Psychological Levels (Zones + Alerts) - StableThis technical indicator plot support and resistance levels based on the psychological numbers
指標和策略
MTF Candle Countdown — HUD V1 (By Price-Action-Art)
MTF Candle Countdown — HUD V1 (By Price-Action-Art)
A clean, lightweight HUD that shows you exactly how much time is left in multiple higher-timeframe candles — all in one place.
This tool is designed for traders who rely on multi-timeframe precision.
Instead of constantly switching charts or checking timers, the HUD gives you a real-time countdown for up to six timeframes (Daily, 4H, 1H, 30m, 15m, 5m by default).
You can fully customize the timeframes, text size, and HUD position on your chart.
Perfect for:
Intraday and scalping timing
Swing traders waiting for HTF candle closes
ICT / SMC structure-based traders
Anyone who needs exact candle close timing without distractions
Features:
Real-time multi-timeframe candle countdown
Fully adjustable HUD placement (all corners)
Customizable timeframes and text size
Clean, minimal, and non-intrusive design
Updates only on the last bar for performance efficiency
Optional border for a sharper HUD look
Whether you’re waiting for a Daily close to confirm structure or timing your entries around 5m/15m candles, this HUD keeps everything visible and precise at a glance.
If you find this tool helpful, feel free to like, comment, and follow — it motivates me to keep releasing more tools for the community.
MTF-CPR TableTable gives you CPR values based on Camarilla calculation with S&R 3 & 4 Levels...
Highlights the cell green when Price is in range and marks the Pivot Red when we have a Narrow CPR range...
Enjoy!!
Cumulative Delta Difference HistogramINTRODUCTION:
This "Cumulative Delta Difference Histogram" is a volume-based indicator that calculates the difference (delta) between aggressive buying volume and selling volume for each candle and then builds a cumulative momentum histogram with the following behavior:
Momentum Tracking: The indicator accumulates the delta values when the delta is positive and increasing, producing green bars whose height visually represents growing buying pressure momentum.
Negative Momentum Detection: When the delta becomes negative or starts to decline, the histogram bars turn red and the accumulation decreases, effectively showing increasing selling pressure momentum.
Directional Reset: On each change from positive to negative delta momentum or vice versa, the accumulator resets to zero, providing a clear and sharp visualization of shifts without persistence from previous trends.
Zero Reference Line: A horizontal zero line serves as a visual baseline to distinguish positive from negative momentum easily.
HOW TO USE:
To trade effectively using the "Cumulative Delta Difference Histogram," you compare the price action chart with the indicator to confirm momentum and detect potential reversals or continuations. Here's how to do it in practice:
Confirming Trends:
When the price is rising, look for the histogram bars to be green and increasing, indicating strong and growing buying pressure supporting the uptrend. If price rises but the histogram shows diminishing green bars or shifts to red, it could signal weakening momentum and a potential reversal.
Identifying Divergences:
Compare price highs/lows with histogram peaks. If price makes a new high but the histogram fails to make a corresponding new high (bearish divergence), it warns of a possible trend reversal. Conversely, if price makes a new low but histogram shows higher lows (bullish divergence), it signals potential bullish reversal.
Volume Confirmation:
The histogram reflects real-time volume aggression behind price moves. Confirmation of price breakouts or breakdowns by corresponding strong histogram colors and bar height increases adds reliability to signals.
By aligning price patterns and levels with the cumulative delta histogram's signals, traders gain a deeper understanding of market strength and better timing for trades.
This combined approach improves the accuracy of entries and exits beyond relying on price alone, especially in markets sensitive to order flow and volume dynamics.
Use this indicator with a default volume or with my other indicator "Agression Histogram" for a better reading.
Count█ OVERVIEW
A library of functions for counting the number of times (frequency) that elements occur in an array or matrix.
█ USAGE
Import the Count library.
import joebaus/count/1 as c
Create an array or matrix that is a `float`, `int`, `string`, or `bool` type to count elements from, then call the count function on the array or matrix.
id = array.from(1.00, 1.50, 1.25, 1.00, 0.75, 1.25, 1.75, 1.25)
countMap = id.count() // Alternatively: countMap = c.count(id)
The "count map" will return a map with keys for each unique element in the array or matrix, and with respective values representing the number of times the unique element was counted. The keys will be the same type as the array or matrix counted. The values will always be an `int` type.
array mapKeys = countMap.keys() // Returns unique keys
array mapValues = countMap.values() // Returns counts
If an array is in ascending or descending order, then the keys of the map will also generate in the same order.
