TruTrend Market Bias FREETruTrend — Market Bias & Signal Indicator (Free)
TruTrend (Free) is a real-time market bias and signal indicator designed to help traders see trend direction and key buy/sell moments with clarity.
This version focuses on core trend structure and momentum shifts, giving you a clean visual read of the market without clutter. Signals update live and are intended to help traders stay on the right side of the move.
TruTrend Free is built to be simple, fast, and easy to use — ideal for traders who want structure without complexity.
What the Free Version Provides
• Market bias (bullish vs bearish)
• Basic buy & sell signals
• Trend structure visualization
• Clean, easy-to-read chart layout
Important Notes
• Signals are real-time and non-repainting
• Designed for general guidance, not trade automation
• Works across all markets and timeframes
Upgrade to Pro / Pro+
For advanced filtering, earlier entries, stronger confirmations, and premium features, check out TruTrend Pro and Pro+.
🔓 Upgrade access: whop.com
Forecasting
Sri - Bollinger Bands (Custom TF) Sri – Bollinger Bands (Custom Timeframe) is an enhanced Bollinger Bands indicator designed to provide higher-timeframe volatility structure directly on a lower-timeframe chart.
Instead of calculating bands on the chart’s native timeframe, this script allows traders to select an independent custom timeframe (CTF) for Bollinger Band computation, enabling clearer trend context, noise reduction, and multi-timeframe confluence.
This is not a visual mashup. The indicator uses true higher-timeframe statistical calculations via request.security(), ensuring that the basis, deviation, and bands are mathematically derived from the selected timeframe candles, not approximated or resampled.
🔍 How It Works (Conceptual Explanation)
Custom Timeframe Logic
Bollinger Bands are calculated entirely on the user-selected timeframe (e.g., 1H, 4H, Daily), regardless of the chart timeframe.
This allows traders on 5-min or 15-min charts to trade within higher-timeframe volatility envelopes.
Flexible Moving Average Basis
The middle band (basis) supports multiple MA types:
SMA
EMA
SMMA (RMA)
WMA
VWMA
This flexibility lets traders adapt the band behavior to trend-following, mean-reversion, or volume-weighted strategies.
Standard Deviation Envelope
Upper and lower bands are derived using true standard deviation from the selected timeframe’s price data.
The multiplier is user-controlled, allowing tighter or wider volatility envelopes.
Overlay-Friendly Design
Bands are plotted directly on price with optional offset support.
A soft background fill visually highlights the volatility zone without obscuring candles.
🧠 Why This Indicator Is Useful
Eliminates the need to switch charts to view higher-timeframe Bollinger Bands
Helps identify:
HTF support & resistance zones
Volatility expansion and contraction
Mean-reversion opportunities inside HTF structure
Especially effective for:
Intraday traders trading in the direction of HTF bands
Scalpers using HTF volatility boundaries as dynamic targets
Swing traders aligning entries with higher-timeframe compression or breakout zones
⚙️ Inputs Explained
Custom Timeframe – Timeframe used for Bollinger Band calculation
Length – Lookback period for MA and standard deviation
Basis MA Type – Choice of moving average for the middle band
Source – Price source (Close, HL2, etc.)
StdDev Multiplier – Controls band width
Offset – Visual displacement only (does not affect calculations)
📈 Example Use Cases
Trade 5-minute breakouts when price expands beyond the 1-hour upper band
Look for mean-reversion setups when price stretches outside daily Bollinger Bands
Combine with volume, VWAP, or trend filters for confirmation
🛡️ Notes
This script focuses on clarity and structure, not signal repainting or alerts.
Calculations are transparent and consistent with standard Bollinger Band methodology, enhanced through multi-timeframe statistical integrity.
Week Levels (OHLC, Settlement, CE) [Tradeisto]Weekly Levels (Tradeisto) is a sophisticated tool designed to bring institutional-grade weekly analysis to your chart. It goes beyond simple horizontal lines by combining authoritative Settlement data with pixel-perfect origination times, ensuring your levels are both accurate and contextually precise.
Key Features
Dual Precision Technology:
Price Accuracy: Uses the authoritative Weekly timeframe to capture Settlement
prices,
ensuring your levels match official exchange data (critical for Futures).
