relevant for trading.
Settings:
- TF Checkboxes (Daily/Weekly FVG): Toggle the visibility of Daily or Weekly gaps independently based on your analysis needs.
- Design Mode:
Colored: Uses classic Green (Bullish) and Red (Bearish) colors for easy trend identification.
Monochrome: Uses Gray tones for a minimalist look that reduces visual noise on the chart.
Usage:
Use these zones to identify potential reversal points or liquidity targets. Since these are higher-timeframe levels, they often carry more weight than intraday imbalances.
インジケーターとストラテジー
EDUVEST Lorentzian ClassificationEDUVEST Lorentzian Classification - Machine Learning Signal Detection
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█ ORIGINALITY
This indicator enhances the original Lorentzian Classification concept by jdehorty with EduVest's visual modifications and alert system integration. The core innovation is using Lorentzian distance instead of Euclidean distance for k-NN classification, providing more robust pattern recognition in financial markets.
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█ WHAT IT DOES
- Generates BUY/SELL signals using machine learning classification
- Displays kernel regression estimate for trend visualization
- Shows prediction values on each bar
- Provides trade statistics (Win Rate, W/L Ratio)
- Includes multiple filter options (Volatility, Regime, ADX, EMA, SMA)
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█ HOW IT WORKS
【Lorentzian Distance Calculation】
Unlike Euclidean distance, Lorentzian distance uses logarithmic transformation:
d = Σ log(1 + |xi - yi|)
This provides:
- Better handling of outliers
- More stable distance measurements
- Reduced sensitivity to extreme values
【Feature Engineering】
The classifier uses up to 5 configurable features:
- RSI (Relative Strength Index)
- WT (WaveTrend)
- CCI (Commodity Channel Index)
- ADX (Average Directional Index)
Each feature is normalized using the n_rsi, n_wt, n_cci, or n_adx functions.
【k-Nearest Neighbors Classification】
1. Calculate Lorentzian distance between current bar and historical bars
2. Find k nearest neighbors (default: 8)
3. Sum predictions from neighbors
4. Generate signal based on prediction sum (>0 = Long, <0 = Short)
【Kernel Regression】
Uses Rational Quadratic kernel for smooth trend estimation:
- Lookback Window: 8
- Relative Weighting: 8
- Regression Level: 25
【Filters】
- Volatility Filter: Filters signals during extreme volatility
- Regime Filter: Identifies market regime using threshold
- ADX Filter: Confirms trend strength
- EMA/SMA Filter: Trend direction confirmation
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 15M, 1H, 4H, Daily
- Neighbors Count: 8 (default)
- Feature Count: 5 for comprehensive analysis
【Signal Interpretation】
- Green BUY label: Long entry signal
- Red SELL label: Short entry signal
- Bar colors: Green (bullish) / Red (bearish) prediction strength
【Trade Statistics Panel】
- Winrate: Historical win percentage
- Trades: Total (Wins|Losses)
- WL Ratio: Win/Loss ratio
- Early Signal Flips: Premature signal changes
【Filter Recommendations】
- Enable Volatility Filter for ranging markets
- Enable Regime Filter for trend confirmation
- Use EMA Filter (200) for higher timeframes
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█ CREDITS
Original Lorentzian Classification concept and MLExtensions library by jdehorty.
Enhanced with visual modifications and alert integration by EduVest.
License: Mozilla Public License 2.0
Price Compression Scanner (Chartink Logic)Breakout above range high → BUY
🔹 Breakdown below range low → SELL
🔹 Best with volume expansion
🔹 Works well for swing trades & momentum breakouts
Highs
Highest High of last 10 days (ending 1 day agos) < Highest High of previous 10 days
Highest High of last 10 days < Highest High of earlier 10 days
➡️ Lower highs (falling resistance)
Lows
3. Lowest Low of last 10 days > Lowest Low of previous 10 days
4. Lowest Low of last 10 days > Lowest Low of earlier 10 days
SMA Cross + Adaptive Q MA + AMA Channel
📘 OPERATIONAL MANUAL: Adaptive Trend & SR Breakout SystemThis system combines non-parametric regression, volatility channels, and automated price action structures to identify high-probability entries.
1. Core IndicatorsAdaptive Q (KAMA): The primary trend line.
Green = Bullish;
Red = Bearish.
AMA Channel: An ATR-based envelope ($1.5 \times ATR$) that defines the "Value Area".
SMA 50 Filter: Global trend filter. Trade Long only above; Short only below.
SR Zones: Automatic boxes marking historical Support
(Blue/Green) and Resistance (Red).Shutterstock
2. Entry Rules
🟢 LONG SETUP:Price is above SMA 50.Large Lime Triangle appears (Channel Cross).Adaptive Q line is Green.Best entry: Price bounces off a Support Box.
🔴 SHORT SETUP:Price is below SMA 50.Large Red Triangle appears (Channel Cross).Adaptive Q line is Red.Best entry: Price rejects a Resistance Box.
3. Risk Management
Stop Loss: Set at $1.5 \times ATR$ or behind the nearest SR Box.
Take Profit: Target the next opposite SR Zone or exit if the Adaptive Q changes color.
4. LegendLarge Triangles: High-conviction volatility signals.
Small Triangles: Standard SMA Cross (early warning).
Red/Green Boxes: Supply and Demand zones for structural confirmation.
ADR% / ATR / LoD dist. Table - V2ADR% / ATR / LoD Distance Table (V2) + ATR Range Lines is a simple “daily volatility dashboard” that helps you quickly judge how extended a stock is during the day and where “normal” daily movement zones sit relative to price.
It’s designed to help you answer:
“Has this stock already made most of its usual daily move?”
“Am I chasing too late?”
“Where are typical +ATR / −ATR stretch and pullback zones?”
What you’ll see
ADR% (Average Daily Range %)
Shows the stock’s typical daily travel (low → high) as a percentage.
Example: ADR% = 4% means the stock often swings ~4% in a normal day.
ATR (Average True Range)
Shows the stock’s typical daily movement in price units ($ / points).
Example: ATR = 2.50 means it often moves about $2.50 per day.