intArray = array.from(2, 2, 2, 3, 4, 4, 4, 4, 4, 6, 6) // Ascending order
map countMap = intArray.count() // Creates a "count map" of all unique elements
array mapKeys = countMap.keys() // Returns // Ascending order
array mapValues = countMap.values() // Returns count
Include a value to get the count of only that value in an array or matrix.
floatMatrix = matrix.new(3, 3, 0.0)
floatMatrix.set(0, 0, 1.0), floatMatrix.set(1, 0, 1.0), floatMatrix.set(2, 0, 1.0)
floatMatrix.set(0, 1, 1.5), floatMatrix.set(1, 1, 2.0), floatMatrix.set(2, 1, 2.5)
floatMatrix.set(0, 2, 1.0), floatMatrix.set(1, 2, 2.5), floatMatrix.set(2, 2, 1.5)
int countFloatMatrix = floatMatrix.count(1.0) // Counts all 1.0 elements, returns 5
// Alternatively: int countFloatMatrix = c.count(floatMatrix, 1.0)
The string method of count() can use strings or regular expressions like "bull*" to count all matching occurrences in a string array.
stringArray = array.from('bullish', 'bull', 'bullish', 'bear', 'bull', 'bearish', 'bearish')
int countString = stringArray.count('bullish') // Returns 2
int countStringRegex = stringArray.count('bull*') // Returns 4
To count multiple values, use an array of values instead of a single value. Returning a count map only of elements in the array.
countArray = array.from(1.0, 2.5)
map countMap = floatMatrix.count(countArray)
array mapKeys = countMap.keys() // Returns keys
array mapValues = countMap.values() // Returns counts
Multiple regex patterns or strings can be counted as well.
stringMatrix = matrix.new(3, 3, '')
stringMatrix.set(0, 0, 'a'), stringMatrix.set(1, 0, 'a'), stringMatrix.set(2, 0, 'a')
stringMatrix.set(0, 1, 'b'), stringMatrix.set(1, 1, 'c'), stringMatrix.set(2, 1, 'd')
stringMatrix.set(0, 2, 'a'), stringMatrix.set(1, 2, 'd'), stringMatrix.set(2, 2, 'b')
// Count the number of times the regex patterns `'^(a|c)$'` and `'^(b|d)$'` occur
array regexes = array.from('^(a|c)$', '^(b|d)$')
map countMap = stringMatrix.count(regexes)
array mapKeys = countMap.keys() // Returns
array mapValues = countMap.values() // Returns
An optional comparison operator can be specified to count the number of times an equality was satisfied for `float`, `int`, and `bool` methods of `count()`.
intArray = array.from(2, 2, 2, 3, 4, 4, 4, 4, 4, 6, 6)
// Count the number of times an element is greater than 4
countInt = intArray.count(4, '>') // Returns 2
When passing an array of values to count and a comparison operator, the operator will apply to each value.
intArray = array.from(2, 2, 2, 3, 4, 4, 4, 4, 4, 6, 6)
values = array.from(3, 4)
// Count the number of times and element is greater than 3 and 4
map countMap = intArray.count(values, '>')
array mapKeys = countMap.keys() // Returns
array mapValues = countMap.values() // Returns
Multiple comparison operators can be applied when counting multiple values.
intMatrix = matrix.new(3, 3, 0)
intMatrix.set(0, 0, 2), intMatrix.set(1, 0, 3), intMatrix.set(2, 0, 5)
intMatrix.set(0, 1, 2), intMatrix.set(1, 1, 4), intMatrix.set(2, 1, 2)
intMatrix.set(0, 2, 5), intMatrix.set(1, 2, 2), intMatrix.set(2, 2, 3)
values = array.from(3, 4)
comparisons = array.from('<', '>')
// Count the number of times an element is less than 3 and greater than 4
map countMap = intMatrix.count(values, comparisons)
array mapKeys = countMap.keys() // Returns
array mapValues = countMap.values() // Returns
Daily Vertical Lines 6PM (Arctic Blue – No Sundays)Daily vertical lines to show each day's beginning at 6 pm, very simple, just bars to represent the days of each week in arctic blue, no sundays, so that it goes in tandem with my weekly indicator.
Weekly Vertical Lines (Sunday 6 PM) Weekly BarsSimply a light blue vertical line at the beginning of each week at exactly Sunday at 6 pm.