Visual Precision: Uses 15-minute timeframe data to pinpoint the exact origination
time of the High and Low. Your lines start exactly when the level was created, not just at the
"start of the week".
Dynamic Current Week:
Live Updates: Watch the "Current Week" Open, High, Low, and CE (50%) develop in
real-time.
Auto-Rename: When the trading week closes (e.g., Friday Settlement), the "Current"
labels automatically switch to "Week Open/High/Low" labels, seamlessly transitioning into
history.
Smart Labeling:
"Prev." Prefix: Automatically distinguishes the immediate previous week (labeled
"Prev.") from older history (labeled "Week").
Settlement Awareness: Automatically labels the Close as "Settlement" for Futures
contracts when enabled, and "Close" for other assets.
Historical Reference: Configurable "Weeks to Show" allows you to keep a clean chart or dig deep into past market structure.
Settings
Settlement as Close: Toggle this to prioritize the Settlement price for the Weekly Close (Standard for Futures analysis).
Weeks to Show: Control how much history remains on your chart.
Current Week Visibility: Toggle individual components for the developing week (Open, High, Low, CE).
Tradeisto delivers a professional, clean, and highly accurate weekly framework for serious market analysis.
Risk Reward Table Only UYRisk–Reward Template (UY) — How to Read & Use It
This tool is designed to make position risk and reward fully transparent before you trade.
What You Enter (Inputs)
Account Size ($)
Your total trading capital.
Account Invested ($)
How much capital you are allocating to this position before leverage.
Entry and Exit Prices
How to Use This Tool Properly
If Total Risk % feels uncomfortable, the trade is oversized.
If Stop % is large, If Gain doesn’t justify Risk, skip the trade.
If Leverage inflates risk too much, reduce size
Session Levels (RTH OHLC, Settlement and others) [Tradeisto]Session Levels (Tradeisto) is a precision-focused trading tool designed to automatically plot the most critical price levels for intraday and swing analysis. Built for traders who rely on session structure, this indicator keeps your chart clean by managing levels dynamically.
Key Features
RTH Structure: Automatically detects and plots Regular Trading Hours (RTH) High, Low, Open, and Close.
Key Daily Levels: Displays essential daily references including Settlement, Daily Open, and Midnight Open.
Smart Mitigation: Levels are dynamic—they remain on your chart until price acts upon them. Once a level is "mitigated" (touched), it is automatically removed to keep your workspace uncluttered.
Real-Time Visibility: Mitigated levels stay visible for the duration of the current bar, so you never miss a reaction in real-time.
Precision Origination: Unlike standard indicators, our lines originate from the exact timestamp where the level was created. This ensures pixel-perfect accuracy on lower timeframes (e.g., 1m, 5m).
Multi-Asset Support: Intelligent RTH detection for major asset classes including:
Indices (NQ, ES, YM)
Metals (Gold, Silver)
Energy (Crude, NG)
Currencies & Grains
Manual Mode for custom session times.
Customization
Fully customizable colors for every level type.
Adjustable lookback/history depth (choose how many days of past levels to keep).
Toggle visibility for individual components (e.g., show only Settlement and RTH High/Low).
Tradeisto provides the clarity you need to trade session levels with confidence.
Spot Taker Flow & Early Warning System How Does This Code Detect a "Fake" Rise?
Spot VWMA Logic: The moving average looks not only at the price but also at how much "spot volume" is circulating at that price.
Fake Rise Scenario: If the price (candles) is going up but the Yellow (Binance) or Blue (Coinbase) lines we've drawn are below it, or the price is drooping to the level of these lines; know that the rise is being triggered by bots in futures trading, not spot buyers. This is a "Fake" rise.
Confirmed Rise: If the price is above all these L1 lines, there may be "real money behind it".
Algorithmic Regime Classifier - Lovable Chart**Join our Discord community for further discussion, updates, and help:**
discord.gg
---
### **Algorithmic Regime Classifier (Market Regime Scanner Pro)**
The **Algorithmic Regime Classifier** is a comprehensive, all-in-one market intelligence system designed to remove the noise from your charts. By combining volatility, momentum, volume, and multi-timeframe analysis, this indicator identifies the specific "Regime" the market is currently in—helping you trade *with* the flow rather than against it.
