Gamma & Volatility Levels [Pro]General Purpose
This indicator analyzes volatility levels and expected price movements, combining gamma concepts (financial options) with volatility analysis to identify support and resistance zones.
Main Components
High Volatility Level (HVL): Calculates a volatility level based on the simple moving average (SMA) of the price plus one standard deviation. This level is represented by an orange line showing where volatility is concentrated.
Expected Movement (Movimiento Esperante): Uses the Average True Range (ATR) multiplied by an adjustable factor to project potential upward and downward movement ranges from the current price. It is drawn in green (upward) and red (downward).
Gamma Levels (Nivelas Gamma): Identifies two key levels: the call resistance (highest high of the last 50 periods) in blue, and the put support (lowest low) in purple. These are based on recent extreme prices.
Additional Information: The indicator calculates the percentage distance between the current price and the HVL, displaying it in a label.
Visual Elements
Colored lines on the chart for each level.
Labels with exact values next to each line.
A table in the upper right corner summarizing all calculated values.
Options to show or hide each element according to preference.
This is a useful tool for traders who work with options or seek to identify levels of extreme volatility and dynamic support/resistance zones.
Statistics
Al Brooks - Bar CountIndicator Purpose:
This indicator displays bar counts on the chart to help traders identify important time nodes and cycle transitions
Features smart session filtering with automatic futures/stock detection and appropriate trading session counting
Core Features:
Smart asset detection: Auto-detect futures and stocks
Session filter toggle: Choose all-day or session-specific counting
Auto timezone handling: Chicago time for futures, NY time for stocks
Flexible display control: Customizable display frequency and label size
Session Settings:
8:30-15:15 (CT) / Futures mode: Chicago time 8:30-15:15 (CT)
9:30-16:00 (ET) / Stock mode: New York time 9:30-16:00 (ET)
All-day mode: Count from first bar of the day
Timeframe Correspondence:
Multiples of 3: Correspond to 15-minute chart update cycles
Multiples of 12: Correspond to 1-hour chart update cycles
18: Key nodes, important time turning points
Dynamic MAs Zscore | Lyro RSThe Dynamic MAs Zscore is an adaptive momentum and valuation oscillator built around advanced moving averages and statistical Z-Score normalization. By combining a wide selection of moving average types with dynamic deviation bands, this indicator delivers clear insights into trend strength , directional bias , and relative valuation — all in a clean, visually intuitive format.
━━━━━━━━━━━━━━━
Key Features
━━━━━━━━━━━━━━━
Dynamic Moving Average Engine
Applies one of 12 selectable moving average types (SMA, EMA, WMA, VWMA, HMA, ALMA, TEMA, etc.) to the chosen source. This allows fine-tuning between responsiveness and smoothness depending on market conditions.
Z-Score Normalization
Transforms the selected moving average into a standardized Z-Score:
(MA − mean) / standard deviation
This normalization makes momentum strength comparable across assets and timeframes.
Adaptive Deviation Bands
Upper and lower bands are derived from the rolling standard deviation of the Z-Score:
Custom band length
Independent positive and negative multipliers
These bands dynamically expand and contract with volatility.
Dual Signal Modes
Trend Mode – Focuses on directional continuation. Color changes and signals occur when Z-Score breaks above or below deviation bands.
Valuation Mode – Highlights relative overvaluation and undervaluation using a gradient color scale and predefined value zones.
Advanced Visual System
Includes bold layered plots, gradient fills, background shading, and candle/bar coloring to clearly reflect current market state.
Custom Color Palettes
Choose from multiple preset themes (Classic, Mystic, Accented, Royal) or define your own bullish and bearish colors.
━━━━━━━━━━━━━━━
How It Works
━━━━━━━━━━━━━━━
MA Calculation – The selected moving average type is applied to the chosen price source.
Z-Score Computation – The MA is normalized over a user-defined lookback period to quantify deviation from its mean.
Band Construction – Standard deviation of the Z-Score is calculated over the band length and scaled by positive/negative multipliers.
Mode-Dependent Logic
Trend Mode – Breaks above the upper band signal bullish momentum; breaks below the lower band signal bearish momentum.
Valuation Mode – A gradient reflects relative valuation from undervalued to overvalued, with background highlights at extreme Z-Score levels.
━━━━━━━━━━━━━━━
Signal Interpretation
━━━━━━━━━━━━━━━
Trend Confirmation
In Trend Mode, sustained moves beyond deviation bands indicate strong directional bias.
Momentum Strength
The distance of the Z-Score from zero reflects the intensity of trend momentum.
Relative Valuation
In Valuation Mode, deep negative Z-Scores suggest undervaluation, while high positive Z-Scores suggest overvaluation.
Visual Clarity
Bar and candle coloring aligned with oscillator state allows for rapid assessment of market conditions.
━━━━━━━━━━━━━━━
Customization
━━━━━━━━━━━━━━━
Adjust MA type and length to balance speed vs. smoothness.
Modify Z-Score length to control sensitivity.
Tune band length and multipliers for volatility adaptation.
Switch between Trend and Valuation modes depending on strategy.
Personalize visuals using preset or custom color palettes.
━━━━━━━━━━━━━━━
Alerts
━━━━━━━━━━━━━━━
Bullish condition when Z-Score > 0
Bearish condition when Z-Score < 0
Overvalued and undervalued valuation alerts
⚠️ Disclaimer
This indicator is intended for technical analysis and educational purposes only. It does not guarantee profitable outcomes and should be used alongside other tools, confirmation methods, and sound risk management. The author is not responsible for any financial decisions made using this indicator.
EMA Slope Angle# EMA Slope Angle Indicator
A professional, non-repainting overlay indicator that visualizes EMA slope strength as an angle in degrees, providing instant visual feedback through dynamic EMA coloring and comprehensive trend analysis.
## ORIGINALITY
This indicator is original in its approach to slope measurement:
- **Angle-based calculation**: Uses arctangent to calculate slope as an angle in degrees (not percentage), providing a more intuitive measure of trend strength
- **Dynamic visual feedback**: Combines real-time EMA line coloring with regime detection, creating a continuous visual representation of market conditions
- **Comprehensive analysis**: Integrates angle-based trend shift signals with optional statistical analysis in a single, cohesive tool
- **Non-repainting design**: All calculations use confirmed bars only, ensuring reliable, deterministic output
## HOW IT WORKS
The indicator calculates the EMA slope angle using trigonometric functions:
```
Angle = arctan((EMA_current - EMA_past) / lookback_bars) × 180/π
```
This provides an intuitive measure where:
- **Steep angles** = strong trends (visualized with saturated colors)
- **Shallow angles** = weak trends (visualized with lighter colors)
- **Near-zero angles** = flat/consolidation (visualized in gray)
The EMA line color dynamically reflects:
- **Direction**: Green shades for uptrends, red shades for downtrends
- **Strength**: Color intensity based on normalized angle (stronger slopes = more saturated colors)
- **Regime**: Gray for flat conditions when angle is below threshold
## KEY FEATURES
### Dynamic EMA Coloring
- EMA line color changes continuously based on slope strength
- Color intensity reflects trend strength (50-100% opacity range)
- Instant visual feedback without cluttering the chart
### Regime Detection
- Automatically classifies market conditions: **RISING**, **FALLING**, or **FLAT**
- Configurable angle thresholds for regime classification
- Real-time regime updates on confirmed bars only
### Trend-Shift Signals
- Detects transitions from FLAT to RISING/FALLING regimes
- Visual arrows on chart when significant trend shifts occur
- Prevents signal spam by only triggering from FLAT state
- Configurable trigger thresholds for signal sensitivity
### KPI Dashboard
- Real-time angle display (rounded to 1 decimal place)
- Current regime status with color coding
- Last signal tracking (UP/DOWN/NONE)
- Positioned in top-right corner for easy reference
### Advanced Angle Statistics (Optional)
- Detailed breakdown of angle distribution across 9 granular buckets:
- 0-0.2°, 0.2-0.5°, 0.5-1°, 1-1.5°, 1.5-2°, 2-3°, 3-5°, 5-10°, >10°
- Shows count and percentage for each bucket
- Automatically resets on symbol/timeframe changes
- Useful for analyzing historical slope patterns
## SETTINGS
### Main Settings
- **EMA Length**: Period for exponential moving average (default: 50)
- **Slope Lookback Bars**: Number of bars to compare for slope calculation (default: 5)
### Angle Settings
- **Flat Angle Threshold**: Maximum angle for FLAT regime classification (default: 2.0°)
- **Rising Angle Trigger**: Minimum angle to trigger RISING regime and UP signals (default: 1.0°)
- **Falling Angle Trigger**: Maximum angle to trigger FALLING regime and DOWN signals (default: -1.0°)
- **Max Angle for Color Saturation**: Maximum angle for full color intensity (default: 30.0°)
### Display Options
- **Uptrend Color**: Color for rising trends (default: dark green)
- **Downtrend Color**: Color for falling trends (default: dark red)
- **Flat Color**: Color for flat conditions (default: gray)
- **Show Trend-Shift Signals**: Toggle signal arrows on/off (default: true)
- **Show Angle Statistics**: Toggle statistics dashboard on/off (default: false)
## NON-REPAINTING GUARANTEE
- All calculations use confirmed bars only (`barstate.isconfirmed`)
- No future bar references
- No higher timeframe calls using `request.security()`
- Deterministic output - what you see is what you get
- Reliable for backtesting and live trading
## USE CASES
- **Trend Identification**: Instantly identify trend strength and direction at a glance
- **Reversal Detection**: Spot trend reversals early through regime changes
- **Trade Filtering**: Filter trades based on slope strength and regime
- **Consolidation Monitoring**: Identify flat market conditions for range trading
- **Pattern Analysis**: Study historical angle distributions to understand market behavior
- **Momentum Assessment**: Gauge trend momentum through visual color intensity
## LIMITATIONS
- Angle calculation depends on EMA length and lookback period settings
- Regime classification is based on configurable thresholds - adjust to match your trading style
- Signals only trigger when transitioning from FLAT state to prevent spam
- Statistics reset on symbol/timeframe changes (by design)
- Color intensity is normalized to max angle setting - adjust for your market's typical ranges
## TECHNICAL NOTES
- Uses Pine Script v6
- Overlay indicator (plots on price chart)
- No external dependencies
- Compatible with all TradingView chart types
- Works on all timeframes and symbols
## DISCLAIMER
This indicator is designed for visual trend analysis and educational purposes. Always combine with other technical analysis tools, fundamental analysis, and proper risk management strategies. Past performance does not guarantee future results. Trading involves risk of loss.