Rendement périodes (finary compass)Rendement sur une période donnée,
Outil de décision pour stratégie Momentum
indicator CalibrationIndicator Calibration - Multi-Indicator Consensus System
Overview
Indicator Calibration is a powerful consensus-based trading indicator that leverages the MyIndicatorLibrary (NormalizedIndicators) to combine multiple trend-following indicators into a single, actionable signal. By averaging the normalized outputs of up to 8 different trend indicators, this tool provides traders with a clear consensus view of market direction, reducing noise and false signals inherent in single-indicator approaches.
The indicator outputs a value between -1 (strong bearish) and +1 (strong bullish), with 0 representing a neutral market state. This creates an intuitive, easy-to-read oscillator that synthesizes multiple analytical perspectives into one coherent signal.
🎯 Core Concept
Consensus Trading Philosophy
Rather than relying on a single indicator that may give conflicting or premature signals, Indicator Calibration employs a democratic voting system where multiple indicators contribute their normalized opinion:
Each enabled indicator votes: +1 (bullish), -1 (bearish), or 0 (neutral)
The votes are averaged to create a consensus signal
Strong consensus (closer to ±1) indicates high agreement among indicators
Weak consensus (closer to 0) indicates market indecision or transition
Key Benefits
Reduced False Signals: Multiple indicators must agree before strong signals appear
Noise Filtering: Individual indicator quirks are smoothed out by averaging
Customizable: Enable/disable indicators and adjust parameters to suit your trading style
Universal Application: Works across all timeframes and asset classes
Clear Visualization: Simple line oscillator with clear bull/bear zones
📊 Included Indicators
The system can utilize up to 8 normalized trend-following indicators from the library:
1. BBPct - Bollinger Bands Percent
Parameters: Length (default: 20), Factor (default: 2)
Type: Stationary oscillator
Strength: Mean reversion and volatility detection
2. NorosTrendRibbonEMA
Parameters: Length (default: 20)
Type: Non-stationary trend follower
Strength: Breakout detection with momentum confirmation
3. RSI - Relative Strength Index
Parameters: Length (default: 9), SMA Length (default: 4)
Type: Stationary momentum oscillator
Strength: Overbought/oversold with smoothing
4. Vidya - Variable Index Dynamic Average
Parameters: Length (default: 30), History Length (default: 9)
Type: Adaptive moving average
Strength: Volatility-adjusted trend following
5. HullSuite
Parameters: Length (default: 55), Multiplier (default: 1)
Type: Fast-response moving average
Strength: Low-lag trend identification
6. TrendContinuation
Parameters: MA Length 1 (default: 50), MA Length 2 (default: 25)
Type: Dual HMA system
Strength: Trend quality assessment with neutral states
7. LeonidasTrendFollowingSystem
Parameters: Short Length (default: 21), Key Length (default: 10)
Type: Dual EMA crossover
Strength: Simple, reliable trend tracking
8. TRAMA - Trend Regularity Adaptive Moving Average
Parameters: Length (default: 50)
Type: Adaptive trend follower
Strength: Adjusts to trend stability
⚙️ Input Parameters
Source Settings
Source: Choose your price input (default: close)
Can be modified to: open, high, low, close, hl2, hlc3, ohlc4, hlcc4
Indicator Selection
Each indicator can be enabled or disabled via checkboxes:
use_bbpct: Enable/disable Bollinger Bands Percent
use_noros: Enable/disable Noro's Trend Ribbon
use_rsi: Enable/disable RSI
use_vidya: Enable/disable VIDYA
use_hull: Enable/disable Hull Suite
use_trendcon: Enable/disable Trend Continuation
use_leonidas: Enable/disable Leonidas System
use_trama: Enable/disable TRAMA
Parameter Customization
Each indicator has its own parameter group where you can fine-tune:
val 1: Primary period/length parameter
val 2: Secondary parameter (multiplier, smoothing, etc.)