LoD dist. (Low of Day distance)
Shows how far price is from today’s Low of Day, measured relative to ATR (as a %).
Higher % = more extended away from the day’s low.
Optional: ATR Range Lines (added in this version)
You can enable two guide lines that extend to the right:
ATR Up Line = Price + ATR
ATR Down Line = Price − ATR
These act like volatility guardrails to visualize “typical daily stretch” and “typical pullback” zones.
ATR “Live vs Locked” option (important)
Lock ATR to last completed day (no intraday updates):
ON (Locked): Uses the last completed daily ATR (yesterday’s finished value).
✅ ATR stays constant all day while the market is live.
OFF (Live): ATR can update intraday as today’s daily candle expands.
✅ ATR may change during the session.
Either way, ATR is still based on your chosen ATR Length (lookback period). Locking simply prevents the ATR from drifting intraday.
How to use it (Kullamägi-style principle)
Kristjan Kullamägi’s momentum style emphasizes pressing strength when conditions are right, but also respecting extension and risk/reward. This tool helps you quantify that:
If ADR%/ATR suggests the stock already moved near its usual daily range, chasing can be lower reward.
The ATR lines help you visualize when price is in a “normal stretch zone” vs a better risk area.
Locking ATR gives you stable intraday reference levels for cleaner execution.
Tips
Use ADR% to understand whether there’s likely “room” left in today’s move.
Use LoD dist. to quickly gauge if price is already far from the day’s low (extended).
Use ATR Up/Down Lines as a simple volatility framework for entries, add-ons, and risk planning.
Keep Lock ATR ON if you prefer stable levels throughout the session.
Credits
Original indicator concept & script: ArmerSchlucker
ADR% formula credit: MikeC / TheScrutiniser and GlinckEastwoot
Modifications (V2): TradersPod
Added optional ATR Up/Down lines extending to the right
Added “Lock ATR to last completed day” option for stable intraday ATR reference
Kept the original logic and purpose intact
Percentage Price LevelsPercentage Price Levels displays dynamic price levels based on percentage gains and losses from the current price. Instantly visualize where price would be at ±2%, ±4%, ±6%, ±8%, ±10%(and beyond) — perfect for setting profit targets, stop-losses, and understanding potential price movement.
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🎯 WHAT IT DOES
• Draws horizontal lines at percentage-based price levels above and below current price
• Green lines = potential profit targets (positive %)
• Red lines = potential stop-loss zones (negative %)
• Yellow line = current price reference
• Summary table shows all levels in a clean, easy-to-read format
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⚙️ FEATURES
• Up to 8 positive and 8 negative percentage levels
• Fully customizable percentages (set your own values)
• Toggle each level on/off individually
• Adjustable font size (Tiny to Huge)
• Multiple line styles (Solid, Dashed, Dotted)
• Movable summary table (any corner)
• Base price options: Close, Open, High, Low, HL2, OHLC4
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📈 HOW TO USE
1. Add the indicator to your chart
2. Default shows ±2%, ±4%, ±6%, ±8%, ±10% levels
3. Open Settings to customize:
• Enable/disable specific levels
• Change percentage values
• Adjust colors and font size
• Move table position
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💡 USE CASES
• Day Trading — Quick intraday profit targets
• Swing Trading — Visualize multi-day price zones
• Risk Management — Set stop-losses based on % risk tolerance
• Options Trading — Find strike prices relative to spot
• Position Sizing — See exact dollar values at each level
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🔧 DEFAULT SETTINGS
Positive: +2%, +4%, +6%, +8%, +10% (3 extra slots available)
Negative: -2%, -4%, -6%, -8%, -10% (3 extra slots available)
Font Size: Normal
Line Style: Dashed
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If you find this useful, please leave a like! Feedback and suggestions welcome in the comments.
7-13 Sequential CounterThis indicator displays a sequential count (7-13) setup phase. It tracks consecutive bars where the close is lower than the close 4 bars ago (bullish/buy count, labeled below bars) or higher (bearish/sell count, labeled above bars), resetting on interruption or after 13. Toggle individual numbers (I personally use 7,9,13) and customize bullish/bearish label colors to spot potential trend exhaustion and reversal points.
CVD Complete Volume Analysis ProCVD Complete Volume Analysis Pro | Order Flow & Absorption
Introduction:
In the world of modern trading, Price is the advertisement, but Volume is the fuel. However, standard volume indicators on TradingView are often insufficient. They tell you how much was traded, but they don’t tell you how it was traded.
Was that large volume spike aggressive buying driving the trend? or was it a "buying frenzy" hitting a wall of passive limit orders (absorption)?
The CVD Complete Volume Analysis Pro (v5) is an advanced institutional-grade Order Flow engine. By utilizing 1-second intrabar data, this indicator reconstructs the "Tick Rule" to separate Aggressive (Market) orders from Passive (Limit) orders. It calculates Cumulative Volume Delta (CVD), detects Absorption/Distribution anomalies, and utilizes an embedded Logistic Regression model to predict daily directional bias.
This is not just an indicator; it is a complete Order Flow Dashboard designed to aid and support complex footprint charts for the everyday trader.
🏗️ How It Works: The "Micro-Structure" Engine
Most volume indicators on TradingView look at the close of a 1-minute or 5-minute bar to guess the volume direction. This script goes deeper.
1. The 1-Second Granularity
Using TradingView's request.security_lower_tf capability, this script pulls 1-second resolution data regardless of the chart timeframe you are on.
It analyzes the price movement every second.
It applies the "Tick Rule": If price moves up, volume is classified as Buy. If price moves down, volume is classified as Sell.
This allows for a highly accurate reconstruction of Buying vs. Selling pressure that standard indicators miss.
2. The "Cluster" Concept
The script aggregates these 1-second data points into Clusters.
Default: 60 seconds (1 minute) per cluster.
This creates a normalized "Heartbeat" of the market, allowing us to compare the efficiency of volume over fixed time windows, removing the noise of time-based chart distortions.
3. The "Passive" Detection Logic (The Core Feature)
This is the most powerful aspect of the tool. It calculates the relationship between Effort (CVD) and Result (Price Move).