---
**Perfect for**: Swing traders, day traders, trend followers, and market analysts seeking intuitive trend strength visualization.
MenthorQ Levels ConversionLevels Conversion helps traders accurately overlay price levels from spot/index ETFs and indices (like SPX, SPY, QQQ, NDX) onto futures charts (like ES, NQ, etc.).
Because futures and spot/index prices don’t trade at the same price, your levels will be misaligned if you plot them directly. Futures typically trade at a spread or ratio versus their related index/ETF. This indicator solves that by calculating the conversion ratio automatically, so your levels stay aligned on the futures chart.
How it works
This script calculates the ratio between Asset A and Asset B and applies it to convert levels from one instrument to the other (for example, SPX → ES, QQQ → NQ).
Ratio options (3 modes)
You can choose one of three ratio sources:
✅ T1 Ratio (Morning Snapshot)
Select a specific time to “lock” the ratio.
Default: 10:00 AM ET (morning session snapshot)
✅ T2 Ratio (Afternoon Snapshot)
Select a second time to “lock” the ratio.
Default: 3:30 PM ET (afternoon snapshot)
✅ Last Price Ratio (Live)
Uses the last traded price of both assets to compute the ratio.
Note: To refresh the “Last Price” baseline, simply remove and re-add the indicator.
Learn more about Levels Conversions: menthorq.com
Common levels conversions
Some popular use-cases include:
- SPX Gamma Levels → ES
- SPY Gamma Levels → ES
- QQQ Gamma Levels → NQ
- NDX Gamma Levels → NQ
- SPX Intraday Gamma Levels → ES
- QQQ Intraday Gamma Levels → NQ
- SPX Swing Trading Levels → ES
- QQQ Swing Trading Levels → NQ
- GLD Levels → GC
- DIA Levels → YM
- USO Levels → CL
- NVDA / MAG7 Levels → QQQ
PatternTransitionTablesPatternTransitionTables Library
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- 1. INTRODUCTION --------- 🌸
💮 Overview
This library provides precomputed state transition tables to enable ultra-efficient, O(1) computation of Ordinal Patterns. It is designed specifically to support high-performance indicators calculating Permutation Entropy and related complexity measures.
💮 The Problem & Solution
Calculating Permutation Entropy, as introduced by Bandt and Pompe (2002), typically requires computing ordinal patterns within a sliding window at every time step. The standard successive-pattern method (Equations 2+3 in the paper) requires ≤ 4d-1 operations per update.
Unakafova and Keller (2013) demonstrated that successive ordinal patterns "overlap" significantly. By knowing the current pattern index and the relative rank (position l) of just the single new data point, the next pattern index can be determined via a precomputed look-up table. Computing l still requires d comparisons, but the table lookup itself is O(1), eliminating the need for d multiplications and d additions. This reduces total operations from ≤ 4d-1 to ≤ 2d per update (Table 4). This library contains these precomputed tables for orders d = 2 through d = 5.
🌸 --------- 2. THEORETICAL BACKGROUND --------- 🌸
💮 Permutation Entropy
Bandt, C., & Pompe, B. (2002). Permutation entropy: A natural complexity measure for time series.
doi.org
This concept quantifies the complexity of a system by comparing the order of neighbouring values rather than their magnitudes. It is robust against noise and non-linear distortions, making it ideal for financial time series analysis.
💮 Efficient Computation
Unakafova, V. A., & Keller, K. (2013). Efficiently Measuring Complexity on the Basis of Real-World Data.
doi.org
This library implements the transition function φ_d(n, l) described in Equation 5 of the paper. It maps a current pattern index (n) and the position of the new value (l) to the successor pattern, reducing the complexity of updates to constant time O(1).
🌸 --------- 3. LIBRARY FUNCTIONALITY --------- 🌸
💮 Data Structure
The library stores transition matrices as flattened 1D integer arrays. These tables are mathematically rigorous representations of the factorial number system used to enumerate permutations.
💮 Core Function: get_successor()
This is the primary interface for the library for direct pattern updates.
• Input: The current pattern index and the rank position of the incoming price data.
• Process: Routes the request to the specific transition table for the chosen order (d=2 to d=5).
• Output: The integer index of the next ordinal pattern.
💮 Table Access: get_table()
This function returns the entire flattened transition table for a specified dimension. This enables local caching of the table (e.g. in an indicator's init() method), avoiding the overhead of repeated library calls during the calculation loop.
💮 Supported Orders & Terminology
The parameter d is the order of ordinal patterns (following Bandt & Pompe 2002). Each pattern of order d contains (d+1) data points, yielding (d+1)! unique patterns:
• d=2: 3 points → 6 unique patterns, 3 successor positions
• d=3: 4 points → 24 unique patterns, 4 successor positions
• d=4: 5 points → 120 unique patterns, 5 successor positions
• d=5: 6 points → 720 unique patterns, 6 successor positions
Note: d=6 is not implemented. The resulting code size (approx. 191k tokens) exceeds the Pine Script limit of 100k tokens (as of 2025-12).
EMA + ATR Semi-Auto strategy -Kohei Matsumura-EMAとATRを自動調節するストラテジー
This is an EMA- and ATR-based trading strategy that adapts its parameters according to recent market behavior and performance characteristics.
The strategy dynamically adjusts trend sensitivity and risk management settings to maintain robustness across varying market conditions, while operating strictly on confirmed price data.
online Moment-Based Adaptive Detection🙏🏻 oMBAD (online Moment-Based Adaptive Detection): adaptive anomaly || outlier || novelty detection, higher-order standardized moments; at O(1) time complexity
For TradingView users: this entity would truly unleash its true potential for you ‘only’ if you work with tick-based & seconds-based resolutions, otherwise I recommend to keep using original non-online MBAD . Otherwise it may only help with a much faster backtesting & strategy development processes.
...
Main features :
O(1) time complexity: the whole method works @ O(1) time complexity, it’s lighting fast and cheap
HFT-ready: frequency, amount and magnitude of data points are irrelevant
Axiomatic: no need to optimize or to provide arbitrary hyperparameters, adaptive thresholds are completely data-driven and based on combination of higher-order central moments
Accepts weights: the method can gain additional information by accepting weights (e.g. volume weighting)
Example use cases for high-frequency trading:
Ordeflow analysis: can be applied on non-aggregated flow of market orders to gauge its imbalance and momentum
Liquidity provision: can be applied to high-resolution || tick data to place and dynamically adjust prices of limit orders
ML-based signals: online estimates of higher-order central moments can be used as features & in further feature engineering for trading signal generation
Operation & control: can be applied on PnL stream of your strategy for immediate returns analysis and equity control
Abstract:
This method is the online version of originally O(n) MBAD (Moment-Based Adaptive Detection) . It uses higher-order central & standardized moments to naturally estimate data’s extremums using all data while not touching order-statistics (i.e. current min and max) at all. By the same principles it also estimates “ever-possible” values given the data-generating process stays the same.