📈 Signal Interpretation
Output Line (Orange)
The main output oscillates between -1 and +1:
+1.0 to +0.5: Strong bullish consensus (all or most indicators agree on uptrend)
+0.5 to +0.2: Moderate bullish bias (bullish indicators outnumber bearish)
+0.2 to -0.2: Neutral zone (mixed signals or transition phase)
-0.2 to -0.5: Moderate bearish bias (bearish indicators outnumber bullish)
-0.5 to -1.0: Strong bearish consensus (all or most indicators agree on downtrend)
Reference Lines
Green line (+1): Maximum bullish consensus
Red line (-1): Maximum bearish consensus
Gray line (0): Neutral midpoint
💡 Trading Strategies
Strategy 1: Consensus Threshold Trading
Entry Rules:
- Long: Output crosses above +0.5 (strong bullish consensus)
- Short: Output crosses below -0.5 (strong bearish consensus)
Exit Rules:
- Exit Long: Output crosses below 0 (consensus lost)
- Exit Short: Output crosses above 0 (consensus lost)
Strategy 2: Zero-Line Crossover
Entry Rules:
- Long: Output crosses above 0 (bullish shift in consensus)
- Short: Output crosses below 0 (bearish shift in consensus)
Exit Rules:
- Exit on opposite crossover
Strategy 3: Divergence Trading
Look for divergences between:
- Price making higher highs while indicator makes lower highs (bearish divergence)
- Price making lower lows while indicator makes higher lows (bullish divergence)
Strategy 4: Extreme Reading Reversal
Entry Rules:
- Long: Output reaches -0.8 or below (extreme bearish consensus = potential reversal)
- Short: Output reaches +0.8 or above (extreme bullish consensus = potential reversal)
Use with caution - best combined with other reversal signals
🔧 Optimization Tips
For Trending Markets
Enable trend-following indicators: Noro's, VIDYA, Hull Suite, Leonidas
Use higher threshold levels (±0.6) to filter out minor retracements
Increase indicator periods for smoother signals
For Range-Bound Markets
Enable oscillators: BBPct, RSI
Use zero-line crossovers for entries
Decrease indicator periods for faster response
For Volatile Markets
Enable adaptive indicators: VIDYA, TRAMA
Use wider threshold levels to avoid whipsaws
Consider disabling fast indicators that may overreact
Custom Calibration Process
Start with all indicators enabled using default parameters
Backtest on your chosen timeframe and asset
Identify which indicators produce the most false signals
Disable or adjust parameters for problematic indicators
Test different threshold levels for entry/exit
Validate on out-of-sample data
📊 Visual Guide
Color Scheme
Orange Line: Main consensus output
Green Horizontal: Bullish extreme (+1)
Red Horizontal: Bearish extreme (-1)
Gray Horizontal: Neutral zone (0)
Reading the Chart
Line above 0: Net bullish sentiment
Line below 0: Net bearish sentiment
Line near extremes: Strong consensus
Line fluctuating near 0: Indecision or transition
Smooth line movement: Stable consensus
Erratic line movement: Conflicting signals
⚠️ Important Considerations
Lag Characteristics
This is a lagging indicator by design (consensus takes time to form)
Best used for trend confirmation rather than early entry
May miss the first portion of strong moves
Reduces false entries at the cost of delayed entries
Number of Active Indicators
More indicators = smoother but slower signals
Fewer indicators = faster but potentially noisier signals
Minimum recommended: 4 indicators for reliable consensus
Optimal: 6-8 indicators for balanced performance
Market Conditions
Best: Strong trending markets (up or down)
Good: Volatile markets with clear directional moves
Poor: Choppy, sideways markets with no clear trend
Worst: Low-volume, range-bound conditions
Complementary Tools
Consider combining with:
Volume analysis for confirmation
Support/resistance levels for entry/exit points
Market structure analysis (higher timeframe trends)
Risk management tools (ATR-based stops)
🎓 Example Use Cases
Swing Trading
Timeframe: Daily or 4H
Enable: All 8 indicators with default parameters
Entry: Consensus > +0.5 or < -0.5
Hold: Until consensus reverses to opposite extreme
Day Trading
Timeframe: 15m or 1H
Enable: Faster indicators (RSI, BBPct, Noro's, Hull Suite)
Entry: Zero-line crossover with volume confirmation
Exit: Opposite crossover or profit target
Position Trading
Timeframe: Weekly or Daily
Enable: Slower indicators (TRAMA, VIDYA, Trend Continuation)
Entry: Strong consensus (±0.7) with higher timeframe confirmation
Hold: Months until consensus weakens significantly
🔬 Technical Details
Calculation Method
1. Each enabled indicator calculates its normalized signal (-1, 0, or +1)
2. All active signals are stored in an array
3. Array.avg() computes the arithmetic mean
4. Result is plotted as a continuous line
Output Range
Theoretical: -1.0 to +1.0
Practical: Typically ranges between -0.8 to +0.8
Rare: All indicators perfectly aligned at ±1.0
Performance
Lightweight calculation (simple averaging)
No repainting (all indicators are non-repainting)
Compatible with all Pine Script features
Works on all TradingView plans
📋 License
This code is subject to the Mozilla Public License 2.0 at mozilla.org
🚀 Quick Start Guide
Add to Chart: Apply indicator to your chart
Choose Timeframe: Select appropriate timeframe for your trading style
Enable Indicators: Start with all 8 enabled
Observe Behavior: Watch how consensus forms during different market conditions
Calibrate: Adjust parameters and indicator selection based on observations
Backtest: Validate your settings on historical data
Trade: Apply with proper risk management
🎯 Key Takeaways
✅ Consensus beats individual indicators - Multiple perspectives reduce errors
✅ Customizable to your style - Enable/disable and tune to preference
✅ Simple interpretation - One line tells the story
✅ Works across markets - Stocks, crypto, forex, commodities
✅ Reduces emotional trading - Clear, objective signal generation
✅ Professional-grade - Built on proven technical analysis principles
Indicator Calibration transforms complex multi-indicator analysis into a single, actionable signal. By harnessing the collective wisdom of multiple proven trend-following systems, traders gain a powerful edge in identifying high-probability trade setups while filtering out market noise.
