ETI IndicatorThe Ensemble Technical Indicator (ETI) is a script that combines multiple established indicators into one single powerful indicator. Specifically, it takes a number of technical indicators and then converts them into +1 to represent a bullish trend, or a -1 to represent a bearish trend. It then adds these values together and takes the running sum over the past 20 days.
The ETI is composed of the following indicators and converted to +1 or -1 using the following criteria:
Simple Moving Average (10 days) : When the price is above the 10-day simple moving averaging, +1, when below -1
Weighted Moving Average (10 days) : Similar to the SMA 10, when the the price is above the 10-day weighted moving average, +1, when below -1
Stochastic K% : If the current Stochastic K% is greater than the previous value, then +1, else -1.
Stochastic D% : Similar to the Stochastic K%, when the current Stochastic D% is greater than the previous value, +1, else -1.
MACD Difference : First subtract the MACD signal (i.e. the moving average) from the MACD value and if the current value is higher than the previous value, then +1, else -1.
William's R% : If the current William's R% is greater than the previous one, then +1, else -1.
William's Accumulation/Distribution : If the current William's AD value is greater than the previous value, then +1, else -1.
Commodity Channel Index : If the Commodity Channel Index is greater than 200 (overbought), then -1, if it is less than -200 (oversold) then +1. When it is between those values, if the current value is greater than the previous value then +1, else -1.
Relative Strength Index : If the Relative Strength Index is over 70 (overbought) then -1 and if under 30 (oversold) then +1. If the Relative Strength Indicator is between those values then if the current value is higher than the previous value +1, else -1.
Momentum (9 days) : If the momentum value is greater than 0, then +1, else -1.
Again, once these values have been calculated and converted, they are added up to produce a single value. This single value is then summed across the previous 20 candles to produce a running sum.
By coalescing multiple technical indicators into a single value across time, traders can better understand how multiple inter-related indicators are behaving at once; high scores indicate that numerous indicators are showing bullish signals indicating a potential or ongoing uptrend (and vice-versa with low scores).
Additional Features
Numerous smoothing transformations have also been added (e.g. gaussian smoothing) to remove some of the noise might exist.
Suggested Use
It is recommended that stocks are shorted when the cross below 0, and are bought when the ETI crosses above -40. Arrows can be shown on the indicator to show these points. However feel free to use levels that work best for you.
Traditionally, I have treated values above +50 as overbought and below -40 as undersold (with -80 indicating extremely oversold); however these levels could also indicate either upwards and downwards momentum so taking a position based on where the ETI is (rather than crossing levels) should be done with caution.
Statistics
Relative Strength Index with Percentile📈 Relative Strength Index with Percentile Rank (RSI + Percentile)
This advanced RSI indicator adds a powerful percentile ranking system to the classic Relative Strength Index, providing deeper insight into current RSI values relative to recent history.
🔍 Key Features:
Standard RSI Calculation: Identifies overbought/oversold levels using a customizable period.
RSI Percentile (0–100%): Calculates where the current RSI value stands within a user-defined lookback period.
Dynamic Background Coloring:
🟩 Green when RSI percentile is above 80% (strong relative strength)
🟥 Red when RSI percentile is below 20% (strong relative weakness)
Optional Divergence Detection: Spot classic bullish and bearish divergences between price and RSI.
Smoothing Options: Apply various moving averages (SMA, EMA, RMA, etc.) to the RSI, with optional Bollinger Bands.
Flexible Settings: Full control over lookback periods, smoothing type, and band sensitivity.
🧠 Why Use RSI Percentile?
Traditional RSI values can become less informative during trending markets. By ranking the RSI as a percentile, you gain contextual insight into whether the current strength is unusually high or low compared to recent history, rather than just a fixed 70/30 threshold.
Money Flow based probabilityMoney Flow based probability
This indicator provides a comprehensive correlation and momentum analysis between your main asset and up to three selected correlated assets. It combines correlation, trend, momentum, and overbought/oversold signals into a single, easy-to-read table directly on your chart.
Correlated Asset Selection :
You can select up to three correlated assets (e.g., indices, currencies, bonds) to compare with your main chart symbol. Each asset can be toggled on or off.
Correlation Calculation :
The indicator uses the native Pine Script ta.correlation function to measure the statistical relationship between the closing prices of your asset and each selected pair over a user-defined period.
Technical Analysis Integration :
For each asset (including the main one), the indicator calculates:
Trend direction using EMA (Exponential Moving Average) – optional
Momentum using MACD – optional
Overbought/oversold status using RSI – optional
Probability Scoring :
A weighted scoring system combines correlation, trend, MACD, RSI, and trend exhaustion signals to produce buy and sell probabilities for the main asset.
Visual Table Output :
A customizable table is displayed on the chart, showing:
Asset name
Correlation (as a percentage, -100% to +100%)
Trend (Bullish/Bearish)
MACD status (Bullish/Bearish)
RSI value and status
Buy/Sell probability (with fixed-width formatting for stability)
User Customization :
You can adjust:
Table size, color, and position
Correlation period
EMA, MACD, and RSI parameters
Which assets to display
This indicator is ideal for traders who want to quickly assess the influence of major correlated markets and technical signals on their trading instrument, all in a single glance.
---
Example: Correlation Calculation
corrCurrentAsset1 = ta.correlation(close, asset1Data, correlationPeriod)
Example: Table Output (Buy/Sell %)
buyStr = f_formatPercent(buyProbability) + "%"
sellStr = f_formatPercent(sellProbability) + "%"
cellStr = buyStr + " / " + sellStr
The Echo System🔊 The Echo System – Trend + Momentum Trading Strategy
Overview:
The Echo System is a trend-following and momentum-based trading tool designed to identify high-probability buy and sell signals through a combination of market trend analysis, price movement strength, and candlestick validation.
Key Features:
📈 Trend Detection:
Uses a 30 EMA vs. 200 EMA crossover to confirm bullish or bearish trends.