From detecting "Master Pattern" squeezes to identifying institutional order blocks and volume spikes, this tool acts as your automated trading analyst.
---
### **🌟 Key Features**
#### **1. Market Regime Detection (The Core Engine)**
The indicator automatically classifies price action into clear color-coded phases, removing analysis paralysis:
* **🔵 Contraction (Blue):** The "Squeeze." Volatility is low, and energy is building. *Strategy: Wait for the breakout.*
* **🟨 Expansion (Yellow):** The "Breakout." Volatility is expanding rapidly from a squeeze.
* **🟩 Strong Uptrend (Green):** Confirmed bullish trend with volume and ADX support.
* **🟥 Strong Downtrend (Red):** Confirmed bearish trend with volume and ADX support.
* **⬜ Normal/Weak Range:** Low probability choppy zones.
#### **2. 🤖 AI Smart Companion**
A unique text-based assistant located on your chart that interprets all data points in real-time. It provides:
* **Current Status:** (e.g., "MASTER PATTERN: CONTRACTION")
* **Actionable Advice:** (e.g., *"Value building in progress. STAY FLAT."* or *"Institutional Entry Detected! Trail stops."*)
* **Visual Confidence:** Changes color based on the strength of the setup (Green for Go, Purple for Trap, Blue for Wait).
#### **3. Multi-Timeframe (MTF) Bias Dashboard**
Don't trade in a vacuum. The pro dashboard analyzes **Trend, Money Flow, Momentum, Volume, and Volatility** across timeframes ranging from **1 minute to Monthly**.
* **Confluence Check:** Calculates a composite score to tell you if "Buyers are in Control" or if there are "Mixed Signals."
* **Anchoring:** Checks higher timeframes to ensure you aren't scalping against a massive trend.
#### **4. Smart Money Concepts (SMC) & Structure**
* **Order Blocks:** Automatically plots Bullish and Bearish order blocks based on consolidation and volume breakouts. Includes mitigation logic (blocks disappear when price tests them).
* **Support & Resistance:** Dynamic pivot-based S/R levels that track when zones are tested and broken.
#### **5. Quant Delta Volume Bubbles**
Detects hidden institutional activity using statistical Z-Scores.
* **Momentum Events:** Large aggressive buying/selling.
* **Absorption:** Passive limit orders absorbing aggressive market orders (often marks reversals).
* **Ghost Lines:** Visualizes where large liquidity entered the market, acting as future defense levels.
#### **6. VIX Exhaustion Signals**
Uses a calculated "Fear Index" (Williams Vix Fix) combined with Bollinger Bands to identify market bottoms and top-exhaustion points.
* **Signals:** High-contrast arrows and labels indicating potential reversals when price is overextended.
---
### **🛠️ How to Trade This System**
**The "Master Pattern" Strategy:**
1. **Wait for Blue (Contraction):** Look for the blue background and "Squeeze" signals. This indicates energy storage.
2. **Await the Breakout:** Watch for the transition to **Yellow (Expansion)** or **Green/Red (Trend)**.
3. **Confirm with AI & MTF:** Check the AI Companion text. If it says "IGNITION" and the MTF Dashboard shows alignment (e.g., Buyers in Control), enter the trade.
4. **Target:** Use the generated Support/Resistance lines or Order Blocks as take-profit targets.
---
### **Settings & Customization**
* **Regime Sensitivity:** Adjust the Contraction/Expansion factors to fit your asset's volatility.
* **Dashboard Positioning:** Move the AI Companion and MTF tables to any corner of the screen to fit your layout.
* **Visuals:** Toggle specific features (Order Blocks, Bubbles, S/R) on or off to keep your chart clean.
---
**Disclaimer:**
*This indicator is for educational and analytical purposes only. Past performance does not guarantee future results. Always manage your risk.*
Apex Wallet - Lorentzian Classification: Adaptive Signal SuiteOverview The Apex Wallet Lorentzian Classification is a high-performance signal engine that utilizes an adaptive multi-feature approach to identify high-probability entry points. It synthesizes five distinct technical features—RSI, CCI, ADX, MFI, and ROC—to calculate a weighted trend bias.