The Baseline: The script calculates a rolling statistical baseline (Standard Deviation) of how much price should move for a given amount of Delta.
Absorption (Hidden Buying): If we see massive Aggressive Selling (Negative CVD) but price refuses to drop (or drops significantly less than the statistical model predicts), the script identifies this as Passive Buying.
Distribution (Hidden Selling): If we see massive Aggressive Buying (Positive CVD) but price refuses to rise, the script identifies this as Passive Selling.
📊 The Dashboard Breakdown
The on-screen dashboard is your command center. It updates in real-time to provide a snapshot of the market's internal mechanics.
Section 1: Flow Analysis
This section analyzes the current session's behavior.
Flow Type: Categorizes the market state using algorithmic logic.
Aggressive Buying/Selling: The market is trending, and aggressive participants are winning.
Strong Accumulation/Distribution: A reversal signal. Aggressive participants are trapped, and passive whales are absorbing order flow.
Flow vs. Price: Detects divergences instantly.
Bullish Divergence: Net Flow is Positive, but Price is down (indicates manipulation or temporary suppression).
Bearish Divergence: Net Flow is Negative, but Price is up (indicates a "trap" move).
Section 2: Volume Breakdown
A detailed ledger of the day's activity.
Aggressive Buy/Sell: Market orders executing at the ask/bid. This represents "Impatience."
Passive Buy/Sell: The estimated volume of Limit Orders absorbing the aggressive flow. This represents "Intent."
Net Flow: The mathematical sum of all buy pressure minus sell pressure.
Section 3: Net Positioning (Multi-Day)
Markets don't happen in a vacuum. This section looks back (default 5 days) to see the accumulated inventory.
Bias: Are we in a multi-day accumulation or distribution phase?
Activity Type:
High Hidden Activity: Indicates a fighting market with heavy limit orders (choppy/reversal prone).
Mostly Aggressive: Indicates a trending market with low resistance.
Section 4: Predictive Model (Machine Learning)
The script features an embedded Logistic Regression Model.
It trains on the last N days of Flow Data (CVD, Net Aggressive, Net Passive, Passive Ratios).
It outputs a Probability Score (0% to 100%) regarding the likelihood of an UP close for the current session.
Note: This is a probability model based on order flow history, not a guarantee. Use it as a bias confirmation tool.
🧠 Educational: How to Trade With This
Strategy 1: The "Absorption" Reversal
Context: Price hits a major resistance level.
Look at the Dashboard: You want to see "Flow Type" switch to "Strong Distribution".
The Logic: Price is rising, and aggressive buyers are hitting the ask. However, the script detects that for every buy order, a passive seller is absorbing it. Price stops moving up despite high volume.
The Trigger: When Price creates a lower low on the chart while the dashboard shows Distribution, this is a high-probability short entry.
Strategy 2: The Flow Divergence
Context: Price is trending down.
Look at the Dashboard: Price is making new lows, but the "Net Flow" is turning Green (Positive), or the "Cum CVD" is sloping upwards.
The Logic: This is "Effort vs. Result." Sellers are exhausted. They are pushing price down, but the net flow is shifting to buyers.
The Trigger: Enter Long on the first structure break.
Strategy 3: Trend Continuation
Context: Market is opening or breaking a range.
Look at the Dashboard: You want "Full Alignment."
Signals: "Flow Type" says Aggressive Buying, Net Flow is Positive, and the Predictive Model shows >60% Bullish Probability.
The Logic: There is no passive resistance. Aggressive buyers are pushing price up freely.
The Trigger: Buy pullbacks.
⚙️ Settings & Configuration
Cluster Size: The number of 1-second bars to group together.
Use 60 (1 min) for Scalping.
Use 300 (5 min) for Day Trading.
Average Length: The baseline for statistical calculations. Higher numbers = smoother baselines but slower adaptation.
Detection Settings:
Passive Multiplier: Adjusts the sensitivity of the absorption estimation. 1.0 is standard. Increase to 1.5 if you only want to see extreme anomalies.
Daily Tracking:
History Days: How many days of data to display in the table. Note: Due to TradingView data limits, keeping this between 3-5 days ensures the most stability.
⚠️ Important Technical Limitations
Please read this section carefully to understand the constraints of the Pine Script environment:
Data Depth (The 100k Limit): TradingView limits request.security_lower_tf to approximately 100,000 intrabars.
This means the script can typically only "see" the last 3 to 5 days of true 1-second data.
If you set History Days or Training Days too high (e.g., 20 days), the script may return 0 values for older dates because the high-resolution data simply doesn't exist on the server.
Approximation of Ticks: While 1-second data is extremely precise, it is still an aggregation. In extremely high-volatility events (like CPI releases), multiple ticks happen inside one second. The script attributes the volume of that second based on the close relative to the open/prev close. It is the best approximation possible on TradingView, but not a replacement for Level 3 Tick Data feeds.
Calculation Time: This is a heavy script. On lower-end devices or when loading on many charts simultaneously, you may experience a "Calculation took too long" warning. If this happens, reduce the History Days to 3.
🛡️ Disclaimer
No Repainting: This indicator uses strict historical referencing and does not repaint closed clusters.
Not Financial Advice: This tool provides data visualization. Order flow is a subjective art. Always manage your risk.
Author's Note:
I built this tool because I wanted the power of Order Flow footprint charts without the visual clutter. By using statistical baselines to detect passive liquidity, we can finally see the "invisible hand" of the market directly on our TradingView charts. I hope this adds value to your trading.
👍 If you find this script useful, please leave a Boost and a Comment below!
Gann Square (Weekly) + Auto-Fit Helper v6Helps show best fit for the Gann Square on the weekly log scale chart
COT + SMI Dual Strategy (Rev/Trend)I use this script to test whether stochastic COT report filtering for trade direction makes a difference or not for forex.
It seems it does! Feel free to test and comment. I am always happy to see to be proven wrong.
Timeframe-Independent Anchored VWAPAn anchored VWAP (Volume Weighted Average Price) that produces identical values (down to the tick!) across different timeframes (unlike, for example, TradingView's built-in Anchored VWAP).
