ATR Trailing Stop (Seemple)The ATR Trailing Stop (Seemple) is a clean and intuitive trend following indicator that helps traders visualise dynamic stop levels based on market volatility.
1. How it works:
Uses the Average True Range (ATR) to calculate trailing stop levels.
The stop dynamically adjusts with price movement:
Rises in an uptrend to lock in gains.
Falls in a downtrend to protect against reversals.
Incorporates a flip condition that identifies potential trend shifts when price crosses above or below the stop level.
2. Customisable Inputs:
ATR Period : Defines the sensitivity of the volatility calculation.
ATR Multiple : Sets how tight or wide the stop should be based on ATR.
3. Application:
Ideal for trend-following strategies, trailing stop placement, and visual guidance for exit signals.
Penunjuk dan strategi
15min intervalsindicator displays 4 15 minute intervals within the hour. this simple indicator can be used for effective scalping.
VWEMA-Based Trend Strength IndicatorThis script plots the strength and direction of a trend as the percentage difference between two volume weighted EMAs.
CipherMatrix Dashboard (MarketCipher B)Pre-compute MarketCipher-B values for each fixed timeframe (5 m, 15 m, 30 m, 60 m, 4 H, Daily).
Pass those values into plotRow() instead of calling request.security() inside the helper—removes the style warning.
Added explicit range parameters to table.clear(dash, 0, 0, 2, 6) to satisfy v6’s argument requirement.
This version should compile without the previous warnings/errors. Swap in your real MarketCipher-B histogram when you’re ready, and the dashboard is good to go!
Multi-Indicator PanelMulti-indicator panel that combines the following into one panel:
RSI2
RSI14
%K (for stochastics)
%D (for stochastics)
ADX
DI+
DI-
MACD
MACD signal
MACD histogram
All can be toggled on/off and parameters can be adjusted in settings.
KT Gaussian Bands🎯 Overview
KT Gaussian Bands is an advanced technical indicator that uses Gaussian-weighted smoothing to create dynamic support and resistance bands. This sophisticated algorithm provides high-quality buy and sell signals by filtering market noise and adapting to price volatility.
🔬 How It Works
The indicator employs a Gaussian weighting function to smooth price data, creating more accurate trend detection compared to traditional moving averages. The algorithm calculates:
Dynamic Upper Band (Resistance Level)
Dynamic Lower Band (Support Level)
Adaptive Signal Generation based on price interaction with bands
📊 Key Features
✨ Smart Signal Generation
🔺 BUY Signal: When price crosses below the lower band and bounces back up
🔻 SELL Signal: When price crosses above the upper band and drops back down
Real-time arrows displayed directly on the chart
⚙️ Customizable Parameters
Bandwidth (h): Controls the smoothness of the calculation (Default: 8.0)
Multiplier: Adjusts the sensitivity of the bands (Default: 3.0)
Source: Choose your preferred price source (Default: Close)
Repainting Mode: Toggle between real-time and historical accuracy
🎨 Visual Elements
Color-coded bands (Teal for upper, Red for lower)
Clear arrow signals for entry/exit points
Clean dashboard showing current mode status
📈 Trading Applications
Best Timeframes
Works effectively on all timeframes
Particularly strong on 15M, 1H, and 4H charts
Daily charts for swing trading setups
Trading Strategies
Trend Following: Use signals in the direction of the major trend
Mean Reversion: Trade bounces off the bands in ranging markets
Breakout Confirmation: Validate breakouts with band penetration
Risk Management
Use stop-loss below/above the opposite band
Position size based on band width (wider = higher volatility)
Combine with other indicators for confirmation
⚠️ Important Notes
Repainting Mode
Enabled: Shows the most accurate current analysis (may change on live bars)
Disabled: Historical signals remain fixed (recommended for backtesting)
Best Practices
Don't trade every signal - wait for high-probability setups
Consider market context and overall trend direction
Use proper risk management on every trade
Backtest on your preferred timeframes before live trading
🔧 Settings Guide
Bandwidth (8.0): Lower = More responsive, Higher = Smoother
Multiplier (3.0): Lower = More signals, Higher = Fewer but stronger signals
Repainting: Enable for live analysis, Disable for backtesting
📊 Performance Characteristics
Low Lag: Responds quickly to price changes
Noise Reduction: Filters out false signals effectively
Adaptive: Automatically adjusts to market volatility
Versatile: Works across different market conditions
🎓 Educational Value
This indicator demonstrates advanced mathematical concepts in trading:
Gaussian distribution applications in finance
Dynamic volatility adjustment
Weighted moving average techniques
⭐ Why Choose KT Gaussian Bands?