Dynamic Adaptation The core strength of this indicator is its ability to automatically recalibrate its internal periods based on your selected Trading Mode.
Scalping: Uses ultra-fast periods (e.g., RSI 7, ADX 10) for quick reaction on 1m to 5m charts.
Day-Trading: Balanced settings (e.g., RSI 14, ADX 14) optimized for 15m to 1h timeframes.
Swing-Trading: Smooth, long-term filters (e.g., RSI 21, ADX 20) to capture major market shifts.
Logic & Signal Flow
Feature Extraction: The script calculates five momentum and volatility features using the current close price.
Signal Summation: Each feature contributes to a global signal score based on established technical thresholds.
EMA Smoothing: The raw signal is processed through an EMA filter to eliminate market noise and false breakouts.
Execution: Clear BUY and SELL labels are printed directly on the chart when the smoothed score crosses specific conviction levels.
Key Features:
Zero-Configuration: No need to manually adjust lengths; simply pick your trading style.
Clean Visuals: High-fidelity labels (BUY/SELL) with integrated alert conditions for automation.
Prop-Firm Ready: Ideal for traders needing fast confirmation for high-conviction trades.
LINHFX Bull Bear DivergenceBull Bear Divergence is a momentum-based indicator designed to analyze bullish and bearish strength and identify divergence between price action and market momentum.
It helps traders detect:
Bullish divergence (potential upside reversal)
Bearish divergence (potential downside reversal)
Shifts in buying and selling pressure
This indicator is ideal for Price Action, Smart Money Concept (SMC), intraday and swing trading, and works across multiple timeframes and markets such as Forex, Gold, Crypto, and Indices.
Best used in combination with market structure, key levels, and risk manageme
LinhFX Bull Bear Divergence 2.0 Bull Bear Divergence is a momentum-based indicator designed to analyze bullish and bearish strength and identify divergence between price action and market momentum.
It helps traders detect:
Bullish divergence (potential upside reversal)
Bearish divergence (potential downside reversal)
Shifts in buying and selling pressure
This indicator is ideal for Price Action, Smart Money Concept (SMC), intraday and swing trading, and works across multiple timeframes and markets such as Forex, Gold, Crypto, and Indices.
Best used in combination with market structure, key levels, and risk manageme
Custom Daily POC with Date LabelsThis indicator provides a clear view of today's control levels in relation to the point of control from previous days, revealing where the big whales are navigating and manipulating the market.
It's a simple yet genius tool...
Advanced kNN Target Price and TimeDeliver Target Price, Target Price probability and time to reach.
Machine Learning Based.
Eccodax Robust k-NN Machine Learning LorentzianHere is the complete, final, corrected, and clean code, already including:
✅ Fixed shadowing of the variable d
✅ No compilation warnings
✅ No temporal leaks
✅ Target = real future return
✅ Robust Lorentzian distance
✅ Correct Matrix structure
✅ Consistent feature engineering
✅ Min-Max normalization
✅ Weighted k-NN inference
✅ Correct price reconstruction
1. What this code is
It is a predictive indicator based on classic Machine Learning (k-Nearest Neighbors), fully implemented in PineScript v6, designed to:
Learn historical market patterns
Compare the current state with similar past states
Estimate the expected future price movement
Reconstruct a projected price consistent with the current level
It is not an oscillator, it is not a traditional technical indicator, and it does not react only to the immediate past.
2. What the Model Learns (Supervised Learning)
2.1 Features (Input Variables)
The model uses three dimensions of information, all normalized by Z-score:
Return
Measures the percentage change in price
Captures the immediate momentum of the market
Momentum (ROC)
Measures acceleration or deceleration of the movement
Differentiates trends from consolidations
Volatility
Measures the degree of market uncertainty
Adjusts the weight of strong movements vs. noise
These three variables form a market state vector.