Visual trend strength meter powered by percentile ranking of EMA distance.
🔄 Momentum Check:
Detects significant price moves over the past 6 bars, enhanced by ATR-based scaling to filter weak signals.
🕯️ Candle Confirmation:
Validates recent price action using the previous and current candle body direction.
✅ Smart Conditions Table:
A live dashboard showing all trade condition checks (Trend, Recent Price Move, Candlestick confirmations) in real-time with visual feedback.
📊 Backtesting & Stats:
Auto-calculates average win, average loss, risk-reward ratio (RRR), and win rate across historical signals.
Clean performance dashboard with color-coded metrics for easy reading.
🔔 Alerts:
Set alerts for trade signals or significant price movements to stay updated without monitoring the chart 24/7.
Visuals:
Trend markers and price movement flags plotted directly on the chart.
Dual tables:
📈 Conditions table (top-right): breaks down trade criteria status.
📊 Performance table (bottom-right): shows real-time stats on win/loss and RRR.🔊 The Echo System – Trend + Momentum Trading Strategy
Overview:
The Echo System is a trend-following and momentum-based trading tool designed to identify high-probability buy and sell signals through a combination of market trend analysis, price movement strength, and candlestick validation.
Key Features:
📈 Trend Detection:
Uses a 30 EMA vs. 200 EMA crossover to confirm bullish or bearish trends.
Visual trend strength meter powered by percentile ranking of EMA distance.
🔄 Momentum Check:
Detects significant price moves over the past 6 bars, enhanced by ATR-based scaling to filter weak signals.
🕯️ Candle Confirmation:
Validates recent price action using the previous and current candle body direction.
✅ Smart Conditions Table:
A live dashboard showing all trade condition checks (Trend, Recent Price Move, Candlestick confirmations) in real-time with visual feedback.
📊 Backtesting & Stats:
Auto-calculates average win, average loss, risk-reward ratio (RRR), and win rate across historical signals.
Clean performance dashboard with color-coded metrics for easy reading.
🔔 Alerts:
Set alerts for trade signals or significant price movements to stay updated without monitoring the chart 24/7.
Visuals:
Trend markers and price movement flags plotted directly on the chart.
Dual tables:
📈 Conditions table (top-right): breaks down trade criteria status.
📊 Performance table (bottom-right): shows real-time stats on win/loss and RRR.
Machine Learning: ARIMA + SARIMADescription
The ARIMA (Autoregressive Integrated Moving Average) and SARIMA (Seasonal ARIMA) are advanced statistical models that use machine learning to forecast future price movements. It uses autoregression to find the relationship between observed data and its lagged observations. The data is differenced to make it more predictable. The MA component creates a dependency between observations and residual errors. The parameters are automatically adjusted to market conditions.
Differences
ARIMA - This excels at identifying trends in the form of directions
SARIMA - Incorporates seasonality. It's better at capturing patterns previously seen
How To Use
1. Model: Determine if you want to use ARIMA (better for direction) or SARIMA (better for overall prediction). You can click on the 'Show Historic Prediction' to see the direction of the previous candles. Green = forecast ending up, red = forecast ending down
2. Metrics: The RMSE% and MAPE are 10 day moving averages of the first 10 predictions made at candle close. They're error metrics that compare the observed data with the predicted data. It is better to use them when they're below 8%. Higher timeframes will be higher, as these models are partly mean-reverting and higher TFs tend to trend more. Better to compare RMSE% and MAPE with similar timeframes. They naturally lag as data is being collected
3. Parameter selection: The simpler, the better. Both are used for ARIMA(1,1,1) and SARIMA(1,1,1)(1,1,1)5. Increasing may cause overfitting
4. Training period: Keep at 50. Because of limitations in pine, higher values do not make for more powerful forecasts. They will only criminally lag. So best to keep between 20 and 80
BTC vs ALT Lag Detector [MEXC Overlay]This indicator monitors the price movement of Bitcoin (BTC) and compares it in real time to a customizable list of major altcoins on the MEXC exchange.
It helps you identify lagging altcoins — tokens that are underperforming or overperforming BTC’s price action over a selected timeframe. These temporary deviations can offer profitable entry or rotation opportunities, especially for scalpers, day traders, and arbitrage-style strategies.
Key Features:
- Real-time deviation detection between BTC and altcoins
- Customizable comparison timeframe: 1m, 6m, 12m, 30m, 1h, 4h, or 1d
- Deviation threshold alert: Highlights coins that lag BTC by more than 0.5%, 1%, 2%, or 3%
- Compact stats table embedded in the price chart
- Fully adjustable layout: Table position (Top/Bottom/Center + Left/Right), Font size (Tiny, Small, Medium)
- Built-in alert system when deviation exceeds your chosen threshold
How to Use It:
Set your desired timeframe for comparison (e.g., 1 hour).
Select a deviation threshold (e.g., 1.0%).
The table will show:
Each altcoin’s % change
BTC’s % change
The delta (deviation) vs BTC
Red highlights indicate alts whose deviation exceeded the threshold.
When at least one alt lags beyond your threshold, the indicator can trigger an alert — helping you capitalize on potential catch-up trades.
Please provide any feedback on it.
Best SMA FinderThis script, Best SMA Finder, is a tool designed to identify the most robust simple moving average (SMA) length for a given chart, based on historical backtest performance. It evaluates hundreds of SMA values (from 10 to 1000) and selects the one that provides the best balance between profitability, consistency, and trade frequency.
What it does:
The script performs individual backtests for each SMA length using either "Long Only" or "Buy & Sell" logic, as selected by the user. For each tested SMA, it computes:
- Total number of trades
- Profit Factor (total profits / total losses)
- Win Rate
- A composite Robustness Score, which integrates Profit Factor, number of trades (log-scaled), and win rate.
Only SMA configurations that meet the user-defined minimum trade count are considered valid. Among all valid candidates, the script selects the SMA length with the highest robustness score and plots it on the chart.