Advantages
This indicator calculates identical values whether you view it on 1m, 5m, 15m, or any other timeframe within reasonable ranges. Even challenging non-integer timeframe ratios like calculating on 2m while viewing on 3m are handled perfectly. In High or Low mode, VWAP will anchor precisely at the selected candle's high/low. As usual for AVWAP, up to 3 standard deviation bands are supported.
How to Use
Setting the Anchor: When the indicator is added, select your anchor time. This is typically placed at a significant swing high/low or session open.
Source Selection: Choose whether to anchor from High, Low, or Close price.
Calculation Timeframe: Select the timeframe used for VWAP calculation.
For intraday trading (1m-1H charts): Just keep the default setting (1m)
For swing trading (4H-D charts): Use 5m or 15m calculation timeframe
For position trading (D-W charts): Use 1H calculation timeframe
Important: Lower calculation timeframes provide more precise data but may hit Pine Script's bar limit on very long timeframes
Standard Deviation Bands: Enable additional band sets as needed for your trading style.
Technical Implementation
The indicator achieves timeframe independence through the following algorithm:
Lower Timeframe Sampling: Uses Pine Script's request.security_lower_tf() to retrieve bar data at the specified calculation timeframe, regardless of the viewing timeframe. This provides consistent data resolution across all chart timeframes.
Anchor Detection: Scans the lower timeframe data to identify the exact bar containing the selected anchor price. The algorithm handles both simple cases (where anchor falls on a complete bar) and complex cases (where anchor falls within a split bar in non-integer timeframe ratios like calculating on 2m while viewing on 3m).
FIFO Buffer Management: Maintains a First-In-First-Out buffer of lower timeframe bars. On each chart bar:
Adds new lower timeframe bars to the buffer
Processes exactly one period worth of bars (matching the viewing timeframe)
Removes processed bars from the buffer
This approach ensures consistent calculation regardless of viewing timeframe.
First Bar Initialization: On the anchor bar, processes only the single anchor bar to ensure the VWAP starts exactly at the anchor price. Subsequent bars process the full period, maintaining mathematical accuracy.
VWAP Calculation: Applies the standard volume-weighted average price formula:
VWAP = Σ(Price × Volume) / Σ(Volume)
StdDev = √(Σ(Price² × Volume) / Σ(Volume) - VWAP²)
All calculations accumulate from the anchor point forward.
Visual Continuity: For edge cases where the anchor falls in an incomplete bar (e.g., calculating on 2m while viewing on 3m), displays the anchor price as a visual placeholder until the actual calculation begins on the next bar. This ensures the line always starts visually at the anchor point.
Volume Bubbles by EV Volume Bubbles visualizes high-activity candles using chart bubbles placed at an estimated intrabar origin point derived from lower timeframe data. When enabled, the script uses lower timeframe OHLC to approximate directional volume delta and selects an origin candle inside the parent bar using one of several methods. A relative-volume filter based on the parent bar can be used to reduce noise, and bubble size can be mapped to relative volume to highlight unusually active bars. If intrabar data is unavailable, the script can fall back to placing bubbles on the parent bar to keep behavior consistent. For best stability, the “Only confirmed bars” option is recommended.
4 EMA Perfect Order + Strength + MTFリリースノート
🇯🇵 日本語説明文
📌 スクリプト概要
このスクリプトは、EMA10・20・40・80 を使用して「パーフェクトオーダー（PO）」を判定し、
PO が確定したタイミングで矢印とアラートを表示します。
さらに、PO の強さ（短期と長期 EMA の乖離率）を数値化して表示し、
上位足（MTF）でも同様の判定と強さ表示が可能です。
🔧 機能一覧
• EMA10/20/40/80 のライン表示（黒・赤・オレンジ・青）
• パーフェクトオーダー（Bull/Bear）の自動判定
• PO 確定時に矢印（▲/▼）を表示
• PO の強さ（乖離率）をリアルタイム表示
• 上位足（MTF）での PO 判定と強さ表示
• アラート条件付き（Bull/Bear PO 確定時）
• 背景は白で視認性を重視
📈 パーフェクトオーダーとは？
• Bull PO（上昇トレンド）
EMA10 > EMA20 > EMA40 > EMA80
• Bear PO（下降トレンド）
EMA10 < EMA20 < EMA40 < EMA80
PO が確定したバーで矢印とアラートが発生します。
🧠 活用例
• PO の強さを使ってトレンドの勢いを測定
• 上位足の PO と一致しているか確認して精度を向上
• トレンドフォロー戦略のフィルターとして利用
• EMA の並びが崩れたら背景色を塗るなどの拡張も可能
🇺🇸 English Description
📌 Overview
This script detects “Perfect Order” (PO) conditions using EMA10, EMA20, EMA40, and EMA80.
When a PO is confirmed, it displays arrows and triggers alerts.
It also calculates the strength of the PO (based on EMA divergence) and supports multi‑timeframe (MTF) analysis.
🔧 Features
• Displays EMA10/20/40/80 with color coding (black, red, orange, blue)
• Detects Bull and Bear Perfect Order conditions
• Shows arrows (▲/▼) when PO is confirmed
• Displays PO strength as a percentage (EMA10 vs EMA80 divergence)
• Supports MTF PO detection and strength display
• Includes alert conditions for Bull/Bear PO confirmation
• Clean white background for better visibility
📈 What is a Perfect Order?
• Bull PO (Uptrend): EMA10 > EMA20 > EMA40 > EMA80
• Bear PO (Downtrend): EMA10 < EMA20 < EMA40 < EMA80
Arrows and alerts are triggered only when the PO condition is newly confirmed.
🧠 Use Cases
• Measure trend momentum using PO strength
• Confirm alignment with higher timeframe trends
• Use as a trend‑following filter
• Can be extended with background coloring or histogram strength display
Keltner-Aroon-EFI FlowKeltner-Aroon-EFI Flow - |K| |A| |E| |F|
KAE Flow is a quantitative trend-aggregation engine designed to determine the dominant market bias by fusing three distinct market dimensions: Volatility, Trend Strength, and Volume.
This script does not rely on a single metric. Instead, it creates a composite "Flow" score derived from the Daily timeframe to act as a high-level bias filter for intraday or swing trading.