2.2 Normalization (Z-Score)
Each feature is converted to:
Mean ≈ 0
Standard deviation ≈ 1
This ensures that:
No variable dominates the distance
The statistical comparison is valid
The model is stable in different price regimes
2.3 Target (Predicted Variable)
The model does not predict absolute price. It learns:
Observed future return after forecastBars
That is:
Learns movement, not level
Eliminates historical bias
Avoids predictions inconsistent with the current price
3. How the model makes the prediction
3.1 Search for similar patterns (k-NN)
For each current candle, the model:
Analyzes the last lookback candles
Calculates the Euclidean distance between the current state and each past state
Selects the k most similar states
Observes what happened after them
3.2 Inference
The predicted return is calculated as:
Weighted average of the future returns of the neighbors
Weights inversely proportional to the distance
More similar states → greater influence.
4. Price Reconstruction (Key Information)
From the predicted return, the model reconstructs:
Predicted Price = Current Close × (1 + Predicted Return)
Predicted Price = Current Close × (1 + Predicted Return)
This ensures that:
The forecast respects the current market level
The output is visually interpretable
There is no regression to past regimes
5. Relevant Information the Indicator Delivers
5.1 Predicted Price (Green Line)
What it is: Estimated price after forecastBars.
How to use:
Above the current price → bullish bias
Below → bearish bias
Large distance → expectation of strong movement
5.2 Predicted Return (Implicit)
Even though not plotted directly, it is the most important information in the model.
Positive → expectation of appreciation
Negative → expectation of decline
Negative → expectation of decline
Near zero → sideways market
5.3 Directional Classification (optional)
The model also acts as a binary classifier:
High if expected return > 0
Low if expected return < 0
This is used as:
Noise filter
Trend confirmation
False signal reduction
5.4 Implicit statistical context
The indicator carries information that is not visual, but is fundamental:
Market regime (trending vs. sideways)
Statistical similarity with the past
Relative confidence (via distance from neighbors)
6. What this indicator does NOT do
It is important to align expectations:
❌ Does not predict exogenous events
❌ Does not anticipate gaps
❌ Does not work well on illiquid assets
❌ Does not extrapolate long trends
k-NN replicates patterns, does not create scenarios Unprecedented.
7. Where this model works best
Markets with repetitive structure
Medium timeframes (5m – 1D)
Liquid assets
Environments with alternating regimes
8. How to use it in practice (professional recommendation)
Ideal use:
k-NN direction → bias
Technical indicator → timing
Risk management → execution
Never use it in isolation for entry.
9. Executive summary
This code delivers:
A functional supervised ML model in Pine
Prediction consistent with the current price
Statistical market direction
Reduction of historical bias
Solid foundation for quantitative strategies
Eccodax Advanced kNN Lorentziano Matrix1. What this code is
It is a predictive indicator based on classic Machine Learning (k-Nearest Neighbors), fully implemented in PineScript v6, designed to:
Learn historical market patterns
Compare the current state with similar past states
Estimate the expected future price movement
Reconstruct a projected price consistent with the current level
It is not an oscillator, it is not a traditional technical indicator, and it does not react only to the immediate past.
2. What the Model Learns (Supervised Learning)
2.1 Features (Input Variables)
The model uses three dimensions of information, all normalized by Z-score:
Return
Measures the percentage change in price
Captures the immediate momentum of the market
Momentum (ROC)
Measures acceleration or deceleration of the movement
Differentiates trends from consolidations
Volatility
Measures the degree of market uncertainty
Adjusts the weight of strong movements vs. noise
These three variables form a market state vector.
2.2 Normalization (Z-Score)
Each feature is converted to:
Mean ≈ 0
Standard deviation ≈ 1
This ensures that:
No variable dominates the distance
The statistical comparison is valid
The model is stable in different price regimes
2.3 Target (Predicted Variable)
The model does not predict absolute price. It learns:
Observed future return after forecastBars
That is:
Learns movement, not level
Eliminates historical bias
Avoids predictions inconsistent with the current price
3. How the model makes the prediction
3.1 Search for similar patterns (k-NN)
For each current candle, the model:
Analyzes the last lookback candles
Calculates the Euclidean distance between the current state and each past state
Selects the k most similar states
Observes what happened after them
3.2 Inference
The predicted return is calculated as:
Weighted average of the future returns of the neighbors
Weights inversely proportional to the distance
More similar states → greater influence.