MAG8 Breadth RSI This indicator is for my personal monitoring breadth of MAG 8 , including AVGO for use to trade spy/es and qqq/nq.
A green bar over 6 translates to 6 out of the 8 stocks have RSI's<30. Conversely a red indicator at 6 would indicate 6 out of 8 are overbought, RSI >70.
Extreme 6-8 of 8 either overbought (red) or oversold (green)
Moderate 4-5 of 8 either overbought (red) or oversold (green)
No Signal 0-3 of 8 either overbought (red) or oversold (green)
Not trading advice but thought I would share.
Smart RSI Money Flow — Core Bands V1.01SMART RSI – Money Flow Bands (Technical Overview)
1. Background: RSI and Its Behavior on Lower Timeframes
The Relative Strength Index (RSI) originally is a momentum oscillator calculated from average gains and losses over a selected period. In its standard form, RSI is derived solely from price changes; it does not incorporate volume data or order-flow information in its formula.
Because RSI is price-based, its interpretation depends strongly on the timeframe:
• On higher timeframes, each bar aggregates more trading activity, and RSI tends to behave more smoothly.
• On lower timeframes (1-hour down to intraday scalping intervals), price fluctuations are quicker, and RSI becomes more sensitive to short-term noise.
This does not imply that RSI becomes invalid, but that its signals on fast charts can be more reactive and may benefit from additional context such as volume behavior or structural information.
2. Purpose of This Indicator
This indicator extends the classical RSI by adding information that RSI does not include:
• Mapping RSI values into price-based bands instead of the 0–100 oscillator space.
• Retrieving lower timeframe volume data and separating it into buy and sell components.
• Comparing the slope (angle) of price movement with the slope of buy and sell volume.
The goal is to provide a structural interpretation of where price sits relative to RSI conditions and how volume is behaving on a lower timeframe.
3. Technical Differences Compared to Classical RSI
A) Classical RSI
• Input: price only (usually close).
• Output: normalized oscillator between 0 and 100.
• Does not incorporate intra-bar volume distribution.
• Does not separate buy/sell volume.
B) SMART RSI – Money Flow Bands
1) RSI-to-Price Mapping
Converts RSI values into upper/lower price bands using recent price extremes.
2) Lower Timeframe Volume Decomposition
Retrieves LTF data and splits each bar’s volume into buy (close>open) and sell (close
NormalizedIndicatorsNormalizedIndicators - Comprehensive Trend Normalization Library
Overview
This Pine Script™ library provides an extensive collection of normalized trend-following indicators and calculation functions for technical analysis. The main advantage of this library lies in its unified signal output: All trend indicators are normalized to a standardized format where 1 represents a bullish signal, -1 represents a bearish signal, and 0 (where applicable) represents a neutral signal.
This normalization enables traders to seamlessly combine different indicators, create consensus signals, and develop complex multi-indicator strategies without worrying about different scales and interpretations.
📊 Categories
The library is divided into two main categories:
1. Trend-Following Indicators
2. Calculation Indicators
🔄 Trend-Following Indicators
Stationary Indicators
These oscillate around a fixed value and are not bound to price.