1. The Quantitative Logic (The Engine)
The core of this indicator is the KAE Engine, which polls data from the Daily timeframe (by default) to ensure you are always trading in alignment with the macro trend. It aggregates three logical components:
K (Keltner Channels): Measures Volatility Breakouts.
Logic: Returns bullish if price closes above the Upper Channel, bearish if below the Lower Channel. This captures the expansion phase of price action.
A (Aroon): Measures Trend Age & Strength.
Logic: Returns bullish only if the Aroon Up is > 70 and dominating the Aroon Down. This ensures the trend is not just present, but mathematically strong.
E (Elder’s Force Index): Measures Volume-Weighted Momentum.
Logic: Uses volume pressure to confirm price moves. Positive smoothed force indicates bullish accumulation.
2. Signal Processing (ALMA)
Raw data is noisy. The KAE Flow takes the aggregated raw score from the components above and runs it through an ALMA (Arnaud Legoux Moving Average).
Why ALMA? It offers the best balance between smoothness and responsiveness, removing "false flips" in the trend bias while reacting quickly to genuine reversals.
The Color (The Bias):
Deep Blue: Strong Bullish Flow (KAE Score > 0.1). Look for Long entries .
White: Strong Bearish Flow (KAE Score < -0.1). Look for Short entries.
Gray: Neutral/Transition. Volatility is contracting or the trend is conflicting.
5. Settings & Configuration
Keltner/Aroon/EFI Lengths: Fully customizable to fit different asset classes (Crypto vs. Forex).
Active Smoothing: Toggle ALMA on/off.
Active Components: You can toggle specific engines (K, A, or E) on or off. Default uses Keltner + Aroon for a pure Price/Time analysis.
Risk Warning: This indicator pulls higher-timeframe data (Daily) to color lower-timeframes. While this provides a powerful macro view, be aware that closed candle data is used to prevent repainting issues in real-time.
D_Quant --- Trade With Discipline
Kalman Absorption/Distribution Tracker 3-State EKFQuant-Grade Institutional Flow: 3-State EKF Absorption Tracker
SUMMARY
An advanced, open-source implementation of a 3-State Extended Kalman Filter (EKF) designed to track institutional Order Flow. By analyzing 1-second intrabar microstructure data, this script estimates the true Position, Velocity, and Volatility of the Cumulative Volume Delta (CVD), revealing hidden Absorption and Distribution events in real-time.
INTRODUCTION: THE SIGNAL AMIDST THE NOISE
In the world of technical analysis, noise is the enemy. Traditional indicators rely on Moving Averages (SMA, EMA) to smooth out price and volume data. The problem is the "Lag vs. Noise" paradox: to get a smooth signal, you must accept lag; to get a fast signal, you must accept noise.
This indicator solves that paradox by introducing aerospace-grade mathematics to the TradingView community: The 3-State Extended Kalman Filter (EKF).
Unlike moving averages that blindly average past data, a Kalman Filter is a probabilistic state-space model. It constantly predicts where the order flow "should" be, compares it to the actual measurement, and updates its internal model based on the calculated uncertainty of the market.
This script is not just another volume oscillator. It is a full microstructure analysis engine that digests intrabar data (down to 1-second resolution) to track the true intent of "Smart Money" while filtering out the noise of retail chop.
THE INNOVATION: WHY 3 STATES?
Most Kalman Filters found in public libraries are "1-State" (tracking price only) or occasionally "2-State" (tracking price and velocity). This script introduces a highly advanced 3-State EKF.
The filter tracks three distinct variables simultaneously in a feedback loop:
State 1: Position (The True CVD)
This is the noise-filtered estimate of the Cumulative Volume Delta. It represents the actual inventory accumulation of aggressive buyers versus sellers, stripped of random noise.
State 2: Velocity (The Momentum)
This tracks the rate of change of the order flow. Is buying accelerating? Is selling pressure fading even as price drops? This provides a leading signal before the cumulative value even turns.
State 3: Volatility (The Adaptive Regime)
This is the game-changer. The filter estimates the current volatility of the order flow (Log-Volatility). In high-volatility environments (like news events), the filter automatically widens its uncertainty bands (Covariance) and reacts faster. In low-volatility environments (chop), it tightens up and ignores minor fluctuations.
THE LOGIC: DETECTING ABSORPTION AND DISTRIBUTION
The core philosophy of this indicator is based on Wyckoff Logic: Effort vs. Result.
-- Effort: Represented by the CVD (Buying/Selling pressure).
-- Result: Represented by Price Movement.
When these two diverge, we have an actionable signal. The script uses the EKF Velocity state to detect these moments:
Absorption (Bullish)
This occurs when the EKF detects high negative Velocity (aggressive selling), but Price refuses to drop. The "Smart Money" is absorbing the sell orders via limit buys. The indicator highlights this as a Blue Event in the dashboard.
Distribution (Bearish)
This occurs when the EKF detects high positive Velocity (aggressive buying), but Price refuses to rise. Limit sellers are capping the market. The indicator highlights this as an Orange Event.
TECHNICAL DEEP DIVE: UNDER THE HOOD
For the developers and quants, here is how the Pine Script is architected using the "type" and "method" features of Pine Script v5.
1. Data Ingestion (Microstructure)
The script uses "request.security_lower_tf" to pull intrabar data regardless of your chart timeframe. This allows the script to see "inside" the bar. A 5-minute candle might look green, but the microstructure might reveal that 80% of the volume was selling absorption at the wick. This script sees that.
2. Tick Classification
Standard CVD assumes that if Price Close is greater than Price Open, all volume is buying. This is often flawed. This script offers three modes of tick handling, including a "High-Low Distribution" method that statistically apportions volume based on where the tick closed relative to its high and low.
3. The EKF Mathematics
The script implements the standard Extended Kalman Filter equations manually. It calculates the Jacobian matrix to handle the non-linear relationship between volatility and price. The "Process Noise Matrix" (Q) is dynamically scaled by the Volatility State. This means the mathematics of the indicator literally "breathe" with the market conditions—expanding during expansion and contracting during consolidation.