How to use it:
- Choose the strategy type: "Long Only" or "Buy & Sell"
- Set the minimum trade count to filter out statistically irrelevant results
- Enable or disable the summary stats table (default: enabled)
The selected optimal SMA is plotted on the chart in blue. The optional table in the top-right corner shows the corresponding SMA length, trade count, Profit Factor, Win Rate, and Robustness Score for transparency.
Key Features:
- Exhaustive SMA optimization across 991 values
- Customizable trade direction and minimum trade filters
- In-chart visualization of results via table and plotted optimal SMA
- Uses a custom robustness formula to rank SMA lengths
Use cases:
Ideal for traders who want to backtest and auto-select a historically effective SMA without manual trial-and-error. Useful for swing and trend-following strategies across different timeframes.
📌 Limitations:
- Not a full trading strategy with position sizing or stop-loss logic
- Only one entry per direction at a time is allowed
- Designed for exploration and optimization, not as a ready-to-trade system
This script is open-source and built entirely from original code and logic. It does not replicate any closed-source script or reuse significant external open-source components.
Bitcoin Monthly Seasonality [Alpha Extract]The Bitcoin Monthly Seasonality indicator analyzes historical Bitcoin price performance across different months of the year, enabling traders to identify seasonal patterns and potential trading opportunities. This tool helps traders:
Visualize which months historically perform best and worst for Bitcoin.
Track average returns and win rates for each month of the year.
Identify seasonal patterns to enhance trading strategies.
Compare cumulative or individual monthly performance.
🔶 CALCULATION
The indicator processes historical Bitcoin price data to calculate monthly performance metrics
Monthly Return Calculation
Inputs:
Monthly open and close prices.
User-defined lookback period (1-15 years).
Return Types:
Percentage: (monthEndPrice / monthStartPrice - 1) × 100
Price: monthEndPrice - monthStartPrice
Statistical Measures
Monthly Averages: ◦ Average return for each month calculated from historical data.
Win Rate: ◦ Percentage of positive returns for each month.
Best/Worst Detection: ◦ Identifies months with highest and lowest average returns.
Cumulative Option
Standard View: Shows discrete monthly performance.
Cumulative View: Shows compounding effect of consecutive months.
Example Calculation (Pine Script):
monthReturn = returnType == "Percentage" ?
(monthEndPrice / monthStartPrice - 1) * 100 :
monthEndPrice - monthStartPrice
calcWinRate(arr) =>
winCount = 0
totalCount = array.size(arr)
if totalCount > 0
for i = 0 to totalCount - 1
if array.get(arr, i) > 0
winCount += 1
(winCount / totalCount) * 100
else
0.0
🔶 DETAILS
Visual Features
Monthly Performance Bars: ◦ Color-coded bars (teal for positive, red for negative returns). ◦ Special highlighting for best (yellow) and worst (fuchsia) months.
Optional Trend Line: ◦ Shows continuous performance across months.
Monthly Axis Labels: ◦ Clear month names for easy reference.
Statistics Table: ◦ Comprehensive view of monthly performance metrics. ◦ Color-coded rows based on performance.
Interpretation
Strong Positive Months: Historically bullish periods for Bitcoin.
Strong Negative Months: Historically bearish periods for Bitcoin.
Win Rate Analysis: Higher win rates indicate more consistently positive months.
Pattern Recognition: Identify recurring seasonal patterns across years.
Best/Worst Identification: Quickly spot the historically strongest and weakest months.
🔶 EXAMPLES
The indicator helps identify key seasonal patterns
Bullish Seasons: Visualize historically strong months where Bitcoin tends to perform well, allowing traders to align long positions with favorable seasonality.
Bearish Seasons: Identify historically weak months where Bitcoin tends to underperform, helping traders avoid unfavorable periods or consider short positions.
Seasonal Strategy Development: Create trading strategies that capitalize on recurring monthly patterns, such as entering positions in historically strong months and reducing exposure during weak months.
Year-to-Year Comparison: Assess how current year performance compares to historical seasonal patterns to identify anomalies or confirmation of trends.
🔶 SETTINGS
Customization Options
Lookback Period: Adjust the number of years (1-15) used for historical analysis.
Return Type: Choose between percentage returns or absolute price changes.
Cumulative Option: Toggle between discrete monthly performance or cumulative effect.
Visual Style Options: Bar Display: Enable/disable and customize colors for positive/negative bars, Line Display: Enable/disable and customize colors for trend line, Axes Display: Show/hide reference axes.
Visual Enhancement: Best/Worst Month Highlighting: Toggle special highlighting of extreme months, Custom highlight colors for best and worst performing months.
The Bitcoin Monthly Seasonality indicator provides traders with valuable insights into Bitcoin's historical performance patterns throughout the year, helping to identify potentially favorable and unfavorable trading periods based on seasonal tendencies.
DEMA HMA Z-score OscillatorThis custom oscillator combines the power of the Hull Moving Average (HMA) with the Z-Score to identify momentum shifts and potential trend reversals. The Z-Score measures how far the current HMA is from its historical mean, helping to spot overbought or oversold conditions.
Uptrend: Long signals are generated when the Z-Score crosses above the defined Long Threshold.
Downtrend: Short signals are triggered when the Z-Score drops below the Short Threshold.
Visuals: The Z-Score is plotted along with background color changes and fills to clearly indicate trend strength. Green fills highlight uptrends, while pink fills indicate downtrends.
Alerts: Alerts are available for both long and short conditions based on Z-Score crossovers.
Customizable Inputs:
HMA Length
Smoothing Length (for DEMA)
Z-Score Length
Long and Short Thresholds
This indicator is ideal for detecting momentum shifts, confirming trend strength, and helping to time entry/exit points in your trading strategy.
Ticker DataThis script mostly for Pine coders but may be useful for regular users too.