Mathematically Sound: Based on proven statistical methods
User-Friendly: Clear signals with minimal complexity
Flexible: Adapts to your trading style and timeframe
Reliable: Consistent performance across market conditions
Disclaimer: This indicator is for educational and informational purposes only. Always use proper risk management and never risk more than you can afford to lose. Past performance does not guarantee future results.
CipherMatrix Dashboard (MarketCipher B)does it work. A lightweight, multi-time-frame overlay that turns MarketCipher B data into an at-a-glance dashboard:
Time-frames shown: current chart TF first, then 5 m, 15 m, 30 m, 1 H, 4 H, Daily.
Bias icons:
🌙 = bullish (MCB > 0)
🩸 = bearish (MCB < 0)
Signal icons:
⬆️ = histogram crosses above 0 (potential long)
⬇️ = histogram crosses below 0 (potential short)
Table location: bottom-right of chart; updates on every confirmed bar.
Tao Bounce & Exit + Rip AlertsTao bounce long and short flags/alerts, plus exit alerts (both 2 and 3 ATR). Also includes "rip" indicators to try to flag when a strong trend is in process but all the Tao entry criteria aren't met.
Supports & Resistances with MomentumSupports & Resistances with Momentum is an advanced indicator for scalping and intraday trading It shows dynamic support and resistance levels, clear BUY/SELL signals with TP targets and stop-loss lines, plus optional RSI and volume plots Fully customizable and designed for quick, precise trade decisions.
10/21 EMA Cross10/21 EMA crossover and crossunder indicator. Not timeframe specific. Shows a small arrow at top and bottom of the chart indicating the crossover has occurred.
Swing Structure [HH HL LH LL + 😎 + 👻]Tracks real-time swing structure (HH, HL, LH, LL) using confirmed pivot points. Shows ghost 👻 and cool 😎 emojis at key higher low setups. Great for identifying breakout retests and trend continuation zones. No repaint.
5,8,10,13 EMA Cluster CrossThis is a rough cross signal or signals for the 5,8,10,13 emas to be bullish or bearish, a secondary caution indicator is programed in for the 5,8,10 cross like a yellow caution light. This is not timeframe specific and this indicator is meant to show momentum changes near pivotal points.
Any updates and improvement welcome.
Breakout LabelsThis script labels the highest price of the lowest candle over a period of time. It then labels any bullish breakouts where the close price is higher than the high of the lowest candle.
Crypto Risk-Weighted Allocation SuiteCrypto Risk-Weighted Allocation Suite
This indicator is designed to help users explore dynamic portfolio allocation frameworks for the crypto market. It calculates risk-adjusted allocation weights across major crypto sectors and cash based on multi-factor momentum and volatility signals. Best viewed on INDEX:BTCUSD 1D chart. Other charts and timeframes may give mixed signals and incoherent allocations.
🎯 How It Works
This model systematically evaluates the relative strength of:
BTC Dominance (CRYPTOCAP:BTC.D)
Represents Bitcoin’s share of the total crypto market. Rising dominance typically indicates defensive market phases or BTC-led trends.
ETH/BTC Ratio (BINANCE:ETHBTC)
Gauges Ethereum’s relative performance versus Bitcoin. This provides insight into whether ETH is leading risk appetite.
SOL/BTC Ratio (BINANCE:SOLBTC)
Measures Solana’s performance relative to Bitcoin, capturing mid-cap layer-1 strength.
Total Market Cap excluding BTC and ETH (CRYPTOCAP:TOTAL3ES)
Represents Altcoins as a broad category, reflecting appetite for higher-risk assets.
Each of these series is:
✅ Converted to a momentum slope over a configurable lookback period.
✅ Standardized into Z-scores to normalize changes relative to recent behavior.
✅ Smoothed optionally using a Hull Moving Average for cleaner signals.
✅ Divided by ATR-based volatility to create a risk-weighted score.
✅ Scaled to proportionally allocate exposure, applying user-configured minimum and maximum constraints.
🪙 Dynamic Allocation Logic
All signals are normalized to sum to 100% if fully confident.