4. Price Reconstruction (Key Information)
From the predicted return, the model reconstructs:
Predicted Price = Current Close × (1 + Predicted Return)
Predicted Price = Current Close × (1 + Predicted Return)
This ensures that:
The forecast respects the current market level
The output is visually interpretable
There is no regression to past regimes
5. Relevant Information the Indicator Delivers
5.1 Predicted Price (Green Line)
What it is: Estimated price after forecastBars.
How to use:
Above the current price → bullish bias
Below → bearish bias
Large distance → expectation of strong movement
5.2 Predicted Return (Implicit)
Even though not plotted directly, it is the most important information in the model.
Positive → expectation of appreciation
Negative → expectation of decline
Negative → expectation of decline
Near zero → sideways market
5.3 Directional Classification (optional)
The model also acts as a binary classifier:
High if expected return > 0
Low if expected return < 0
This is used as:
Noise filter
Trend confirmation
False signal reduction
5.4 Implicit statistical context
The indicator carries information that is not visual, but is fundamental:
Market regime (trending vs. sideways)
Statistical similarity with the past
Relative confidence (via distance from neighbors)
6. What this indicator does NOT do
It is important to align expectations:
❌ Does not predict exogenous events
❌ Does not anticipate gaps
❌ Does not work well on illiquid assets
❌ Does not extrapolate long trends
k-NN replicates patterns, does not create scenarios Unprecedented.
7. Where this model works best
Markets with repetitive structure
Medium timeframes (5m – 1D)
Liquid assets
Environments with alternating regimes
8. How to use it in practice (professional recommendation)
Ideal use:
k-NN direction → bias
Technical indicator → timing
Risk management → execution
Never use it in isolation for entry.
9. Executive summary
This code delivers:
A functional supervised ML model in Pine
Prediction consistent with the current price
Statistical market direction
Reduction of historical bias
Solid foundation for quantitative strategies
Relevant information provided by this code
1. Forecasted price (line)
Statistical projection consistent with the current level
Based on similar historical patterns
2. Implicit direction
Return > 0 → bullish bias
Return < 0 → bearish bias
3. Structural robustness
Lower sensitivity to outliers
Lower scale bias
Better adaptation to different regimes
This refactored version introduces significant improvements based on modern quantitative Machine Learning practices (similar to those found in jdehorty's "Lorentzian Classification" indicator):
Lorentzian Distance: Replaces the Euclidean distance (which is affected by noise and outliers) with Lorentzian Distance, which is much more robust for financial markets.
Matrix Structure: Uses the matrix object in Pine V6 to manage training data more efficiently and cleanly than loose arrays.
Feature Engineering (WaveTrend & RSI): Replaces simple Momentum with normalized indicators (RSI, WaveTrend, CCI, ADX), better capturing market dynamics.
Min-Max Normalization: Features are normalized on a 0-100 scale so that indicators with different magnitudes do not distort the distance calculation.
Inverse Distance Weighting: Instead of a simple average, the nearest neighbors (most similar) have greater weight in the prediction.
VSA 2.0ENG
VSA 2.0 is a next-generation Volume Spread Analysis based on tick volume and price behavior, stripped of classical rules and indicators.
It focuses on context, effort vs result, and institutional intent, filtering retail noise to read what smart money is doing, not what textbooks say.
Follow me on YOUTUBE and Telegram!
BehindTheScalper
ETH&BTCThis script is a streamlined trend-following strategy designed specifically for major crypto pairs like ETH and BTC.
It eliminates the noise by using a hardcoded, "black box" logic that combines Price Action with Trend Momentum. Instead of relying on lagging indicators alone, it analyzes market structure, volume flows, and directional strength to identify high-probability entry points.
Minimalist Integrated Trading[WuYaa]图表出现信号后看大时间框架趋势是否一致
例：15分钟出现信号，看1小时或4小时趋势是否与15分钟框架一致
After a signal appears on the chart, check whether the trend on a larger timeframe is consistent.
For example: if a signal appears on the 15-minute chart, check whether the trend on the 1-hour or 4-hour chart is consistent with the 15-minute timeframe.
SPY / DIA Divergence Z-Score (30s Optimized)SPY / DIA Divergence Z-Score (30s Optimized) is a short-term relative strength indicator designed for opening-range mean reversion trading.