I often find myself needing quick access to certain information about a ticker — like its full ticker name, mintick, last bar index and so on. Usually, I write a few lines of code just to display this info and check it.
Today I got tired of doing that manually, so I created a small script that shows the most essential data in one place. I also added a few extra fields that might be useful or interesting to regular users.
Description for regular users (from Pine Script Reference Manual)
tickerid - full ticker name
description - description for the current symbol
industry - the industry of the symbol. Example: "Internet Software/Services", "Packaged software", "Integrated Oil", "Motor Vehicles", etc.
country - the two-letter code of the country where the symbol is traded
sector - the sector of the symbol. Example: "Electronic Technology", "Technology services", "Energy Minerals", "Consumer Durables", etc.
session - session type (regular or extended)
timezone - timezone of the exchange of the chart
type - the type of market the symbol belongs to. Example: "stock", "fund", "index", "forex", "futures", "spread", "economic", "fundamental", "crypto".
volumetype - volume type of the current symbol.
mincontract - the smallest amount of the current symbol that can be traded
mintick - min tick value for the current symbol (the smallest increment between a symbol's price movements)
pointvalue - point value for the current symbol
pricescale - a whole number used to calculate mintick (usually (when minmove is 1), it shows the resolution — how many decimal places the price has. For example, a pricescale 100 means the price will have two decimal places - 1 / 100 = 0.01)
bar index - last bar index (if add 1 (because indexes starts from 0) it will shows how many bars available to you on the chart)
If you need some more information at table feel free to leave a comment.
Central Bank Assets YoY % with StdDev BandsCentral Bank Assets YoY % with StdDev Bands - Indicator Documentation
Overview
This indicator tracks the year-over-year (YoY) percentage change in combined central bank assets using a custom formula. It displays the annual growth rate along with statistical bands showing when the growth is significantly above or below historical norms.
Formula Components
The indicator is based on a custom symbol combining multiple central bank balance sheets:
Federal Reserve balance sheet (FRED)
Bank of Japan assets converted to USD (FX_IDC*FRED)
European Central Bank assets converted to USD (FX_IDC*FRED)
Subtracting Fed reverse repo operations (FRED)
Subtracting Treasury General Account (FRED)
Calculations
Year-over-Year Percentage Change: Calculates the percentage change between the current value and the value from exactly one year ago (252 trading days).
Formula: ((current - year_ago) / year_ago) * 100
Statistical Measures:
Mean (Average): The 252-day simple moving average of the YoY percentage changes
Standard Deviation: The 252-day standard deviation of YoY percentage changes
Display Components
The indicator displays:
Main Line: YoY percentage change (green when positive, red when negative)
Zero Line: Reference line at 0% (gray dashed)
Mean Line: Average YoY change over the past 252 days (blue)
Standard Deviation Bands: Shows +/- 1 standard deviation from the mean
Upper band (+1 StdDev): Green, line with breaks style
Lower band (-1 StdDev): Red, line with breaks style
Interpretation
Values above zero indicate YoY growth in central bank assets
Values below zero indicate YoY contraction
Values above the +1 StdDev line indicate unusually strong growth
Values below the -1 StdDev line indicate unusually severe contraction
Crossing above/below the mean line can signal shifts in central bank policy trends
Usage
This indicator is useful for:
Monitoring global central bank liquidity trends
Identifying unusual periods of balance sheet expansion/contraction
Analyzing correlations between central bank activity and market performance
Anticipating potential market impacts from changes in central bank policy
The 252-day lookback period (approximately one trading year) provides a balance between statistical stability and responsiveness to changing trends in central bank behavior.
Z-Score Trend Monitor [EdgeTerminal]The Z-Score Trend Monitor measures how far the short-term moving average deviates from the long-term moving average using the spread difference of the two — in standardized units. It’s designed to detect overextension, momentum exhaustion, and potential mean-reversion points by converting the spread between two moving averages into a normalized Z-score and tracking its change and direction over time.
The idea behind this is to catch the changes in the direction of a trend earlier than the usual and lagging moving average lines, allowing you to react faster.
The math behind the indicator itself is very simple. We take the simple moving average of the spread between a long term and short term moving average, and divide it by the difference between the spread and spread mean.
This results in a relatively accurate and early acting trend detector that can easily identify overbought and oversold levels in any timeframe. From our own testing, we recommend using this indicator as a trend confirmation tool.
How to Use It:
Keep an eye on the Z-Score or the blue line. When it goes over 2, it indicates an overbought or near top level, and when it goes below -2, it indicates an oversold or near bottom.
When Z-Score returns to zero or grey line, it suggests mean reversion is in progress.
You can also change the Z-Score criteria from 2 and -2 in the settings to any number you’d like for tighter or wider levels.
For scalping and fast trading setups, we recommend shorter SMAs, such as 5 and 20, and for longer trading setups such as swing trades, we recommend 20 and 100.
Settings:
Short SMA: Lookback period of short term simple moving average for the lower side of the SMA spread.
Short Term Weight: Additional weight or multiplier to suppress the short term SMA calculation. This is used to refine the SMA calculation for more granular and edge cases when needed, usually left at 1, meaning it will take the entire given value in the short SMA field.
Long SMA: Lookback period of long term simple moving average for the upper side of the SMA spread.
Long Term Weight: Additional weight or multiplier to suppress the long term SMA calculation. This is used to refine the long SMA calculation for more granular and edge cases when needed, usually left at 1, meaning it will take the entire given value in the long SMA field.
Z-Score Threshold: The threshold for upper (oversold) and lower (overbought) levels. This can also be set individually from the style page.
Z-Score Lookback Window: The lookback period to calculate spread mean and spread standard deviation
True Strength Index (TSI)%📌 Script Name: TSI Percentuale
This script is a custom True Strength Index (TSI) indicator that expresses momentum strength as a percentage from 0% to 100%, instead of the traditional TSI scale.
✅ What the Script Does
Calculates the standard TSI:
Uses double exponential smoothing of price changes and their absolute values.