THE DASHBOARD & VISUALS:
The indicator features a professional-grade HUD (Heads Up Display) located on the chart table.
-- EKF State Vector: Displays the real-time Position, Velocity, and Volatility values derived from the matrix.
-- Ease of Movement (Wyckoff): Calculates how much price moves per 1,000 contracts of CVD. For example, if Price moves +5 points per 1k Buy CVD, but only -2 points per 1k Sell CVD, the "Path of Least Resistance" is clearly UP.
-- Session State: Tracks cumulative confirmed Bullish vs. Bearish events for Today, Yesterday, and the Day Before (3-Day Profile).
-- Bias Summary: An algorithmic conclusion telling you if the day is "Confirmed Bullish," "Accumulating," or "Neutral."
HOW TO TRADE THIS INDICATOR
Strategy A: The Reversal (Absorption Play)
Look for price making a Lower Low.
Look for the EKF Velocity (Histogram) to be Deep Red (High Selling Pressure).
Watch the Dashboard "Absorption" count increase.
SIGNAL: When EKF Velocity crosses back toward zero and turns grey/green, the absorption is complete. This indicates sellers are exhausted and limit buyers have control.
Strategy B: The Trend Continuation (Ease of Movement)
Check the Dashboard "Ease of Movement" section.
If "Price per +1K CVD" is significantly higher than "Price per -1K CVD", buyers are efficient.
Wait for a pullback where EKF Velocity hits the "Neutral Zone" (Gray).
SIGNAL: Enter Long when Velocity ticks positive again, aligning with the dominant Ease of Movement stats.
CONFIGURATION GUIDE:
Because this is a quant-grade tool, the settings allow for fine-tuning the physics of the filter.
-- Velocity Decay: Controls how fast momentum resets to zero. Set high (0.98) for trending markets, or lower (0.85) for mean-reverting chop.
-- Volatility Persistence: Controls how "sticky" volatility regimes are.
-- Process Noise: Increase this if the filter feels too laggy; decrease it if the filter feels too jittery (noisy).
-- Measurement Noise: Increase this to trust the Mathematical Model more than the Price Data (smoother output).
WHY OPEN SOURCE?
Complex statistical filtering is often sold behind closed doors in expensive "Black Box" algorithms. By releasing this 3-State EKF open source, the goal is to raise the standard of development on TradingView.
I encourage the community to inspect the code, specifically the "ekf_update_3state" function, to understand how matrix operations can be simulated in Pine Script to create adaptive, self-correcting indicators. And also update me for improvements.
DISCLAIMER:
This tool analyzes microstructure volume data. It requires a subscription plan that supports Intrabar inspection (Premium/Pro recommended for best results). Past performance of the Kalman Filter logic does not guarantee future results. Volume analysis is subjective and should be used as part of a comprehensive strategy.
SUGGESTED SETTINGS
-- Timeframe: Works best on 1m, 3m, or 5m charts (Intrabar data is fetched from 1S).
-- Asset Class: Highly effective on Futures (ES, NQ, BTC) and high-volume Forex/Crypto pairs where volume data is reliable.
-- Background: Dark mode recommended for Dashboard visibility.
WHAT IS A KALMAN FILTER?
Imagine driving a car into a tunnel where your GPS signal is lost.
Prediction: Your car knows its last speed (Velocity) and position. It predicts where you are every second inside the tunnel.
Update: When you exit the tunnel, the GPS connects again. The system compares where it thought you were versus where the satellite says you are.
Correction: It corrects your position and updates its estimate of your speed.
Now apply this to trading:
-- The Tunnel: Market Noise, wicks, and Fake-outs.
-- The Car: The True Market Trend.
-- This Indicator: The navigation system that tells you where the market actually is, ignoring the noise of the tunnel.
Enjoy the indicator and trade safe!
Dr. Jay Desai
(Investment Management & Derivatives Area, Gujarat University)
Multi Cycles Predictive System ML - GBM IntegratedMulti-Cycle Predictive System: The Gradient Boosting Machine (GBM) Revolution
Introduction: The Death of Static Analysis
The financial markets are not static; they are a living, breathing, and chaotic system. Yet, for decades, traders have relied on static indicators—using the same RSI settings, the same MACD parameters, and the same Moving Averages regardless of whether the market is trending, chopping, or crashing.
The Multi-Cycle Predictive System (MCPS) represents a paradigm shift. It is not just an indicator; it is an Adaptive Machine Learning Engine running directly on your chart.
By integrating a fully functional Gradient Boosting Machine (GBM), this script does not guess—it learns. It monitors 13 distinct algorithmic models, calculates their real-time accuracy against future price action, and dynamically reallocates influence to the "winning" models using gradient descent.
This is Survival of the Fittest applied to technical analysis.
1. The Core Engine: Gradient Boosting & Adaptive Learning
At the heart of the MCPS is a custom-coded Gradient Boosting Machine. While most "ML" scripts on TradingView simply average a few indicators, this system replicates the architecture of advanced data science models.
How the GBM Works:
Ensemble Prediction: The system aggregates signals from 13 different mathematical models.
Residual Calculation: It compares the ensemble's previous predictions against the actual price movement (Price Return) to calculate the error (Residual).
Gradient Descent: It calculates the gradient of the loss function. We utilize a Huber Loss Gradient, which is robust against outliers (market spikes), ensuring the model doesn't overreact to volatility.
Weight Optimization: Using a configurable learning rate, the system updates the weights of each sub-algorithm. Models that predicted correctly gain weight; models that failed lose influence.
Softmax Normalization: Finally, weights are passed through a Softmax function (with Temperature control) to convert them into probabilities that sum to 1.0.
The "Winner-Takes-All" Philosophy
A common failure in ensemble systems is "Signal Dilution"—where good signals are drowned out by bad ones.
The MCPS solves this with Aggressive Weight Concentration:
Top 3 Logic: The script identifies the top 3 performing algorithms based on historical accuracy.
The 90% Rule: It forces the system to allocate up to 90% of the total decision weight to these top 3 performers.
Result: If Ehlers and Schaff are reading the market correctly, but MACD is failing, MACD is effectively silenced. The system listens only to the winners.