This online version achieves reduced time complexity to O(1) by using weighted exponential smoothing, and in particular is based on Pebay et al (2008) work, which provides mathematically correct results for the moments, and is numerically stable, unlike the raw sum-based estimates of moments.
Additionally, I provide adjustments for non-continuous lattice geometry of orderbooks, and correct re-quantization math, allowing to artificially increase the native tick size.
The guidelines of how to adjust alpha (smoothing parameter of exponential smoothing) in order to completely match certain types of moving averages, or to minimize errors with ones when it’s impossible to match; are also provided.
Mathematical correctness of the realization was verified experimentally by observing the exact match with the original non-recursive MBAD in expanding window mode, and confirmed by 2 AI agents independently. Both weighted and non-weighted versions were tested successfully.
...
^^ On micro level with moving window size 1
^^ With artificial tick size increase, moving window size 64
^^ Expanding window mode anchored to session start
^^ Demonstrates numerical stability even on very large inputs
...
∞
Macroeconomic Dashboard by DGTMacroeconomic Dashboard is a script tailored for traders and investors using top-down strategies to navigate global markets. It integrates key macroeconomic indicators, such as monetary policy, inflation, yields, and market sentiment, directly into financial charts.
By visualizing real-time macro data alongside asset price movements, this tool bridges the gap between traditional economic metrics and technical analysis. Whether analyzing crypto or traditional markets, users can better contextualize price action within broader economic cycles and trends.
Designed to support macro-informed decision-making, it helps identify shifts in liquidity, policy direction, and risk appetite, enhancing strategic trade entries and portfolio positioning.
KEY FEATURES
⯌ Macro Dashboard
The script provides a macro dashboard that tracks changes across key economic dimensions: monetary policy, inflation and growth, bond markets, and risk indicators. With built-in anomaly detection and trend analysis across short-, mid-, and long-term timeframes, it helps interpret market moves through a macroeconomic lens, whether analyzing equities, commodities, or digital assets.
⯌ Macro on Chart
By visualizing macro data such as M2 money supply, CPI, treasury yields, and volatility indices, users can more easily correlate economic developments with price action, enhancing situational awareness and decision-making.
MACRO METRICS
The script covers five core macroeconomic domains, each with key metrics:
Liquidity & Monetary Policy
Global M2 Money Supply
Federal Funds Rate
Reverse Repo Operations
Inflation & Economic Growth
Consumer Price Index (CPI)
Producer Price Index (PPI)
Real GDP Growth
Yields & Bond Markets
10-Year Treasury Yield
2-Year Treasury Yield
Yield Curve (10Y–2Y Spread)
Global Risk & Currency Indicators
U.S. Dollar Index (DXY)
Volatility Index (VIX)
Economic Policy Uncertainty Index
Equities, Commodities & Crypto
S&P 500 (SPX)
Nasdaq 100 (NDX)
Gold (XAU/USD)
Crude Oil (WTI)
Bitcoin (BTCUSD)
DISCLAIMER
This script is intended for informational and educational purposes only. It does not constitute financial, investment, or trading advice. All trading decisions made based on its output are solely the responsibility of the user.
Платный скрипт
Shiori TFGI Lite Technical Fear and Greed Index (Open Source)Shiori’s TFGI Lite
Technical Fear & Greed Index (Open Source)
---
English — Official Description
Shiori’s TFGI Lite is an open-source Technical Fear & Greed Index designed to help traders and investors understand market emotion, not predict price.
Instead of generating buy or sell signals, this indicator focuses on answering a calmer, more important question:
> Is the market emotionally stretched away from its own historical balance?
TFGI Lite combines three well-known technical dimensions — volatility, price deviation, and momentum — and normalizes them into a single, intuitive 0–100 sentiment scale.
What This Indicator Is
* A market context tool, not a trading signal
* A way to observe emotional extremes and misalignment
* Designed for any asset, any timeframe
* Fully open source, transparent and adjustable
Core Components
* Fear Factor: Short-term vs long-term ATR ratio with logarithmic compression
* Greed Factor: Price Z-score with tanh-based normalization
* Momentum Factor: Classic RSI as emotional momentum
These factors are blended and gently smoothed to form the current sentiment level.
Historical Baseline & Deviation
TFGI Lite introduces a historical baseline concept:
* The baseline represents the market’s own emotional equilibrium
* Deviation measures how far current sentiment has drifted from that equilibrium
This allows the indicator to highlight conditions such as:
* 🔥 Overheated: High sentiment + strong positive deviation
* 💎 Undervalued: Low sentiment + strong negative deviation
* ⚠️ Misaligned: Emotionally extreme, but inconsistent with historical behavior
How to Use (Lite Philosophy)
* Use TFGI Lite as a background compass, not a trigger
* Combine it with price structure, risk management, and your own strategy
* Extreme readings suggest emotional tension, not immediate reversal
> Think of TFGI Lite as market weather — it tells you the climate, not when to open or close the door.
About Parameters & Customization
All parameters in TFGI Lite are fully adjustable. Markets have different personalities — volatility, sentiment range, and emotional extremes vary by asset and timeframe.
You are encouraged to:
* Adjust fear/greed thresholds based on the asset you trade
* Tune smoothing and baseline lengths to match your timeframe
* Treat sentiment levels as relative, not universal absolutes
There is no single “correct” setting — TFGI Lite is designed to adapt to your market, not force the market into a fixed model.
Important Notes
* This is a technical sentiment indicator, not financial advice
* No future performance is implied
* Designed to reduce emotional decision-making, not replace it
---
🇹🇼 繁體中文 — 指標說明
Shiori’s TFGI Lite（技術型恐懼與貪婪指數） 是一款開源的市場情緒指標，目的不是預測價格，而是幫助你理解市場當下的「情緒狀態」。
與其問「現在該不該買或賣」，TFGI Lite 更關心的是：
> 市場情緒是否已經偏離了它自己的歷史平衡？
本指標整合三個常見但關鍵的技術面向，並統一轉換為 0–100 的情緒刻度，讓市場狀態一眼可讀。
這個指標是什麼
* 市場情緒與狀態觀察工具（非買賣訊號）
* 用來辨識情緒極端與錯位狀態
* 適用於任何商品與任何週期
* 完全開源，可學習、可調整
核心構成
* 恐懼因子：短期 / 長期 ATR 比例（對數壓縮）
* 貪婪因子：價格 Z-Score（tanh 正規化）
* 動能因子：RSI 作為情緒動量
歷史基準與偏離
TFGI Lite 引入「歷史情緒基準」的概念：
* 基準代表市場長期的情緒平衡
* 偏離值顯示當前情緒與自身歷史的距離
因此可以辨識：
* 🔥 過熱（高情緒 + 正向偏離）
* 💎 低估（低情緒 + 負向偏離）
* ⚠️ 錯位（情緒極端，但不符合歷史行為）
使用建議（Lite 精神）
* 將 TFGI Lite 作為「背景雷達」，而非進出場依據
* 搭配價格結構、風險控管與個人策略
* 情緒極端不等於立刻反轉
> 你可以把它想像成市場的天氣預報，而不是交易指令。
參數調整與個人化說明
本指標中的所有參數皆可調整。不同市場、不同商品，其波動特性與情緒區間並不相同。
建議你：
* 依標的特性自行調整恐懼 / 貪婪門檻
* 依交易週期調整平滑與基準長度
* 將情緒數值視為「相對狀態」，而非固定答案
TFGI Lite 的設計初衷，是讓你定義市場，而不是被單一參數綁住。
溫馨提示
如果你在調整指標參數時遇到不熟悉的項目，請點擊參數旁邊的 「!」圖示，每個設定都有清楚的說明。
本指標設計為可慢慢探索，請依自己的節奏理解市場狀態。
---
🇯🇵 日本語 — インジケーター説明
Shiori’s TFGI Lite は、価格を予測するための指標ではなく、
市場の「感情状態」を可視化するためのオープンソース指標です。
この指標が問いかけるのは、
> 現在の市場感情は、過去のバランスからどれだけ乖離しているのか？
という一点です。
特徴
* 売買シグナルではありません
* 市場心理の極端さやズレを観察するためのツールです
* すべての銘柄・時間軸に対応
* 学習・調整可能なオープンソース
構成要素
* 恐怖要素：ATR 比率（対数圧縮）
* 強欲要素：価格 Z スコア（tanh 正規化）
* モメンタム：RSI
ベースラインと乖離
市場自身の感情的な基準点と、
現在の感情との距離を測定します。
過熱・割安・感情のズレを視覚的に把握できます。
パラメータ調整について
TFGI Lite のすべてのパラメータは調整可能です。市場ごとにボラティリティや感情の振れ幅は異なります。
* 恐怖・強欲の閾値は銘柄に応じて調整してください
* 時間軸に合わせて平滑化やベースライン期間を変更できます
* 数値は絶対値ではなく、相対的な感情状態として捉えてください
この指標は、市場に合わせて柔軟に使うことを前提に設計されています。
フレンドリーヒント
入力項目で分からない設定がある場合は、横に表示されている 「!」アイコン をクリックしてください。各パラメータには分かりやすい説明が用意されています。
このインジケーターは、落ち着いて市場の状態を理解するためのものです。
---
🇰🇷 한국어 — 지표 설명
Shiori’s TFGI Lite는 매수·매도 신호를 제공하는 지표가 아니라,
시장 감정의 상태를 이해하기 위한 기술적 심리 지표입니다.