Formula:
TSI_raw
=
100
×
DoubleSmoothed(ΔPrice)
DoubleSmoothed(|ΔPrice|)
TSI_raw=100×
DoubleSmoothed(|ΔPrice|)
DoubleSmoothed(ΔPrice)
Normalizes TSI to a percentile scale:
Over a user-defined lookback period, the script finds the lowest and highest TSI values.
It then rescales the current TSI to a value between 0% (minimum) and 100% (maximum).
50% represents neutral momentum (i.e., "flat").
Plots the result:
tsi_percent is plotted as a blue line.
Horizontal dashed/dotted lines are drawn at:
0% → strong downward momentum
50% → neutral
100% → strong upward momentum
⚙️ Inputs
Long Length: Long EMA smoothing period (default: 25)
Short Length: Short EMA smoothing period (default: 13)
Signal Length: (not used in this version, can be removed or extended)
Lookback Period: Number of bars to calculate min/max normalization (default: 100)
🧠 Why Use This Indicator
The classic TSI ranges around and can be hard to interpret.
This version makes TSI visually intuitive by converting it to percentile form, allowing easier comparison of momentum strength across time and instruments.
It’s particularly useful for defining zones like:
Above 70% = strong bullish
Below 30% = strong bearish
Daily ATR Bonanza: Expected Moves - Tr33man Daily ATR Bonanza: Expected Moves
Overview 🤷♂️
The Daily ATR Bonanza script is a powerful trading tool designed to help traders visualize and understand potential price movements using the Average True Range (ATR). It provides daily and weekly ATR levels, historical statistics, and conditional probability analysis to give traders actionable insights. The script also plots the daily Keltner channel. This script is ideal for traders who want to gauge volatility, identify key levels, and make data-driven decisions.
b]Key Features:
📈 1. Daily and Weekly ATR Levels
🔵ATR Levels: The script calculates and displays ATR-based levels for the day and week. These levels are derived from the previous day's or week's close price and are adjusted using customizable multipliers (0.5x, 1x, and 1.5x by default).
🔵You can choose the number of ATR levels (1, 2, or 3) and adjust the multipliers to suit your trading strategy.
🌐 2. ATR Bands (Keltner Channels)
🔵The script includes an option to display ATR Bands, which are volatility-based envelopes around a moving average. These bands help identify overbought and oversold conditions.
🔵You can adjust the ATR multiplier and the length of the moving average used for the bands.
🧮 3. Historical Statistics and Conditional Probability
🔵 Historical Analysis: The script analyzes historical price movements to calculate the likelihood of closing at certain ATR levels.
🔵 Conditional Probability: This feature shows the probability of the price reaching specific ATR levels given the current market conditions. The conditional matches historical data by an open in the same opening ATR bucket, as well as the current price bucket having been visited in the historical case. Conditional probabilities are just statistics, and do not predict anything.
Data Table: 📚
🔵 Historical Close Probability: The percentage of days the price closed within each ATR level.
🔵 Conditional Close Probability: The likelihood of the price closing within each ATR level today.
❓ What is Conditional Probability? ❓
Conditional probability is a statistical measure that calculates the likelihood of an event occurring given that another event has already occurred. In this script, it is used to determine the probability of the price reaching specific ATR levels based on the current opening range as well as current ATR distance from the previous close.
For example:
If the market opens near the lower end of the first ATR level, the script calculates the likelihood of the price reaching the upper end of the first, second, or third ATR level.
This analysis is based on historical data, making it a powerful tool for understanding potential price movements.
🌟 Understanding the Levels
🔵Daily Levels: These are based on the previous day's close price and ATR. They are updated at the start of each new day.
🔵Weekly Levels: These are based on the previous week's close price and ATR. They are updated at the start of each new week.
🔵ATR Bands: These are dynamic levels that adjust with market volatility.
🔬 Analyze the Statistics (Daily only for now, no weekly yet)
🔵Use the interactive table to understand historical probabilities and conditional probabilities.
🔵Focus on the current opening range and the likelihood of reaching specific levels.
🧠 Make Trading Decisions
🔵Use the ATR levels and bands to identify key support and resistance levels.
🔵Use the conditional probability table to gauge the likelihood of reaching specific targets.
🔵Adjust your strategy based on the historical performance of the market.
Example Use Cases
1. Day Trading
Use the daily ATR levels to set intraday targets and stop-loss levels.
Monitor the conditional probability table to adjust your expectations based on the opening range.
2. Swing Trading
Use the weekly ATR levels to identify longer-term support and resistance levels.
3. Scalping
Use the ATR bands to identify overbought and oversold conditions.
Use the conditional probability table to quickly assess the likelihood of price movements.
ETF Builder & Backtest System [TradeDots]Create, analyze, and monitor your own custom “ETF-like” portfolio directly on TradingView. This script merges up to 10 different assets with user-defined weightings into a single composite chart, allowing you to see how your personalized portfolio would have performed historically. It is an original tool designed to help traders and investors quickly gauge risk and return profiles without leaving the TradingView platform.
📝 HOW IT WORKS
1. Custom Portfolio Construction
Multiple Assets : Combine up to 10 different stocks, ETFs, cryptocurrencies, or other symbols.
User-Defined Weights : Allocate each asset a percentage weight (e.g., 15% in AAPL, 10% in MSFT, etc.).
Single Composite Value : The script calculates a weighted “ETF-style” price, effectively simulating a merged portfolio curve on your chart.
2. Performance Tracking & Return Analysis
Automatic History Capture : The indicator records each asset’s starting price when it first appears in your chosen date range.
Rolling Updates : As time progresses, all asset prices are continually evaluated and the portfolio value is updated in real time.
Buy & Hold Returns : See how each asset—and the overall portfolio—performed from the “start” date to the most recent bar.
Annualized Return : Automatically calculates CAGR (Compound Annual Growth Rate) to help visualize performance over varying timescales.