An overall confidence factor (based on total signal strength) scales the allocation up or down.
Any residual is allocated to cash (unallocated capital) for conservative exposure.
The script automatically avoids “all-in” bias and prevents negative allocations.
📊 Outputs
The indicator displays:
Market Phase Detection (which asset class is currently leading)
Risk Mode (Risk On, Neutral, Risk Off)
Dynamic Allocations for BTC, ETH, SOL, Alts, and Cash
Optional momentum plots for transparency
🧠 Why This Is Unique
Unlike simple dominance indicators or crossovers, this model:
Integrates multiple cross-asset signals (BTC, ETH, SOL, Alts)
Adjusts exposure proportionally to signal strength
Normalizes by volatility, dynamically scaling risk
Includes configurable constraints to reflect your own risk tolerance
Provides a cash fallback allocation when conviction is low
Is entirely non-repainting and based on daily closing data
⚠️ Disclaimer
This script is provided for educational and informational purposes only.
It is not financial advice and should not be relied upon to make investment decisions.
Past performance does not guarantee future results.
Always consult a qualified financial advisor before acting on any information derived from this tool.
🛠 Recommended Use
As a framework to visualize relative momentum and risk-adjusted allocations
For research and backtesting ideas on portfolio allocation across crypto sectors
To help build your own risk management process
This script is not a turnkey strategy and should be customized to fit your goals.
✅ Enjoy exploring dynamic crypto allocations responsibly!
Low Price RSI CrossoverThis Pine Script indicator is a Multi-Timeframe Low RSI Crossover system that combines three key filtering criteria to identify high-probability buy signals. Here's what it does:
Core Concept
The indicator only generates buy signals when all three conditions are met simultaneously:
Price at Multi-Period Low: Current price must be at or near the lowest point within your selected timeframe (1 week to 5 years, or custom)
RSI Momentum Shift: The smoothed RSI must cross above its signal line (EMA), indicating upward momentum
Below Threshold Entry: Both the RSI and its signal line must be below your threshold level (default 50) when the crossover occurs
Key Features
RSI Smoothing: Uses Hull Moving Average (HMA) to smooth the raw RSI, reducing noise and false signals while maintaining responsiveness.
Flexible Timeframes: Choose from predefined periods (1W, 2W, 3W, 1M, 2M, 3M, 6M, 9M, 1Y, 2Y, 3Y, 5Y) or set a custom number of bars.
Visual Feedback:
Plots the smoothed RSI (blue line) and its signal line (red line)
Shows threshold and overbought levels
Highlights signal bars with green background
Displays tiny green triangles at signal points
Real-time status table showing all conditions
Trading Logic
This is essentially a mean-reversion strategy that waits for:
Price to reach significant lows (value zone)
Momentum to start shifting upward (RSI crossover)
Entry from oversold/neutral territory (below 50 RSI)
Why This Works
By requiring price to be at multi-period lows, you avoid buying during downtrends or sideways chop. The RSI crossover confirms that selling pressure is starting to ease, while the threshold filter ensures you're not buying into overbought conditions.
The combination of these filters should significantly reduce false signals compared to using any single indicator alone.
6-Month Average High/Lows Trend LineThis is an indicator that tracks the 6 month high/low average as a MA and the 6 month high/low average as a flat line.
I added alerts if the price action crosses the high or low line. Also makes a great dynamic channel.
If combined with other confirming indicator like the RSI and/or MACD this could be a very effective tool with respect to levels and 6 month high/lows
TestLibraryLibrary "TestLibrary"
TODO: add library description here
difference(x, y)
TODO: add function description here
Parameters:
x (float) : TODO: add parameter x description here
y (float)
Returns: TODO: add what function returns
MyLibraryLibrary "MyLibrary"
TODO: add library description here
test_function(x, y)
TODO: add function description here
Parameters:
x (float) : TODO: add parameter x description here
y (float)
Returns: TODO: add what function returns
Logistic Regression ICT FVG🚀 OVERVIEW
Welcome to the Logistic Regression Fair Value Gap (FVG) System — a next-gen trading tool that blends precision gap detection with machine learning intelligence.
Unlike traditional FVG indicators, this one evolves with each bar of price action, scoring and filtering gaps based on real market behavior.
🔧 CORE FEATURES
✨ Smart Gap Detection
Automatically identifies bullish and bearish Fair Value Gaps using volatility-aware candle logic.