이 지표의 핵심 질문은 다음과 같습니다.
> 현재 시장 감정은 과거의 균형 상태에서 얼마나 벗어나 있는가?
특징
* 거래 신호 아님
* 시장 심리의 과열·저평가·불일치를 관찰
* 모든 자산, 모든 타임프레임 지원
* 오픈소스 기반
구성 요소
* 공포 요인: ATR 비율 (로그 압축)
* 탐욕 요인: Z-Score (tanh 정규화)
* 모멘텀: RSI
활용 방법
TFGI Lite는 배경 지표로 사용하세요.
가격 구조와 리스크 관리와 함께 사용할 때 가장 효과적입니다.
파라미터 조정 안내
TFGI Lite의 모든 설정 값은 사용자가 직접 조정할 수 있습니다. 자산마다 변동성과 감정 범위는 서로 다릅니다.
* 공포 / 탐욕 기준값은 종목 특성에 맞게 조정하세요
* 타임프레임에 따라 스무딩 및 기준 기간을 변경할 수 있습니다
* 감정 수치는 절대적인 값이 아닌 상대적 상태로 해석하세요
이 지표는 하나의 정답을 강요하지 않고, 시장에 맞춰 적응하도록 설계되었습니다.
친절한 안내
설정 값이 익숙하지 않다면, 항목 옆에 있는 "!" 아이콘을 클릭해 보세요. 각 입력값마다 설명이 제공됩니다.
이 지표는 천천히 시장의 맥락을 이해하도록 설계되었습니다.
---
Educational purpose only. Not financial advice.
---
#FearAndGreed #MarketSentiment #TradingPsychology #TechnicalAnalysis #OpenSourceIndicator #Volatility #RSI #ATR #ZScore #MultiAsset #TradingView #Shiori
Quantifiable Broadening Formations [STAT TRADING]Broadening Formations v4
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OVERVIEW
Automatically identifies and draws Broadening Formations — expanding price structures that reveal where the market is auctioning both higher and lower to find fair value.
This indicator uses a quantifiable, rule-based approach to detect expansion patterns and dynamically tracks the evolution of price ranges in real-time. No subjective drawing required — the indicator handles everything automatically.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
FEATURES
▸ Bar Classification System
Each bar is labeled based on its relationship to the previous bar:
1 = Inside Bar — Range contraction, price stayed within prior bar
2u = Trending Up — Higher high AND higher low
2d = Trending Down — Lower high AND lower low
3 = Outside Bar — Expansion, higher high AND lower low in single bar
C3 = Composite 3 — Multi-bar expansion pattern (2d→2u or 2u→2d completing the range)
Color coding helps identify conviction:
• Green = Bullish structure with bullish close
• Red = Bearish structure with bearish close
• Orange = Conflicted (structure and close disagree)
• Yellow = Outside Bar (3)
• Purple = Composite 3 (C3)
▸ Automatic Formation Detection
The indicator detects when price proves it can take both sides of a range, then:
• Draws dynamic upper and lower boundary lines
• Extends lines forward as projected support/resistance
• Updates the formation in real-time as price makes new highs or lows
• Detects breakouts when price closes through boundaries with conviction
▸ Support/Resistance Test Dots
Visual markers show when price tests the formation boundaries:
• Red dot at high = Price wicked into upper resistance but closed below (failed test)
• Green dot at low = Price wicked into lower support but closed above (held support)
These dots help you see where the market is probing the boundaries before a decisive move.
▸ Breakout & Reclaim Detection
Clear labels mark key events:
• BREAKOUT ↑ = Close above upper boundary (bullish break)
• BREAKOUT ↓ = Close below lower boundary (bearish break)
• RECLAIM ↑ = Failed breakdown, price recovered back into range
• RECLAIM ↓ = Failed breakout, price fell back into range
Reclaims are powerful signals — failed breakouts often lead to strong moves in the opposite direction. The formation automatically expands to include the failed move.
▸ Sub-Formations (Internal Triangles)
White lines show nested formations within larger structures. These internal patterns can provide earlier signals before the major formation resolves.
Sub-formations only appear when they are truly internal to the parent (not touching parent boundaries).
▸ Formation Labels
Each formation is labeled at its trigger point:
• 3 = Triggered by outside bar
• C3 = Triggered by composite pattern
• R1, R2... = Number of reclaims (e.g., "3 R2" = outside bar trigger with 2 reclaims)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
SETTINGS
Show Bar Classification Labels Display 1/2u/2d/3/C3 below each bar
Detect Composite 3s Identify multi-bar expansion patterns
Show Sub/Internal Formations Display nested formations in white
Show Support/Resistance Test Dots Mark boundary tests with colored dots
Show Breakout/Reclaim Labels Label breakouts and reclaims
Major BF Line Color Color for primary formation lines
Sub BF Line Color Color for nested formation lines
Line Width Thickness of formation lines
Bars to Project Forward How far to extend lines into the future
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ALERTS
Set alerts for key events:
• Outside Bar (3) — Single-bar expansion detected
• Composite 3 (C3) — Multi-bar expansion pattern detected
• New BF Started — New broadening formation triggered
• BF Break — Price closed through formation boundary
• BF Reclaim — Failed breakout, formation continues with expanded range
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
HOW TO USE
Understand your position:
Are you near the upper boundary, lower boundary, or mid-range? Context matters.
Watch for closes, not wicks:
Wicks test levels. Closes show conviction. The indicator only triggers breakouts on closes through the boundary.
Pay attention to reclaims:
A break that fails and reclaims often leads to an aggressive move the other direction. The "R" count on the label shows how many times this has happened.
Use test dots for entries:
Multiple red dots at resistance followed by a green bar = potential short setup. Multiple green dots at support followed by a red bar = potential long setup.
Sub-formations give early signals:
When an internal triangle breaks, it can front-run the larger formation's move.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
NOTES
• Works on all timeframes and instruments
• Lines update dynamically as new bars form
• Historical formations are preserved on the chart
• Composite 3s (C3) are shown in purple to distinguish from single-bar triggers
• Best used to understand current market structure — combine with your existing strategy for entries
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Objective structure. No guesswork.
p.s This is a public version in a different language than our true BF identification algorithm. There will be some bugs and it is unlikely we will fix it in the near future.
BTC Regime Oscillator (MC + Spread) [1D]ONLY SUPPOSED TO BE USED FOR BTC PERPS, AND SPOT LEVERAGING:
This is a risk oscillator that measures whether Bitcoin’s price is supported by real capital or is running ahead of it, and converts that into a simple risk-regime oscillator.
It's built with market cap, and FDV, and Z-scores compressed to -100 <-> 100
I created this indicator because I got tired of FOMO Twitter and Wall Street games.