2. The 13 Algorithmic Pillars
The MCPS draws from a diverse library of Digital Signal Processing (DSP), Statistical, and Momentum algorithms. It does not rely on simple moving averages.
Ehlers Bandpass Filter: Isolates the dominant cycle in price data, removing trend and noise.
Zero-Lag EMA (ZLEMA): Reduces lag to near-zero to track momentum shifts instantly.
Coppock Curve: A classic long-term momentum indicator, modified here for adaptive responsiveness.
Detrended Price Oscillator (DPO): Eliminates the trend to identify short-term cycles.
Schaff Trend Cycle (STC): A double-smoothed stochastic of the MACD, excellent for identifying cycle turns.
Fisher Transform: Converts price into a Gaussian normal distribution to pinpoint turning points.
MESA Adaptive: Uses Maximum Entropy Spectral Analysis to detect the current dominant cycle period.
Goertzel Algorithm: A DSP technique used to identify the magnitude of specific frequency components in the price wave.
Hilbert Transform: Extracts the instantaneous amplitude and phase of the price action.
Autocorrelation: Measures the similarity between the price series and a lagged version of itself to detect periodicity.
Singular Spectrum Analysis (SSA): Decomposes the time series into trend, seasonal, and noise components (Simplified).
Wavelet Transform: Analyzes data at different scales (frequencies) simultaneously.
Empirical Mode Decomposition (EMD): Splits data into Intrinsic Mode Functions (IMFs) to isolate pure cycles.
3. The Dashboard: Total Transparency
Black-box algorithms are dangerous. You need to know why a signal is being generated. The MCPS features two detailed dashboards (tables) located at the bottom of your screen.
The Weight & Accuracy Table (Bottom Right)
This is your "Under the Hood" view. It displays:
Algorithm: The name of the model.
Accuracy: The rolling historical accuracy of that specific model over the lookback period (e.g., 58.2%).
Weight: The current influence that model has on the final signal. Watch this change in real-time. You will see the system "giving up" on bad models and "betting heavy" on good ones.
Prob/Sig: The raw probability and directional signal (Up/Down).
The GBM Stats Table (Bottom Left)
Tracks the health of the Machine Learning engine:
Iterations: How many learning cycles have occurred.
Entropy: A measure of market confusion. High entropy means weights are spread out (models disagree). Low entropy means the models are aligned.
Top 3 Weight: Shows how concentrated the decision power is. If this is >80%, the system is highly confident in specific models.
Confidence & Agreement: Statistical measures of the signal strength.
4. How to Trade with MCPS
This system outputs a single, composite Cycle Line (oscillating between -1 and 1) and a background Regime Color.
Strategy A: The Zero-Cross (Trend Reversal)
Bullish: When the Cycle Line crosses above 0. This indicates that the weighted average of the top-performing algorithms has shifted to a net-positive expectation.
Bearish: When the Cycle Line crosses below 0.
Strategy B: Probability Extremes (Mean Reversion)
Strong Buy: When the Cycle Line drops below -0.5 (Oversold) and turns up. This indicates a high-probability cycle bottom.
Strong Sell: When the Cycle Line rises above +0.5 (Overbought) and turns down.
Strategy C: Regime Filtering
The background color changes based on the aggregate consensus:
Green/Lime: Bullish Regime. Look primarily for Long entries. Ignore weak sell signals.
Red/Orange: Bearish Regime. Look primarily for Short entries.
Gray: Neutral/Choppy. Reduce position size or wait.
5. Configuration & GBM Settings
The script is highly customizable for advanced users who want to tune the Machine Learning hyperparameters.
Prediction Horizon: How many days into the future are we trying to predict? (Default: 3).
Accuracy Lookback: How far back does the model check to calculate "Accuracy"?
GBM Learning Rate: Controls how fast the model adapts.
High (0.2+): Adapts instantly to new market conditions but may be "jumpy."
Low (0.05): Very stable, long-term adaptation.
Temperature: Controls the "Softmax" function. Higher temperatures allow for softer, more distributed weights. Lower temperatures force a "Winner Takes All" outcome.
Max Top 3 Weight: The cap on how much power the top 3 models can hold (Default: 90%).
6. Technical Nuances (For the Geeks)
Huber Gradient: We use Huber loss rather than MSE (Mean Squared Error) for the gradient descent. This is crucial for financial time series because price spikes (outliers) can destroy the learning process of standard ML models. Huber loss transitions from quadratic to linear error, making the model robust.
Regularization: L2 Regularization is applied to prevent overfitting, ensuring the model doesn't just memorize past noise.
Memory Decay: The model has a "fading memory." Recent accuracy is weighted more heavily than accuracy from 200 bars ago, allowing the system to detect Regime Shifts (e.g., transitioning from a trending market to a ranging market).
Disclaimer:
This tool is a sophisticated analytical instrument, not a crystal ball. Machine Learning attempts to optimize probabilities based on historical patterns, but no algorithm can predict black swan events or fundamental news shocks. Always use proper risk management.
The "Warmup Period" is required. The script needs to process 50 bars of history before the GBM engine initializes and produces signals.
Author's Note:
I built the MCPS because I was tired of indicators that stopped working when the market "personality" changed. By integrating GBM, this script adapts to the market's personality in real-time. If the market is cycling, Ehlers and Goertzel take over. If the market is trending, Coppock and ZLEMA take the lead. You don't have to choose—the math chooses for you.
Please leave a boost and a comment if you find this helpful!