📊 Probability-Based Filtering
Uses logistic regression to assign each gap a confidence score (0 to 1), showing only high-probability setups.
🔁 Real-Time Retest Tracking
Continuously watches how price interacts with each gap to determine if it deserves respect.
📈 Multi-Factor Assessment
Evaluates RSI, MACD, and body size at gap formation to build a full context snapshot.
🧠 Self-Learning Engine
The logistic regression model updates on each bar using gradient descent, refining its predictions over time.
📢 Built-In Alerts
Get instant alerts when a gap forms, gets retested, or breaks.
🎨 Custom Display Options
Control the color of bullish/bearish zones, and toggle on/off probability labels for cleaner charts.
🚩 WHAT MAKES IT DIFFERENT
This isn’t just another box-drawing indicator.
While others mark every imbalance, this system thinks before it draws — using statistical modeling to filter out noise and prioritize high-impact zones.
By learning from how price behaves around gaps (not just how they form), it helps you trade only what matters — not what clutters.
⚙️ HOW IT WORKS
1️⃣ Detection
FVGs are identified using ATR-based thresholds and sharp wick imbalances.
2️⃣ Behavior Monitoring
Every gap is tracked — and if respected enough times, it becomes part of the elite training set.
3️⃣ Context Capture
Each new FVG logs RSI, MACD, and body size to provide a feature-rich context for prediction.
4️⃣ Prediction (Logistic Regression)
The model predicts how likely the gap is to be respected and assigns it a probability score.
5️⃣ Classification & Alerts
Gaps above the threshold are plotted with score labels, and alerts trigger for entry/respect/break.
⚙️ CONFIGURATION PANEL
🔧 System Inputs
• Max Retests – How many times a gap must be respected to train the model
• Prediction Threshold – Minimum score to show a gap on the chart
• Learning Rate – Controls how fast the model adapts (default: 0.009)
• Max FVG Lifetime – Expiration duration for unused gaps
• Show Historic Gaps – Show/hide expired or invalidated gaps
🎨 Visual Options
• Bullish/Bearish Colors – Set gap colors to fit your chart style
• Confidence Labels – Show probability scores next to FVGs
• Alert Toggles – Enable alerts for:
– New FVG detected
– FVG respected (entry)
– FVG invalidated (break)
💡 WHY LOGISTIC REGRESSION?
Traditional FVG tools rely on candle shapes.
This system relies on probability — by training on RSI, MACD, and price behavior, it predicts whether a gap will act as a true liquidity zone.
Logistic regression lets the system continuously adapt using new data, making it more accurate the longer it runs.
That means smarter signals, fewer false positives, and a clearer view of where real opportunities lie.
Greer Book Value Yield📘 Script Title
Greer Book Value Yield – Valuation Insight Based on Balance Sheet Strength
🧾 Description
Greer Book Value Yield is a valuation-focused indicator in the Greer Financial Toolkit, designed to evaluate how much net asset value (book value) a company provides per share relative to its current market price. This script calculates the Book Value Per Share Yield (BV%) using the formula:
Book Value Yield (%) = Book Value Per Share ÷ Stock Price × 100
This yield helps investors assess whether a stock is trading at a discount or premium to its underlying assets. It dynamically highlights when the yield is:
🟢 Above its historical average (potentially undervalued)
🔴 Below its historical average (potentially overvalued)
🔍 Use Case
Analyze valuation through asset-based metrics
Identify buy opportunities when book value yield is historically high
Combine with other scripts in the Greer Financial Toolkit:
📘 Greer Value – Tracks year-over-year growth consistency across six key metrics
📊 Greer Value Yields Dashboard – Visualizes multiple valuation-based yields
🟢 Greer BuyZone – Highlights long-term technical buy zones
🛠️ Inputs & Data
Uses Book Value Per Share (BVPS) from TradingView’s financial database (Fiscal Year)
Calculates and compares against a static average yield to assess historical valuation
Clean visual feedback via dynamic coloring and overlays
⚠️ Disclaimer
This tool is for educational and informational purposes only and should not be considered financial advice. Always conduct your own research before making investment decisions.