DO NOT USE THIS AS A BEGIN-ALL-AND-END-ALL. YOU NEED TO USE THIS AS A CONFIRMATION INDICATOR, AND ON HTF ONLY (1D>) IF YOU USE THIS ON LOWER TIMEFRAMES, YOU ARE FEEDING YOUR MONEY TO A LOW-LIFE DING BAT ON WALL STREET. HERE IS HOW IT WORKS:
This indicator is Split up by
A) Market Cap
--> Represents real money in BTC
--> Ownership capital
--> If MC is rising, money is entering BTC
B) FDV (Fully Diluted Valuation)
--> For BTC: price(21M) (21,000,000)
--> Represents the theoretical valuation
--> Since BTC really has a fixed cap, FDV mostly tracks the price
C) Oscillators
Both MC and FDV are:
--> Logged (to handle scale)
--> Normalized (Z-score)
--> Compressed to -100 <-> 100
HERE ARE THREE THINGS YOU ARE GOING TO SEE ON THE CHART
A) The market cap oscillator (MC OSC)
--> Normalized trend of real capital
RISING: Indicates capital inflow
FALLING: Indicates capital outflow
B) FDV Oscillator
--> Normalized trend of valuation pressure
ABOVE MC: Price is ahead of capital
BELOW MC: Capital is keeping up
!!!! FDV IS CONTEXT NOT SIGNALS !!!!
C) Spread = (FDV - MC)
--> The difference between valuation and capital
(THIS IS THE CORE SIGNAL)
NEGATIVE: Capital is gonna lead price
NEAR 0: Balanced
POSITIVE: Price leads capital
(THIS MEANS STRESS FOR BTC, NOT DILLUTION!)
WHAT DOES -60, 0, 60 MEAN?:
--> These are meant to serve as risk zones, not buy/sell dynamics; this is not the same as an RSI oscillator.
A) 0 level
--> Price and capital are balanced
--> No structural stress
(TRADE WITH NORMAL POSITION SIZE, AND NORMAL EXPECTATIONS)
B) Below -60 (Supportive/Compressed)
--> BTC is relatively cheap to recent history
--> Capital supports price well
(ALWAYS REMEMBER TO CONFIRM THIS WITH WHAT THE CHART IS TELLING YOU)
--> Press trends
--> Use higher ATRs
--> Pullbacks are better here
C) Above 60 (Overextension, or fragile)
--> BTC is expensive relative to recent history
--> Price is ahead of capital
(ALWAYS REMEMBER TO CONFIRM THIS WITH WHAT THE CHART IS TELLING YOU)
--> Reduce leverage, use smaller ATR
--> Use lower ATRs, TP faster
--> Do not chase breakouts
--> Expect volatility and whipsaws
"Can I press trades right now? Or do I need to hog my capital?"
CONDITIONS:
Spread Less than 0 and below -60 = Press trades
Spread near 0 = Normal trading conditions
Spread is Greater than 0 or above 60+ = Capital protection
Volume Analysis🙏🏻 (signed) Volume Analysis is 2 of 2 structural layer / ordeflow analysis scripts, while the first one is Liquidity Analysis. Both are independent so can’t be released together as a single script, but should be used together.
The same math used in this script can be applied to other types of aggressive volume data: non-aggregated flow of market orders, volume traded of put vs call options.
There’s no universal agreement about terminology, but this script works with volumes signed by the aggressor who initiated a transaction. Then these volumes get aggregated by time and a cumulative sum is calculated. Mostly this is widely known as Cumulative Volume Delta.
However this script works with 'inferred' volumes vs the provided ones. It’s the better choice for equities, bonds; neutral choice for currencies; and suboptimal choice for natural and artificial commodities.
Contents:
Output description;
How to analyze & use the outputs;
How to use it together with Liquidity Analysis script;
How did I use both scripts to finish The Leap profitably and skipped many losses.
1. Output description
Color of the CVD line reflects (signed) volume imbalance state: red is negative, purple is neutral, blue is positive.
3 purple lines are lower deviation (lower band), basis (middle band), upper deviation (upper band): used to generate signals by a ruleset that would be explained in a minute
Gray number in the script’s status line is the advised input you may put into Inferred volume multiplier in script’s setting, I will explain it
Vertical dash line marks the moving window end, this way you can be certain over what exact data you see the profile was built.
2. How to analyze & use the outputs
Setup up the script:
Moving window length: set it to ~ ¼ of your data analysis window. E.g if you see on your charts and use ~ 256 bars, set the length to 64.
Inferred volume multiplier: you can easily leave it 256, this is not a critical factor for the math, it’s mostly there if you want to ~ equate inferred volumes with real ones in scale. For this, use the gray number in the script status line, it’s calculated as ratio of long term real volumes weighted avg to long term inferred volumes weighted avg.
Again, changing the inferred volume multiplier won’t affect the math.
Use 2 timeframes: main one and a far lower one 3 steps down, just like on the screenshot.
Find out current volume imbalance state:
As mentioned before, based on CVD line color, it can be negative, neutral or positive. This is the state variable that changes slowly and denies/confirms the signals generated by crossovers of CVD line and 3 purple thresholds.
For this I use my own very fast and lightweight metric that is totally statistically grounded, utilizes temporal information, and calculates volume imbalance without using heavy math like regressions as it’s usually done. It also provides a natural neutral zone, when volume imbalance is not strong enough to be confirmed.
...
CVD-based signals:
First you need to understand what precisely a touch of a threshold is:
Touch: an event when either of these 2 happens:
One CVD datapoint is above the threshold, and the next CVD datapoint is below the threshold
One CVD datapoint is below the threshold, and the next CVD datapoint is above the threshold
These are usually called crossovers/crossunders.
Now with the 3 purple thresholds we follow this logic:
Monitor the last touched threshold;
Once another threshold is touched, here we may generate a signal but only once !, after the first generated signal at that threshold we can’t generate more signals on this threshold, we need to wait when CVD comes to another threshold.
If CVD touches one threshold, and then goes down and touches another threshold downwards, we wait when CVD makes a datapoint above this threshold. When it happens, we register a long signal
If CVD touches one threshold, and then goes up and touches another threshold upwards, we wait when CVD makes a datapoint below this threshold. When it happens, we register a short signal
However, don’t open new trades against the current volume imbalance state. So don’t open shorts when the CDV line is blue, and don’t open longs when CVD line is red.
Btw, this technique I call it “reclaim” of a level/threshold. It can be applied to horizontal levels, and it’s very powerful especially when you fade levels on very volatility assets like BTC. This technique allows you to Not fade a level straight away, but wait when price goes past the level a bit, and then comes back and reclaims it, only there you enter, and moreover you now have a very well defined risk point.
The last part is multi-timeframe logic. Prefer to act when a lower timeframe is Not against the main timeframe. That’s all, no multiple higher timeframes are needed.
3. How to use it together with Liquidity Analysis script.
That script also has a mean to generate its own signals, and another state variable called Liquidity Imbalance.
So now you’re not only looking at volume imbalance but also at liquidity imbalance that would deny/confirm the CVD based signal. You need at least one of these two to favor your long or short.
This is the same logic widely used in HFT, where MM bots cancel/shift/resize orders when book is too onesided And ordeflow is one sided as well.
4. How did I use both scripts to finish The Leap profitably and skipped many losses.
Even tho you can use structural information as your main strategic layer, as many so-called orderflow traders do, I traded in objective style: my fade signals were volatility based in essence, and I used ordeflow for better entries and stops, but most importantly to skip losses.
When ‘both‘ liquidity imbalance and volume imbalance (in their main timeframes) were against my trades, I skipped them all, saving many ~$500 stop losses (that was my basis risk unit for the Leap). Unless I had a very strong objective signal, i.e. confluence of several signals, or just one higher timeframe signal, I did all these skips.
I traded ~ intraweek timeframe, so I was analyzing either the last 230 30min bars or 1380 5min bars. Both Liquidity Analysis and (signed) Volume Analysis scripts were set to moving window length 46 or 276 for either granularity.
I finished the leap with 9% profit and max DD ~ 5%, a bit short of my goal of 12.5%. If not these 2 scripts I would’ve finished a bit above breakeven I think.
,,,
Another thing, I made these 2 scripts invite-only because they are made particularly for trading, particularly for certain types of market data. These are tools adapted for particular use case, not like my other posts with general math entities like Kernel Density Estimation or Kalman filter, that you can take and apply properly on any data you need yourself.
However these are made from general math entities like everything else. ‘All’ the components are available in my other scripts, ideas, and other sources related to me. If you want to reverse-engineer these, you can find all the components you need in my already posted open source work.