3. Table & Visual Output
Performance Table : A comprehensive table displays individual asset returns, annualized returns, and portfolio totals.
Normalized Chart Plot : The composite ETF value is scaled to 100 at the start date, making it easy to compare relative growth or decline.
Optional Time Filter : You can define a specific date range (Start/End Dates) to focus on a particular period or to limit historical data.
⚙️ KEY FEATURES
1. Flexible Asset Selection
Choose any symbols from multiple asset classes. The script will only run calculations when data is available—no need to worry about missing quotes.
2. Dynamic Table Reporting
Start Price for each asset
Percentage Weight in the portfolio
Total Return (%) and Annualized Return (%)
3. Simple Backtesting Logic
This script takes a straightforward Buy & Hold perspective. Once the start date is reached, the portfolio remains static until the end date, so you can quickly assess hypothetical growth.
4. Plot Customization
Toggle the main “ETF” plot on/off.
Alter the visual style for tables and text.
Adjust the time filter to limit or extend your performance measurement window.
🚀 HOW TO USE IT
1. Add the Script
Search for “ETF Builder & Backtest System ” in the Indicators & Strategies tab or manually add it to your chart after saving it in your Pine Editor.
2. Configure Inputs
Enable Time Filter : Choose whether to restrict the analysis to a particular date range.
Start & End Date : Define the period you want to measure performance over (e.g., from 2019-12-31 to 2025-01-01).
Assets & Weights : Enter each symbol and specify a percentage weight (up to 10 assets).
Display Options : Pick where you want the Table to appear and choose background/text colors.
3. Interpret the Table & Plots
Asset Rows : Each asset’s ticker, weighting, start price, and performance metrics.
ETF Total Row : Summarizes total weighting, composite starting value, and overall returns.
Normalized Plot : Tracks growth/decline of the combined portfolio, starting at 100 on the chart.
4. Refine Your Strategy
Compare how different weights or a new mix of assets would have performed over the same period.
Assess if certain assets contribute disproportionately to your returns or volatility.
Use the results to guide allocations in your real trading or paper trading accounts.
❗️LIMITATIONS
1. Buy & Hold Only
This script does not handle rebalancing or partial divestments. Once the portfolio starts, weights remain fixed throughout the chosen timeframe.
2. No Reinvestment Tracking
Dividends or other distributions are not factored into performance.
3. Data Availability
If historical data for a particular asset is unavailable on TradingView, related results may display as “N/A.”
4. Market Regimes & Volatility
Past performance does not guarantee similar future behavior. Markets can change rapidly, which may render historical backtests less predictive over time.
⚠️ RISK DISCLAIMER
Trading and investing carry significant risk and can result in financial loss. The “ETF Builder & Backtest System ” is provided for informational and educational purposes only. It does not constitute financial advice.
Always conduct your own research.
Use proper risk management and position sizing.
Past performance does not guarantee future results.
This script is an original creation by TradeDots, published under the Mozilla Public License 2.0.
Use this indicator as part of a broader trading or investment approach—consider fundamental and technical factors, overall market context, and personal risk tolerance. No trading tool can assure profits; exercise caution and responsibility in all financial decisions.
ICT Macro H1"H1 Candle Time Box" is a custom TradingView indicator that highlights a configurable time window surrounding the close of each 1-hour (H1) candle. The indicator draws a transparent box 15 minutes before and after each H1 candle close (by default), helping traders visualize time-based reaction zones.
🔍 Features:
Custom time window: Users can set how many minutes before and after the H1 close the box should appear.
Dynamic positioning: Boxes are drawn slightly above the candles to avoid overlap with price bars.
Live time labels: Each box displays its time range (e.g., "08:45 - 09:15") based on the start and end time of the zone.
Auto-cleaning: Only a limited number of recent boxes (default: 5) are shown, keeping the chart clean.
Requires 1-minute chart for precise timing.
This tool is especially helpful for intraday traders to identify areas of interest or market reactions before and after key hourly closes.
Golden Setup V1Golden Setup V1 is an overlay indicator that automates Tony Rago’s “Golden Setup” price-level framework. It divides the chart into fixed “blockSize” intervals (default 100 points) and plots a series of key horizontal levels within each block—levels at 00, 12, 26, 33, 50, 62, 77 and 88 offsets. These levels act as dynamic support and resistance grids that roll up or down as price moves between blocks.
Key Features
Customizable Offsets
Define eight offset levels corresponding to Rago’s Golden Setup:
00 (Round Number)
12 (Target 12)
26 (First “Golden” level)
33 (Target 33)
50 (Mid-block pivot)
62 (Target 62)
77 (Second “Golden” level)
88 (Target 88)
Multi-Block Coverage
Choose how many blocks above and below the current 100-point block you wish to display, so you always have levels drawn for the surrounding price range.
Golden-Only Filter
A handy toggle lets you show only the two “Golden” offsets (26 & 77), which many traders prioritize for high-probability bounce or breakout areas.
Dynamic Nearest-Level Label
Highlights the closest Golden Setup level (to the right edge of the chart) with a movable label, so you always know which level price is approaching.
Full Styling Control
Customize line colors, widths, block size, label fonts and opacity to suit your charting style.
How It Works
Block Calculation
On each bar, the indicator computes the “current block” by flooring (close / blockSize) and multiplying back by blockSize.
Level Offsets
It adds each of the eight user-defined offsets to that block base (and, if price has moved below the lowest offset, shifts the block down one interval).
Drawing
Each level is drawn as a horizontal line extending across the chart for as many blocks above/below as you select.
Nearest-Level Detection
Within the present block, it calculates which of the plotted levels is closest to price and displays that value on the right edge.
Usage Tips
Use the Golden-Only filter to declutter and focus solely on the 26 & 77 levels, which often act as strong intra-block pivot points.
Combine with volume or momentum indicators to confirm bounces at these levels.