This script measures normalized return divergence between SPY and DIA, converts it into a Z-score, and highlights statistically extreme conditions where short-term reversion is more likely to occur.
Key characteristics:
Optimized specifically for the 30-second timeframe
Uses EMA-smoothed returns to reduce microstructure noise
Focuses on divergence and reversion, not trend-following
Includes a session filter targeting the early NYSE open
Designed as a decision-support tool, not an automated strategy
Intended use:
Best used between 9:32–9:45 ET
Works best when combined with VWAP and price action
Signals indicate potential exhaustion and reversion zones, not guaranteed entries
Important notes:
No trade entries or exits are provided
No repainting
Not financial advice
Meant for discretionary traders who understand execution risk on lower timeframes
This indicator is most effective when used with disciplined risk management and strict time-of-day constraints.
How to Use:
Apply the indicator to a 30-second chart (designed for 30s only)
Trade only during the early NYSE session (approx. 9:32–9:45 ET)
Watch for Z-Score extremes beyond the upper or lower thresholds
Look for stalling behavior (loss of momentum) at extreme readings
Use in confluence with VWAP and price action for confirmation
Signals highlight potential mean-reversion zones, not automatic entries
Use tight risk management and avoid overtrading
Disclaimer:
This script is provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or trade signals. Past performance is not indicative of future results. Use at your own risk.
Gold Premium Histogram
Compares Altins1 to gram gold in turkish lira to see the deviation and suggesting when to arbitrage
Altcoins Buy&Sell 1h tw: stoova0This strategy is designed for Altcoins on the 1H timeframe. It includes hardcoded filters based on specific user requirements. To set an alert, simply open the chart, select the indicator, and choose 'Any alert() function call' from the options.
BTC Buy&Sell 1h tw: stoova0Twitter: stoova0
This works exclusively on the BTC 1h chart. It is recommended to use the OKX exchange chart (specifically BtcUsdt.p) for analysis and trading. To set an alert, simply open the chart, select the indicator, and choose 'Any alert() function call' from the options.
reddddicatorStrategy: Sell 0dte TVC:SPX credit spreads beyond the upper and lower levels.
Time frame: 15min
Session-Anchored Volatility Expansion Bands
reddddicator is a session-aware volatility expansion framework designed to model next-session price dispersion using a multi-day realized range aggregation with custom normalization.
The indicator does not rely on ATR, ADR, standard deviation bands, or moving-average–based volatility estimators. Instead, it derives projected price boundaries from completed daily range realizations , selectively anchored to the most recent fully confirmed daily close based on session state.
Conceptual Methodology (High-Level)
The model samples a fixed window of completed daily high-low ranges.
These ranges are aggregated and normalized using a non-standard divisor , intentionally reducing sensitivity to single-day volatility spikes.
The resulting expansion value is anchored to the last confirmed daily settlement , dynamically determined based on whether the current trading session is open or closed.
Symmetric forward-projected upper and lower volatility bands are plotted and extended into the next session.
This approach is designed to reflect realized volatility expansion tendencies , rather than implied volatility or trend continuation.
Analytical Purpose
The projected bands function as statistical excursion boundaries, intended to identify areas where price extension risk asymmetrically increases.
The indicator is particularly suited for:
Short-duration options frameworks (e.g., TVC:SPX 0DTE credit spreads)
Mean-reversion and volatility exhaustion studies
Contextual risk placement rather than directional forecasting
reddddicator does not generate trade signals and should be used as a volatility reference layer, in conjunction with the user’s own execution logic and risk controls.
Timeframe & Instrument Scope
Calculations are derived from daily market data
Display is optimized for intraday charting
Most effective on liquid index products (e.g., SP:SPX SPX), but adaptable to other instruments
This script does not reproduce ATR, ADR, Bollinger Bands, or any publicly available volatility indicator. While it uses daily range data as an input, the aggregation, normalization, and session-aware anchoring logic are custom implementations developed by the author and are not derived from open-source TradingView scripts or educational materials.
Disclaimer
This indicator is provided for educational and analytical purposes only. It does not constitute financial advice, trade recommendations, or investment guidance. Past behavior of volatility or price expansion does not guarantee future outcomes. Users are solely responsible for their trading decisions, position sizing, and risk management.