∞
Worstfx Key Time Windows + 5 Day Journal🕒 Key Time Windows — Features & Purpose
✔️ Includes 6 Major Time Windows:
• 7:45 PM (Asia Open Overview)
• 12:00 AM (Daily Reset Liquidity Shift)
• 2:00 AM (London Accumulation / Manipulation)
• 7:00 AM (Pre-NY / Expansion Setup)
• 10:00 AM (NY Reversal Window)
• 2:00 PM (NY Power Move / Final Push) ← added
These windows are not random — they are the exact points in the day where:
• Liquidity resets
• Volatility compresses or expands
• Session trends form or reverse
• Market makers reposition
• High-probability setups appear
The panel shows:
➤ INSIDE
You are currently in the window.
Expect movement, structure breaks, or trap/reversal behavior.
➤ NEAR
Approaching a key window.
Prepare, observe order flow, plan entries.
➤ FAR
Out of the actionable range.
Ideal for reducing screen time and avoiding emotional trades.
➤ IDLE
The window passed.
High-probability moment is over — walk away or wait for the next one.
⚡ Why this matters
Most blown accounts come from trading outside high-probability times.
Your edge comes from timing, not randomness.
This panel keeps your brain aligned with the correct moments — not boredom, FOMO, or impulse.
📊 5-Day Performance Journal — Features
✔️ Enter daily P/L manually
• Monday → Friday
• Accepts positive or negative values
• Example: +2500, -300, 0
✔️ Auto-Calculated Weekly Total
• Shown right next to Friday
• Colored based on profit or loss
• Light highlight tint to stand out without distractions
✔️ Two Clean Layouts
• Vertical → For corner placement
• Horizontal → For header-like week summaries
✔️ Psychology Through Design
• Green = rewarded discipline
• Red = consequence of breaking plan
• White-dim = zero day → neutral, no shame, no heat
The goal is not the number —
It’s accountability, awareness, and emotional grounding.
🧠Consistency Over Drama
The weekly total next to Friday forces your brain to think in weeks, not minutes.
Bad day?
You stop early to protect weekly total.
Good day?
You don’t overtrade because the number is already green.
This shifts your psychology from:
“I need to win right now.”
to:
“I need to preserve my weekly edge.
🔋To unlock the full power of the framework, run this together with Worstfx Fractal Sessions🔋
Liquidity Analysis🙏🏻 Liquidity Analysis is 1 of 2 structural layer / orderflow layer analysis scripts. Both are independent so can’t be released together as a single script, but should be used together. The second one which is called (Signed) Volume Analysis is incoming.
The same math used in this script can be applied on other types of profile-like data: orderbooks, trading volumes of all options for each strike.
Important: market or volume profile, just as orderbooks and options traded volume by strikes, are all liquidity ‘estimates’, showing where liquidity is more likely or less likely to be. These estimates however, especially combined with other info, are really useful and reliable.
This script works with inferred volumes vs the provided one. It's the better choice for equities, bonds; neutral choice for currencies; and suboptimal choice for natural & artificial commodities.
Contents:
Output description;
How to analyze & use the outputs;
How to use it together with upcoming (Signed) Volume Analysis script;
How did I use both scripts to finish The Leap profitably and skipped many losses.
1. Output description
Color of the profile reflects the liquidity imbalance state: red is negative, purple is neutral, blue is positive.
Bar coloring represents history values of liquidity imbalance for backtesting purposes. It can be turned on/off in the script's Style settings.
Two purple vertical lines represent calculated borders of excessive liquidity (HVN), scarce liquidity (LVN), and sufficient liquidity (NVN) zones.
Vertical dash line marks the moving window end, this way you can be certain over what exact data you see the profile was built.
2. How to analyze & use the outputs
Setup up the script:
Moving window length: set it to ~ ¼ of your data analysis window. E.g if you see on your charts and use ~ 256 bars, set the length to 64.
Native tick size multiplier: leave it at 0 to calculate optimal number of rows automatically, or set it manually to match native tick size multiples you desire.
Use 2 timeframes: main one and a far lower one 3 steps down, just like on the screenshot.
Native lot size multiplier allows to round profile rows themselves to nearest multiples of native lot size. I added this just in case any1 needs it.
Find out current liquidity imbalance state:
As mentioned before, based on profile color, it can be negative, neutral or positive. This is the state variable that changes slowly and denies/confirms the signals that would be explained in the minute.
I use my own statistically grounded imbalance metric (no hardcoded/learned thresholds), that unlike mainstream imbalance metrics (e.g orderbook imbalance as sum of bids vs sum of asks) provides a natural neutral zone, when liquidity imbalance is ofc there but not strong enough to be considered.
…
Profile-based signals: look at profile shape vs 2 vertical purple lines.
where profile rows exceed the left purple line, these prices are considered HVN. Too much potential liquidity is there.
where profile rows don’t exceed the right purple line, these prices are considered LVN. Potential thin/lack of liquidity is expected there.
where profile rows are in between these 2 purple lines, these are NVN, or neutral liquidity zones.
Trading ruleset itself is based on couple of simple rules:
Only! Use limit orders hence provide liquidity in LVNs and Only! use stop-market orders hence consume liquidity in HVNs;
These orders should be put in advance ‘only’. This is how you discover the direction or orders: you can only put sell limit orders above you and buy limit orders below you, and you can only put buy stop orders above you, and sell stop orders below you.
This is really it. It may look weird, but once you just try to follow these 2 rules letter by letter for 1 hour, you’ll see how liquidity trading works.
Now once you know that, just don’t open new trades against the liquidity imbalance state. So don’t open shorts when the profile is blue, and don’t open longs when it’s red.
The last part is multi-timeframe logic. Prefer to act when a lower timeframe is Not against the main timeframe. That’s all, no multiple higher timeframes are needed.
3. How to use it together with upcoming (Signed) Volume Analysis script.
That upcoming script would also have a mean to generate its own signals, and another state variable called volume imbalance.
So now you’re not only looking at liquidity imbalance but also at volume imbalance that would deny/confirm a profile based signal. You need at least one of these to favor your long or short.
This is the same logic widely used in HFT, where MM bots cancel/shift/resize orders when book is too onesided And ordeflow is one sided as well.
4. How did I use both scripts to finish The Leap profitably and skipped many losses.
Even tho you can use structural information as your main strategic layer, as many so-called orderflow traders do, I traded in objective style: my fade signals were volatility based in essence, and I used ordeflow for better entries and stops, but most importantly to skip losses.
When ‘both‘ liquidity imbalance and volume imbalance (in their main timeframes) were against my trades, I skipped them all, saving many ~$500 stop losses (that was my basis risk unit for the Leap). Unless I had a very strong objective signal, i.e confluence of several signals, or just one higher timeframe signal, I did all these skips.
I traded ~ intraweek timeframe, so I was analyzing either the last 230 30min bars or 1380 5min bars. Both Liquidity Analysis and (signed) Volume Analysis scripts were set to moving window length 46 or 276 for either granulary.
I finished the leap with 9% profit and max DD ~ 5%, a bit short of my goal of 12.5%. If not these 2 scripts I would’ve finished a bit above breakeven I think.
∞
FF calculation Saptarshi ChatterjeeForward factor (in options contexts) measures implied volatility (IV) for a future period between two expirations, like from 30 DTE (days to expiry) front-month to 60 DTE back-month options.
This indicator calculates the FORWARD FACTOR(FF) using 2 IVs of 2 DTEs.
+ve value means front DTE is rich in premium and back expiry is cheap.
-ve value means front DTE IV is cheap and 2nd DTE is expensive
we can use this term structure disbalance to trade calendar spreads with edge.
Mutanabby_AI | ONEUSDT_MR1
ONEUSDT Mean-Reversion Strategy | 74.68% Win Rate | 417% Net Profit
This is a long-only mean-reversion strategy designed specifically for ONEUSDT on the 1-hour timeframe. The core logic identifies oversold conditions following sharp declines and enters positions when selling pressure exhausts, capturing the subsequent recovery bounce.
Backtested Period: June 2019 – December 2025 (~6 years)
Performance Summary
| Metric | Value |
|--------|-------|
| Net Profit | +417.68% |
| Win Rate | 74.68% |
| Profit Factor | 4.019 |
| Total Trades | 237 |
| Sharpe Ratio | 0.364 |
| Sortino Ratio | 1.917 |
| Max Drawdown | 51.08% |
| Avg Win | +3.14% |
| Avg Loss | -2.30% |
| Buy & Hold Return | -80.44% |
Strategy Logic :
Entry Conditions (Long Only):
The strategy seeks confluence of three conditions that identify exhausted selling:
1. Prior Move Filter:*The price change from 5 bars ago to 3 bars ago must be ≥ -7% (ensures we're not entering during freefall)
2. Current Move Filter: The price change over the last 2 bars must be ≤ 0% (confirms momentum is stalling or reversing)
3. Three-Bar Decline: The price change from 5 bars ago to 3 bars ago must be ≤ -5% (confirms a significant recent drop occurred)
When all three conditions align, the strategy identifies a potential reversal point where sellers are exhausted.