Precision Trend Signal V5Strategy Logic OverviewThis indicator is a "Triple-Confirmation" trend-following system. It combines volume-weighted smoothing, immediate price action, and momentum filtering.1. Core ComponentsEMA 1 (The Trigger): Since the period is set to 1, this represents the raw price action. It acts as the fastest possible trigger to capture entries at the exact moment a trend shifts.SALMA (The Baseline): This is a double-smoothed moving average. It provides a stabilized support/resistance line that filters out market noise better than a standard SMA.Tillson T3 (The Trend Filter): Known for its low lag and extreme smoothness. We use this as a "Guardrail." We only take BUY signals when price is above the T3 and SELL signals when price is below it.RSI (The Momentum Filter): Ensures that we only enter a trade when there is sufficient strength ($> 50$ for Long, $< 50$ for Short).2. Signal Rules🚀 BUY SignalA green BUY label appears when:Crossover: EMA 1 crosses above the SALMA line.Trend: The current price is trading above the Tillson T3 line.Momentum: RSI is greater than 50.🔻 SELL SignalA red SELL label appears when:Crossunder: EMA 1 crosses below the SALMA line.Trend: The current price is trading below the Tillson T3 line.Momentum: RSI is less than 50.3. Execution & ManagementTake Profit (TP): Based on your preference, the suggested target is 2%.Alerts: The script includes alertcondition functions. You can set up TradingView alerts to send Webhooks to your quant infrastructure or bot, solving the "manual execution" problem you mentioned.
KCP Double Top/Bottom + VWAP + EMA 200 [Dr. K. C. Prakash]📌 **KCP Double Top/Bottom + VWAP + EMA 200
**
KCP Double Top/Bottom + VWAP + EMA 200 is a price-action–based professional reversal indicator designed to identify high-probability Double Top (DT) and Double Bottom (DB) patterns, filtered with VWAP and EMA 200 for strong trend confirmation.
🔍 What This Indicator Does
Automatically detects Double Top (M-pattern) and Double Bottom (W-pattern) structures
Confirms reversals using VWAP (institutional price benchmark)
Filters trades with EMA 200 to stay aligned with the dominant trend
Visually draws pattern structure + neckline
Highlights filled reversal zones for instant clarity
Generates clear BUY / SELL labels only when conditions are strong
🧠 Trading Logic (Simple Explanation)
🔴 Double Top – SELL
Two swing highs at almost the same price (M-shape)
Price breaks below the neckline
Price below VWAP
Price below EMA 200
→ DT SELL signal appears
🟢 Double Bottom – BUY
Two swing lows at almost the same price (W-shape)
Price breaks above the neckline
Price above VWAP
Price above EMA 200
→ DB BUY signal appears
🎯 Why VWAP & EMA 200 Are Used
VWAP confirms institutional bias (smart-money direction)
EMA 200 confirms long-term trend strength
Together they eliminate false reversals and sideways traps
👁️ Visual Features
✔ M & W structure lines
✔ Dashed neckline
✔ Filled pattern zones (Red for DT, Green for DB)
✔ Large, clear BUY / SELL labels
✔ Clean and professional chart appearance
📊 Best Use Cases
Intraday trading (5-min, 15-min)
Swing trading
Index trading (NIFTY, BANKNIFTY)
Stock & Futures charts
Works best during trending markets
⚠️ Important Note
This indicator focuses on quality over quantity.
Signals are fewer, but high-probability and trend-aligned.
🏆 Ideal For Traders Who
Trade price-action patterns
Avoid false signals
Follow trend + structure
Prefer clean, rule-based entries
EMA Angle Average by Eric ValerianoThis indicator determines market direction by calculating the angle of an exponential moving average and smoothing that angle over several bars. By averaging the EMA’s slope, it reduces noise and clearly classifies the market as bullish, bearish, or neutral based on trend strength rather than short term price fluctuations.
It is best used as a trend filter to confirm direction, avoid choppy conditions, and add context to entries based on other signals such as pullbacks, breakouts, or momentum setups.
SAMIR-Pattern Detector: (Debug Mode)fractal pattern to descover movment action then apply fibo on the pattern
AlgoYields - AAlgoYields A — Everyday Overlay for Clean, Actionable Context
Please follow — more indicators & ideas coming soon!
Equipped with alerts and customizable styles, this overlay is designed for daily use: attractive look for fast reads, low noise, high signal. It blends a few trusted tools into a single, elegant view so you can track trend, momentum, and breakouts without overcrowding.
What’s inside
Trading Session Backdrop
Quarter-tinted background (distinct color per quarter) for quick macro orientation; subtle week-to-week transparency shifts; CME pre-market, regular session, and post-market shading; weekends left clear.
Includes multiple curated color palettes. Ask if you want a custom theme.
EMA Cloud
A staircase of short EMAs for trend strength + two macro EMAs (defaults: 80 & 200). Macro EMAs auto-tint: blue when price is above, orange when below.
All lengths are user-configurable.
RSI-Derived Bar Colors
Contextual bar coloring by RSI level/zone to make strength/weakness instantly visible.
Comes with multiple palettes optimized for light/dark charts.
Price Channel & Breakouts
Select band source: Close (tight), HLC3 (medium), or High/Low (widest). Breakout dots print above/below bars and are color-coded by trend context:
Green : break below lower band in an uptrend (buy-the-dip candidates).
Yellow : break above upper band in an uptrend (potential exhaustion / quick scalp).
Orange : break below lower band in a downtrend (continuation shorts).
Red : break above upper band in a downtrend (fade-the-pop entries).
Buffer values can be tuned to reduce noise or enhance reactivity
How to use it
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Bullish Breakdowns ( green dots) — often attractive dip-buys within uptrends.
Confirm with macro-EMA slope: steeper = stronger follow-through; flatting slope = take quicker profits and watch for potential rollover.
Bullish Breakouts ( yellow dots) — be selective. If RSI confirms strength, these can be solid for quick scalps; otherwise, beware “touch-and-fade” at the upper band.
Apply the same logic in reverse for shorts:
Bearish Breakouts ( red ) and Bearish Breakdowns ( orange ) favor short entries/continuations.
Inputs worth tweaking
EMA lengths (short stack + macro 80/200 defaults).
RSI bar-color palette (pick for light/dark themes).
Channel source (Close / HLC3 / High-Low) and breakout buffer.
Session/quarter palette selection.
Alerts
Choose from built-in signals (channel breaks, EMA crosses, significant RSI levels).
Notes & best practices
Backtest breakouts per asset/timeframe to tune buffers and TP/SL targets.
Use level + slope together: RSI/EMA levels flag conditions; slope confirms impulse/continuation.
Let the EMA cloud and macro EMAs set bias; use RSI bars and breakout dots for timing.
Nixxo ATR Stop LossATR that prints stop losses for short or long positions with a table that shows the pip values in each case!