Adjust blockSize (e.g. 50 or 200) if you wish to work in smaller or larger price increments.
⚠️ Disclaimer: This script is for educational and illustrative purposes only. Trading involves risk—always back-test and validate any strategy on a demo account before going live.
Median Price RSI DeviationThis indicator is a smoothed RSI-based trend filter that combines median price smoothing, customizable moving averages, and standard deviation bands to identify bullish or bearish conditions:
=> It first smooths price using a median filter.
=> Then it calculates RSI on that smoothed price.
=> The RSI is further smoothed using a selectable moving average (e.g., DEMA, EMA).
=> Standard deviation bands are applied around this smoothed RSI.
Signals:
=> A bullish signal is triggered when the upper band exceeds a long threshold (default 50).
=> A bearish signal occurs when the smoothed RSI drops below a short threshold (default 40).
Hippo Battlefield - Bulls VS Bears 20 bars## Hippo Battlefield – Bulls VS Bears (20 Bars)
**What it is**
A multi-dimensional momentum-and-sentiment oscillator that combines classic Bull/Bear Power with ATR- or peak-normalization, then layers on RSI and MACD-derived metrics into:
1. **A colored bar series** showing net Bull+Bear Power strength over the last 20 bars,
2. **A dynamic table** of each of those 20 BBP values (grouped into four 5-bar “quartals”), with symbols, per-bar change, and rolling averages, and
3. **A composite “Weighted BBP” histogram** blending normalized RSI, MACD, and BBP into a single view.
---
### Key Inputs
- **Length (EMA)** – look-back for the underlying EMA (default 60)
- **Normalization Length** – look-back window for peak-normalization (default 60)
- **Use ATR for Norm.** – toggle ATR-based normalization vs. highest-abs(BBP)
- **Show Tables** – toggle the bottom-right 21×11 grid of raw and average BBP values
---
### What You See
#### 1. Colored Bars (Overlay = false)
- Bars are colored by normalized BBP intensity:
- Extreme Bull (≥+10): deep blue
- Strong Bull (+5 to +10): green/yellow
- Weak Bull (+0 to +5): dark green
- Weak Bear (–0 to –5): dark red
- Strong Bear (–5 to –10): pink/red
- Extreme Bear (<–10): magenta
#### 2. Bottom-Right Table (20 Bars of Data)
- Divided into four columns (0–4, 5–9, 10–14, 15–19 bars ago) and one “average” row.
- Each cell shows:
1. Bar index (1–20),
2. Normalized BBP value (to four decimals),
3. Direction symbol (↑/↓/=),
4. Bar-to-bar change (± value),
5. A separator “|”.
- At the very bottom, each column’s 5-bar average is displayed as “Avg: X.XXXX” with a dot marker.
#### 3. Top-Center Mini-Table
- When ≥20 bars have elapsed, shows the date at 20 bars ago and the average BBP across the full 20-bar window.
#### 4. Normalized RSI Line
- Rescales the classic 14-period RSI into a –20…+20 band to align with BBP.
#### 5. MACD Lines (Hidden) & Composite Histogram
- MACD and signal lines are calculated but not plotted by default.
- A “Weighted BBP” histogram combines:
- 20% normalized RSI,
- 20% average of (MACD + signal + normalized BBP),
- 60% normalized BBP
- Plotted as columns, color-coded by strength using the same palette as the main bars.
#### 6. Middle Reference Line
- A horizontal zero line to anchor over/under-zero readings.
---
### How to Use It
- **Trend confirmation**: Strong blue/green bars alongside a rising histogram suggest bull conviction; strong reds/magentas signal bear dominance.
- **Divergence spotting**: Watch for price making new highs/lows while BBP or the histogram fails to follow.
- **Quartal analysis**: The 5-bar group averages can reveal whether recent momentum is accelerating or waning.
- **Cross-indicator weighting**: Because RSI, MACD, and raw BBP all feed into the final histogram, you get a smoothed, blended view of momentum shifts.
---
**Tip:** Tweak the EMA and normalization length to suit your preferred timeframe (e.g. shorter for intraday scalps, longer for swing trades). Enable/disable the table if you prefer a cleaner pane.
Altseason Index | AlchimistOfCrypto
🌈 Altseason Index | AlchimistOfCrypto – Revealing Bitcoin-Altcoin Dominance Cycles 🌈
"The Altseason Index, engineered through advanced mathematical methodology, visualizes the probabilistic distribution of capital flows between Bitcoin and altcoins within a multi-cycle paradigm. This indicator employs statistical normalization principles where ratio coefficients create mathematical boundaries that define dominance transitions between cryptographic asset classes. Our implementation features algorithmically enhanced rainbow visualization derived from extensive market cycle analysis, creating a dynamic representation of value flow with adaptive color gradients that highlight critical phase transitions in the cyclical evolution of the crypto market."
📊 Professional Trading Application
The Altseason Index transcends traditional sentiment models with a sophisticated multi-band illumination system that reveals the underlying structure of crypto sector rotation. Scientifically calibrated across different ratios (TOTAL2/BTC, OTHERS/BTC) and featuring seamless daily visualization, it enables investors to perceive capital transitions between Bitcoin and altcoins with unprecedented clarity.
- Visual Theming 🎨
Scientifically designed rainbow gradient optimized for market cycle recognition:
- Green-Blue: Altcoin accumulation zones with highest capital flow potential
- Neutral White: Market equilibrium zone representing balanced capital distribution
- Yellow-Red: Bitcoin dominance regions indicating defensive capital positioning
- Gradient Transitions: Mathematical inflection points for strategic reallocation
- Market Phase Detection 🔍
- Precise zone boundaries demarcating critical sentiment shifts in the crypto ecosystem
- Daily timeframe calculation ensuring consistent signal reliability
- Multiple ratio analysis revealing the probabilistic nature of market capital flows
🚀 How to Use
1. Identify Market Phase ⏰: Locate the current index relative to colored zones
2. Understand Capital Flow 🎚️: Monitor transitions between Bitcoin and altcoin dominance
3. Assess Mathematical Value 🌈: Determine optimal allocation based on zone location
4. Adjust Investment Strategy 🔎: Modulate position sizing based on dominance assessment
5. Prepare for Rotation ✅: Anticipate capital shifts when approaching extreme zones
6. Invest with Precision 🛡️: Accumulate altcoins in lower zones, reduce in upper zones
7. Manage Risk Dynamically 🔐: Scale portfolio allocations based on index positioning
Max RR CalculatorAutomatically calculates the maximum RR reached during trade. Entry is at the candle close. There is an option available that takes another trade after getting stopped out on the next candle that is in same bias as first trade.