Exit Conditions:
- Primary Exit: Close above the previous bar's high while the open of the previous bar is at or below the close from 9 bars ago (profit-taking on strength)
- Trailing Stop: 11x ATR trailing stop that locks in profits as price rises
Risk Management
- Position Sizing:Fixed position based on account equity divided by entry price
- Trailing Stop:11× ATR (14-period) provides wide enough room for crypto volatility while protecting gains
- Pyramiding:Up to 4 orders allowed (can scale into winning positions)
- **Commission:** 0.1% per trade (realistic exchange fees included)
Important Disclaimers
⚠️ This is NOT financial advice.
- Past performance does not guarantee future results
- Backtest results may contain look-ahead bias or curve-fitting
- Real trading involves slippage, liquidity issues, and execution delays
- This strategy is optimized for ONEUSDT specifically — results may differ on other pairs
- Always test before risking real capital
Recommended Usage
- Timeframe:*1H (as designed)
- Pair: ONEUSDT (Binance)
- Account Size: Ensure sufficient capital to survive max drawdown
Source Code
Feedback Welcome
I'm sharing this strategy freely for educational purposes. Please:
- Drop a comment with your backtesting results any you analysis
- Share any modifications that improve performance
- Let me know if you spot any issues in the logic
Happy trading
As a quant trader, do you think this strategy will survive in live trading?
Yes or No? And why?
I want to hear from you guys
LuxyEnergyIndexThe Luxy Energy Index (LEI) library provides functions to measure price movement exhaustion by analyzing three dimensions: Extension (distance from fair value), Velocity (speed of movement), and Volume (confirmation level).
LEI answers a different question than traditional momentum indicators: instead of "how far has price gone?" (like RSI), LEI asks "how tired is this move?"
This library allows Pine Script developers to integrate LEI calculations into their own indicators and strategies.
How to Import
//@version=6
indicator("My Indicator")
import OrenLuxy/LuxyEnergyIndex/1 as LEI
Main Functions
`lei(src)` → float
Returns the LEI value on a 0-100 scale.
src (optional): Price source, default is `close`
Returns : LEI value (0-100) or `na` if insufficient data (first 50 bars)
leiValue = LEI.lei()
leiValue = LEI.lei(hlc3) // custom source
`leiDetailed(src)` → tuple
Returns LEI with all component values for detailed analysis.
= LEI.leiDetailed()
Returns:
`lei` - Final LEI value (0-100)
`extension` - Distance from VWAP in ATR units
`velocity` - 5-bar price change in ATR units
`volumeZ` - Volume Z-Score
`volumeModifier` - Applied modifier (1.0 = neutral)
`vwap` - VWAP value used
Component Functions
| Function | Description | Returns |
|-----------------------------------|---------------------------------|---------------|
| `calcExtension(src, vwap)` | Distance from VWAP / ATR | float |
| `calcVelocity(src)` | 5-bar price change / ATR | float |
| `calcVolumeZ()` | Volume Z-Score | float |
| `calcVolumeModifier(volZ)` | Volume modifier | float (≥1.0) |
| `getVWAP()` | Auto-detects asset type | float |
Signal Functions
| Function | Description | Returns |
|---------------------------------------------|----------------------------------|-----------|
| `isExhausted(lei, threshold)` | LEI ≥ threshold (default 70) | bool |
| `isSafe(lei, threshold)` | LEI ≤ threshold (default 30) | bool |
| `crossedExhaustion(lei, threshold)` | Crossed into exhaustion | bool |
| `crossedSafe(lei, threshold)` | Crossed into safe zone | bool |
Utility Functions
| Function | Description | Returns |
|----------------------------|-------------------------|-----------|
| `getZone(lei)` | Zone name | string |
| `getColor(lei)` | Recommended color | color |
| `hasEnoughHistory()` | Data check | bool |
| `minBarsRequired()` | Required bars | int (50) |
| `version()` | Library version | string |
Interpretation Guide
| LEI Range | Zone | Meaning |
|-------------|--------------|--------------------------------------------------|
| 0-30 | Safe | Low exhaustion, move may continue |
| 30-50 | Caution | Moderate exhaustion |
| 50-70 | Warning | Elevated exhaustion |
| 70-100 | Exhaustion | High exhaustion, increased reversal risk |
Example: Basic Usage
//@version=6
indicator("LEI Example", overlay=false)
import OrenLuxy/LuxyEnergyIndex/1 as LEI
// Get LEI value
leiValue = LEI.lei()
// Plot with dynamic color
plot(leiValue, "LEI", LEI.getColor(leiValue), 2)
// Reference lines
hline(70, "High", color.red)
hline(30, "Low", color.green)
// Alert on exhaustion
if LEI.crossedExhaustion(leiValue) and barstate.isconfirmed
alert("LEI crossed into exhaustion zone")
Technical Details
Fixed Parameters (by design):
Velocity Period: 5 bars
Volume Period: 20 bars
Z-Score Period: 50 bars
ATR Period: 14
Extension/Velocity Weights: 50/50
Asset Support:
Stocks/Forex: Uses Session VWAP (daily reset)
Crypto: Uses Rolling VWAP (50-bar window) - auto-detected
Edge Cases:
Returns `na` until 50 bars of history
Zero volume: Volume modifier defaults to 1.0 (neutral)
Credits and Acknowledgments
This library builds upon established technical analysis concepts:
VWAP - Industry standard volume-weighted price measure
ATR by J. Welles Wilder Jr. (1978) - Volatility normalization
Z-Score - Statistical normalization method
Volume analysis principles from Volume Spread Analysis (VSA) methodology
Disclaimer
This library is provided for **educational and informational purposes only**. It does not constitute financial advice. Past performance does not guarantee future results. The exhaustion readings are probabilistic indicators, not guarantees of price reversal. Always conduct your own research and use proper risk management when trading.
GIX Analizor strategiiGIX Analyzer – Intelligent Time Filters + X Strategy
This script combines the X Strategy with an advanced system for filtering trades based on time intervals. The strategy allows:
Filtering by preset trading hours (active sessions )
Filtering by a fully customizable time interval (hour + minute, Romania time )
Filtering by calendar range (Start Date → End Date)
Simultaneous activation of both time-filter modes for maximum control
Trading only within valid time ranges, while keeping all logic unchanged
This indicator provides high flexibility for testing and optimizing trading entries based on hours, minutes, and calendar periods—while preserving the simplicity and efficiency of any strategy
Pardos Info DashboardThis indicator presents basic data in a concentrated form
Additions to the indicator are welcome by email to gshayp@gmail.com
Trinity ATR Real Move DetectorTrinity ATR Real Move Detector
This ATR Energy Table indicator is one of the simplest yet most powerful filters you can have on a chart when trading short-dated or 0DTE options or swing trades on any timeframe from 1-minute up to 4-hour. Its entire job is to answer the single most important question in intraday and swing trading: “Does the underlying actually have enough short-term explosive energy right now to make a directional position worth the theta and the spread, or is this just pretty candles that will die in ten minutes?”
Most losing 0DTE and short-dated option trades happen because people buy or sell direction on a “nice-looking” breakout or pullback while the underlying is actually in low-energy grind mode. The premium decays faster than the move develops, and you lose even when you’re “right” on direction. This little table stops that from ever happening again.
Here’s what it does in plain English:
Every bar it measures two things:
- The current ATR on whatever timeframe you are using (1 min, 3 min, 5 min, 10 min, etc.). This tells you how big the average true range of the last 14 bars has been — in other words, how violently the stock or index is actually moving right now.
- The daily ATR (14-period on the daily chart). This is your benchmark for “normal” daily movement over the last two–three weeks.
It then multiplies the daily ATR by a small number (the multiplier you set) and compares the two. If the short-term ATR is bigger than that percentage of the daily ATR, the table turns bright green and says “ENOUGH ENERGY”. If not, it stays red and says “NOT ENOUGH”.
Why this works so well:
- Real explosive moves that carry for 0DTE and 1–3 DTE options almost always show a short-term ATR spike well above the recent daily average. Quiet grind moves never do.
- The comparison is completely adaptive — on a high-vol day the threshold automatically rises, on a low-vol day it automatically drops. You never have to guess if “2 points on SPY is big today”.