Greer EPS Yield📘 Script Title
Greer EPS Yield – Valuation Insight Based on Earnings Productivity
🧾 Description
Greer EPS Yield is a valuation-focused indicator from the Greer Financial Toolkit, designed to evaluate how efficiently a company generates earnings relative to its current stock price. This script calculates the Earnings Per Share Yield (EPS%), using the formula:
EPS Yield (%) = Earnings Per Share ÷ Stock Price × 100
This yield metric provides a quick snapshot of valuation through the lens of profitability per share. It dynamically highlights when the EPS yield is:
🟢 Above its historical average (potentially undervalued)
🔴 Below its historical average (potentially overvalued)
🔍 Use Case
Quickly assess valuation attractiveness based on earnings yield.
Identify potential buy opportunities when EPS% is above its long-term average.
Combine with other indicators in the Greer Financial Toolkit for a fundamentals-driven investment strategy:
📘 Greer Value – Tracks year-over-year growth consistency across six key metrics
📊 Greer Value Yields Dashboard – Visualizes valuation-based yield metrics
🟢 Greer BuyZone – Highlights long-term technical buy zones
🛠️ Inputs & Data
Uses fiscal year EPS data from TradingView’s built-in financial database.
Tracks a static average EPS Yield to compare current valuation to historical norms.
Clean, intuitive visual with automatic color coding.
⚠️ Disclaimer
This tool is for educational and informational purposes only and should not be considered financial advice. Always conduct your own research before making investment decisions.
ArraysAssorted🟩 OVERVIEW
This library provides utility methods for working with arrays in Pine Script. The first method finds extreme values (highest/lowest) within a rolling lookback window and returns both the value and its position. I might extend the library for other ad-hoc methods I use to work with arrays.
🟩 HOW TO USE
Pine Script libraries contain reusable code for importing into indicators. You do not need to copy any code out of here. Just import the library and call the method you want.
For example, for version 1 of this library, import it like this:
import SimpleCryptoLife/ArraysAssorted/1
See the EXAMPLE USAGE sections within the library for examples of calling the methods.
You do not need permission to use Pine libraries in your open-source scripts.
However, you do need explicit permission to reuse code from a Pine Script library’s functions in a public protected or invite-only publication .
In any case, credit the author in your description. It is also good form to credit in open-source comments.
For more information on libraries and incorporating them into your scripts, see the Libraries section of the Pine Script User Manual.
🟩 METHOD 1: m_getHighestLowestFloat()
Finds the highest or lowest float value from an array. Simple enough. It also returns the index of the value as an offset from the end of the array.
• It works with rolling lookback windows, so you can find extremes within the last N elements
• It includes an offset parameter to skip recent elements if needed
• It handles edge cases like empty arrays and invalid ranges gracefully
• It can find either the first or last occurrence of the extreme value
We also export two enums whose sole purpose is to look pretty as method arguments.
method m_getHighestLowestFloat(_self, _highestLowest, _lookbackBars, _offset, _firstLastType)
Namespace types: array
This method finds the highest or lowest value in a float array within a rolling lookback window, and returns the value along with the offset (number of elements back from the end of the array) of its first or last occurrence.
Parameters:
_self (array) : The array of float values to search for extremes.
_highestLowest (HighestLowest) : Whether to search for the highest or lowest value. Use the enum value HighestLowest.highest or HighestLowest.lowest.
_lookbackBars (int) : The number of array elements to include in the rolling lookback window. Must be positive. Note: Array elements only correspond to bars if the consuming script always adds exactly one element on consecutive bars.
_offset (int) : The number of array elements back from the end of the array to start the lookback window. A value of zero means no offset. The _offset parameter offsets both the beginning and end of the range.
_firstLastType (FirstLast) : Whether to return the offset of the first (lowest index) or last (highest index) occurrence of the extreme value. Use FirstLast.first or FirstLast.last.
Returns: (tuple) A tuple containing the highest or lowest value and its offset -- the number of elements back from the end of the array. If not found, returns . NOTE: The _offsetFromEndOfArray value is not affected by the _offset parameter. In other words, it is not the offset from the end of the range but from the end of the array. This number may or may not have any relation to the number of *bars* back, depending on how the array is populated. The calling code needs to figure that out.
EXPORTED ENUMS
HighestLowest
Whether to return the highest value or lowest value in the range.
• highest : Find the highest value in the specified range
• lowest : Find the lowest value in the specified range
FirstLast
Whether to return the first (lowest index) or last (highest index) occurrence of the extreme value.
• first : Return the offset of the first occurrence of the extreme value
• last : Return the offset of the last occurrence of the extreme value