(If the first trade is a long and gets stopped out, then the second trade will wait until the next up candle to enter long again)
[Stop!Loss] ADR Signal ADR Signal - a technical indicator located in a separate window, which displays by default the 80%-level , as well as the 100%-level of the average daily range (ADR) for the last 10 days and compares it with the current intraday range. The indicator helps not only with the use of a mathematical-statistical method to identify a potential reversal at the moment during intraday trading, but can also serves as an effective assistant in risk management.
👉 Basic mechanics of the indicator
Firstly, this indicator tracks the performance of the standard ATR indicator on the daily chart, in other words, ADR (Average Daily Range).
Important ❗️The ATR (Average True Range) indicator was created by J. Welles Wilder Jr. He first introduced ATR in his book "New Concepts in Technical Trading Systems", published in 1978. Wilder developed this indicator to measure market volatility to help traders estimate the range of price movements. This indicator is built into TradingView, more details can be found by link: www.tradingview.com
Like ATR , ADR calculates the average true range for a specified period. In this case, the distance in points from the maximum of each day to its minimum is calculated, after which the arithmetic mean is calculated - this is ADR .
👉 Visualization
ADR Signal is located in a separate window on the chart and has 3 levels:
1) "ADR level" (green line) - the same parameter, the calculations of which are briefly described above. There is 100%-level of ATR on the daily chart (ADR).
2) "Current level" (red line) - this is the current price passage within the day, calculated in points. At the start of a new day, this parameter is reset. Therefore, in the indicator window, this line has sharp drops at the start of a new trading day: "A new trading day - the instrument's power reserve is renewed again".
3) "Signal level" (blue line) - this is an individually customized value that demonstrates a certain part of the ADR parameter.
👉 Inputs
1) - is responsible for the ATR indicator period, the value of which will always be calculated on the daily chart. The default value is "10", that is, ATR is calculated for the last 10 days (not including the current one).
2) - signal level (in %). The default value is "0.8", that is, 80%-level of the ADR parameter (set earlier) is calculated.
👉 Style
1) - by default, this level is colored "blue".
2) - by default, this level is colored "red".
3) - by default, this level is colored "green".
👉 How to use this indicator
Important❗️ The two methods of the use of the ADR Signal indicator described below will be most effective when trading intraday (which is highlighted quite well below), so it is more logical to use the indicator information on time periods H1 and below.
1) Identifying potential reversals during intraday trading:
The ADR Signal indicator can be used as a potential individual reversal strategy.
Important ❗️It should be noted that using it in it without additional confirming analysis tools will be a rather aggressive trading approach. Therefore, it is best to support the entry point in particular with other methods.
In this case, the crossing of the red line (the number of points passed within the current day, that is, from the minimum of the current day to its maximum) and the blue line (color of the Signal level based on the default settings), indicates that the trading instrument has passed 80% (based on the default settings for the "Signal level") of its average distance from the maximum to the minimum over the past 10 days (based on the default settings for the "ADR Length"). Such a situation in the context of the mathematical-statistical approach indicates a probable reversal, since the "power reserve" of this instrument is mostly exhausted, so one can expect with a higher probability, at least, a price stop and possibly a reversal. In case of crossing of the red line and the green one (ADR level), it says again that based on the mathematical-statistical approach, this trading instrument has completely exhausted its intraday "power reserve". In this situation, a stop or reversal of the price will be even more likely.
Of course, using the "Signal level" parameter, one can filter out even more reliable situations for potential price reversals within a day, namely, by specifying, for example, 1.5 in the field of this parameter. Under such conditions, in the case of crossing the red and blue lines (based on the default style settings), to say that the trading instrument has passed 150% of its average distance over the last 10 days (based on the default style settings "ADR length"). In this case, the probability of a stop or reversal of the price increases even more.
2) Use in risk management:
In terms of risk management, this indicator is more applicable to open trades. For example, if one had an open Buy-position (especially if it is an intraday trade) and the price has raised significantly during the day, then the crossing of the red line with the blue line , and especially the red line with the green line , may indicate that the price will most likely stop growing, since the "power reserve" is almost or completely exhausted for this instrument within the current day. In this case, one can, at a minimum, move the trade to breakeven or even partially fix the profit.
We will continue to discuss the methods of using this indicator and strategies based on it here. And we are always waiting for your reactions and feedback on this topic 💬.
Thank you for your support 🚀
NIG Probability TableNormal-Inverse Gaussian Probability Table
This indicator implements the Normal-Inverse Gaussian (NIG) distribution to estimate the likelihood of future price based on recent market behavior.
📊 Key Features:
- Estimates the parameters (α: tail heaviness, β: skewness, δ: scale, μ: location)
of the NIG distribution using a sliding window over log returns.
- Uses a numerically approximated version of the modified Bessel function (K₁)
to calculate the NIG probability density function (PDF).
- Normalizes the total probability across all bins to ensure the values are interpretable.
- Displays a dynamic probability table showing the chance of future returns falling into each bin.
⚠️ Notes:
- This is a real-time approximation. The Bessel function and posterior inference are simplified.
- Tail probabilities and shape parameters are sensitive to the window size and input settings.
- Useful for risk analysis, option overlays, and strategy filters.