- It removes emotion completely. You simply wait for green before you even think about clicking buy or sell on an option.
Key settings and what to do with them:
- Energy Multiplier — this is the only number you ever touch. It is expressed as a decimal (0.15 = 15 % of the daily ATR). Lower = more signals, higher = stricter and higher win rate. The tooltip gives you the exact sweet-spot numbers for every popular timeframe (0.09 for 1-minute scalping, 0.13 for 3-minute, 0.14–0.16 for 5-minute, 0.15–0.19 for 10-minute, etc.). Just pick your timeframe once and type the number — done forever.
- ATR Length — leave it at 14. That’s the standard and works perfectly.
- Table Position — move the table to wherever you want on the chart (top-right, bottom-right, bottom-left, top-left).
- Table Size — make the text Tiny, Small, Normal or Large depending on how much screen space you have.
How this helps you make money and stop losing it:
- On most days you will see red 80–90 % of the time — that’s good! It is forcing you to sit on your hands instead of overtrading low-energy chop that eats premium.
- When it finally flips green you know institutions are actually pushing size right now — follow-through probability jumps from ~40 % to 65–75 % depending on the stock and timeframe.
- You stop buying calls on every green candle and puts on every red candle. You only strike when the market is genuinely “awake”.
- Over a week you take dramatically fewer trades, but your win rate and average winner size go way up — which is exactly how consistent intraday option profits are made.
In short, this tiny table is the closest thing to an “edge on/off switch” that exists for short-dated options. Red = preserve capital and go do something else. Green = pull the trigger with confidence. Use it religiously and you’ll immediately feel the difference in your P&L.
TFGI Lite: Technical Fear & Greed Dashboard (All-Assets)📊 TFGI Lite: Technical Fear & Greed Dashboard (All-Assets)
Don't guess the sentiment. Measure it.
不要猜測情緒，去測量它。
🇹🇼 繁體中文：市場情緒的導航儀
什麼是 TFGI Lite？
這是一個簡潔的「市場氣象儀表板」，直接顯示在您的 K 線圖上。它幫助您判斷現在市場是處於「過度恐懼（適合貪婪）」還是「過度貪婪（適合謹慎）」的狀態。適用於股票、加密貨幣、外匯與期貨。
數字代表什麼意義？
分數範圍為 0 到 100：
0 - 25 (極度恐懼 / 綠色區域)：
市場陷入恐慌，價格可能被低估。這通常是尋找買點的機會（別人恐懼我貪婪）。
75 - 100 (極度貪婪 / 紅色區域)：
市場過熱，追高風險極大。這通常是考慮獲利了結或警惕回調的時刻。
25 - 75 (中性震盪)：
市場處於正常波動範圍，順勢操作即可。
儀表板上的三個關鍵數據：
Local TFGI (當前商品)：您現在看的這張圖表（例如比特幣或台積電）的情緒分數。
Global TFGI (全球宏觀)：全球資金的流向與風險偏好（綜合了美股、波動率 VIX、美元與債市）。這就像是「大盤天氣」。如果全球都在下雨（恐慌），您的股票也很難獨善其身。
Spread (情緒溫差)：
如果 Local 分數遠高於 Global，代表這個商品漲過頭了，要注意風險。
如果 Local 分數遠低於 Global，代表這個商品被錯殺了，可能是機會。
🇺🇸 English: Navigate Market Sentiment Simply
What is TFGI Lite?
A clean, professional "Weather Dashboard" for your chart. It quantifies market psychology, helping you decide when to be contrarian. It works on any asset class (Stocks, Crypto, Forex).
How to Read the Numbers (0-100 Score)
0 - 25 (Extreme Fear / Green Zone):
Investors are panicking. The asset may be oversold. Historically, this is often a buying opportunity.
75 - 100 (Extreme Greed / Red Zone):
The market is overheated and FOMO is high. The risk of a correction is increasing. It might be time to take profits.
25 - 75 (Neutral):
Normal market fluctuations.
Key Features on the Dashboard:
Local TFGI: The sentiment score of the specific asset you are watching right now.
Global TFGI: The sentiment of the entire global market (Aggregating SPY, VIX, DXY, and Bonds). Think of this as the "Macro Tide". It's hard to swim against the tide.
Spread: The difference between the Asset and the Global market.
Positive Spread: This asset is hotter than the global market (Potential Overvaluation).
Negative Spread: This asset is weaker than the global market (Potential Undervaluation).
🇯 日本語：相場の「過熱感」を一目で判断
TFGI Liteとは？
チャート上に表示されるシンプルな「センチメント（市場心理）ダッシュボード」です。市場が「悲観（買い時）」にあるのか、「楽観（売り時）」にあるのかを客観的な数値で示します。株、仮想通貨、FXなど、あらゆる資産に対応しています。
スコアの見方（0〜100）
0 - 25 (極度の恐怖 / 緑エリア):
市場はパニック状態です。売られすぎの可能性があり、逆張りの買いチャンスとなることが多いゾーンです。
75 - 100 (極度の強欲 / 赤エリア):
市場は過熱しており、イケイケの状態です。暴落のリスクが高まっているため、利益確定を検討する警戒ゾーンです。
25 - 75 (中立):
通常の変動範囲内です。
ダッシュボードの3つの重要指標:
Local TFGI (個別): 現在表示している銘柄のセンチメントスコアです。
Global TFGI (全体): 世界市場全体のムード（米国株、VIX指数、ドル、債券を総合分析）。「地合い」を確認するために使います。
Spread (乖離): 個別銘柄と世界市場の温度差。この数値が大きい場合、その銘柄だけが異常に買われすぎている可能性があります。
🇰🇷 한국어: 시장의 공포와 탐욕을 한눈에
TFGI Lite란 무엇인가요?
차트 위에 직접 표시되는 깔끔한 "시장 심리 계기판"입니다. 현재 시장이 '과도한 공포(저점 매수 기회)'인지 '과도한 탐욕(고점 매도 주의)'인지 판단하는 데 도움을 줍니다. 주식, 코인, 외환 등 모든 자산에 적용 가능합니다.
숫자가 의미하는 것 (0~100점)
0 - 25 (극심한 공포 / 초록색 구간):
투자자들이 패닉에 빠져 투매가 나옵니다. 역사적으로 이는 저가 매수(Buy the dip)의 기회일 가능성이 높습니다.
75 - 100 (극심한 탐욕 / 빨간색 구간):
시장이 과열되었습니다. 추격 매수는 위험하며, 이익 실현을 고려하거나 조정을 대비해야 할 때입니다.
25 - 75 (중립):
일반적인 시장 변동 구간입니다.
대시보드의 핵심 데이터:
Local TFGI (개별 종목): 지금 보고 계신 차트(코인/주식)의 자체적인 심리 점수입니다。
Global TFGI (글로벌 매크로): 전 세계 자금의 흐름과 위험 선호도(미국 증시, VIX, 달러, 채권 종합). 시장 전체의 "날씨"를 알려줍니다。
Spread (괴리율): 개별 종목과 글로벌 시장 간의 온도 차이. 개별 종목 점수가 글로벌보다 훨씬 높다면, 해당 종목이 과매수되었을 수 있습니다。
KernelFunctionsLibrary "KernelFunctions"
This library provides non-repainting kernel functions for Nadaraya-Watson estimator implementations. This allows for easy substition/comparison of different kernel functions for one another in indicators. Furthermore, kernels can easily be combined with other kernels to create newer, more customized kernels.
rationalQuadratic(_src, _lookback, _relativeWeight, startAtBar)
Rational Quadratic Kernel - An infinite sum of Gaussian Kernels of different length scales.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_relativeWeight (simple float) : Relative weighting of time frames. Smaller values resut in a more stretched out curve and larger values will result in a more wiggly curve. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel.
startAtBar (simple int)
Returns: yhat The estimated values according to the Rational Quadratic Kernel.
gaussian(_src, _lookback, startAtBar)
Gaussian Kernel - A weighted average of the source series. The weights are determined by the Radial Basis Function (RBF).
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
startAtBar (simple int)
Returns: yhat The estimated values according to the Gaussian Kernel.
periodic(_src, _lookback, _period, startAtBar)
Periodic Kernel - The periodic kernel (derived by David Mackay) allows one to model functions which repeat themselves exactly.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Periodic Kernel.
locallyPeriodic(_src, _lookback, _period, startAtBar)
Locally Periodic Kernel - The locally periodic kernel is a periodic function that slowly varies with time. It is the product of the Periodic Kernel and the Gaussian Kernel.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Locally Periodic Kernel.