BBPct() - Bollinger Bands Percent
Source: Algoalpha X Sushiboi77
Parameters:
Length: Period for Bollinger Bands
Factor: Standard deviation multiplier
Source: Price source (typical: close)
Logic: Calculates the position of price within the Bollinger Bands as a percentage
Signal:
1 (bullish): when positionBetweenBands > 50
-1 (bearish): when positionBetweenBands ≤ 50
Special Feature: Uses an array to store historical standard deviations for additional analysis
RSI() - Relative Strength Index
Source: TradingView
Parameters:
len: RSI period
src: Price source
smaLen: Smoothing period for RSI
Logic: Classic RSI with additional SMA smoothing
Signal:
1 (bullish): RSI-SMA > 50
-1 (bearish): RSI-SMA < 50
0 (neutral): RSI-SMA = 50
Non-Stationary Indicators
These follow price movement and have no fixed boundaries.
NorosTrendRibbonSMA() & NorosTrendRibbonEMA()
Source: ROBO_Trading
Parameters:
Length: Moving average and channel period
Source: Price source
Logic: Creates a price channel based on the highest/lowest MA value over a specified period
Signal:
1 (bullish): Price breaks above upper band
-1 (bearish): Price breaks below lower band
0 (neutral): Price within channel (maintains last state)
Difference: SMA version uses simple moving averages, EMA version uses exponential
TrendBands()
Source: starlord_xrp
Parameters: src (price source)
Logic: Uses 12 EMAs (9-30 period) and checks if all are rising or falling simultaneously
Signal:
1 (bullish): All 12 EMAs are rising
-1 (bearish): All 12 EMAs are falling
0 (neutral): Mixed signals
Special Feature: Very strict conditions - extremely strong trend filter
Vidya() - Variable Index Dynamic Average
Source: loxx
Parameters:
source: Price source
length: Main period
histLength: Historical period for volatility calculation
Logic: Adaptive moving average that adjusts to volatility
Signal:
1 (bullish): VIDYA is rising
-1 (bearish): VIDYA is falling
VZO() - Volume Zone Oscillator
Parameters:
source: Price source
length: Smoothing period
volumesource: Volume data source
Logic: Combines price and volume direction, calculates the ratio of directional volume to total volume
Signal:
1 (bullish): VZO > 14.9
-1 (bearish): VZO < -14.9
0 (neutral): VZO between -14.9 and 14.9
TrendContinuation()
Source: AlgoAlpha
Parameters:
malen: First HMA period
malen1: Second HMA period
theclose: Price source
Logic: Uses two Hull Moving Averages for trend assessment with neutrality detection
Signal:
1 (bullish): Uptrend without divergence
-1 (bearish): Downtrend without divergence
0 (neutral): Trend and longer MA diverge
LeonidasTrendFollowingSystem()
Source: LeonidasCrypto
Parameters:
src: Price source
shortlen: Short EMA period
keylen: Long EMA period
Logic: Simple dual EMA crossover system
Signal:
1 (bullish): Short EMA < Key EMA
-1 (bearish): Short EMA ≥ Key EMA
ysanturtrendfollower()
Source: ysantur
Parameters:
src: Price source
depth: Depth of Fibonacci weighting
smooth: Smoothing period
bias: Percentage bias adjustment
Logic: Complex system with Fibonacci-weighted moving averages and bias bands
Signal:
1 (bullish): Weighted MA > smoothed MA (with upward bias)
-1 (bearish): Weighted MA < smoothed MA (with downward bias)
0 (neutral): Within bias zone
TRAMA() - Trend Regularity Adaptive Moving Average
Source: LuxAlgo
Parameters:
src: Price source
length: Adaptation period
Logic: Adapts to trend regularity - accelerates in stable trends, slows in consolidations
Signal:
1 (bullish): Price > TRAMA
-1 (bearish): Price < TRAMA
0 (neutral): Price = TRAMA
HullSuite()
Source: InSilico
Parameters:
_length: Base period
src: Price source
_lengthMult: Length multiplier
Logic: Uses Hull Moving Average with lagged comparisons for trend determination
Signal:
1 (bullish): Current Hull > Hull 2 bars ago
-1 (bearish): Current Hull < Hull 2 bars ago
0 (neutral): No change
STC() - Schaff Trend Cycle
Source: shayankm (described as "Better MACD")
Parameters:
length: Cycle period
fastLength: Fast MACD period
slowLength: Slow MACD period
src: Price source
Logic: Combines MACD concepts with stochastic normalization for early trend signals
Signal:
1 (bullish): STC is rising
-1 (bearish): STC is falling
🧮 Calculation Indicators
These functions provide specialized mathematical calculations for advanced analysis.
LCorrelation() - Long-term Correlation
Creator: unicorpusstocks
Parameters:
Input: First time series
Compare: Second time series
Logic: Calculates the average of correlations across 6 different periods (30, 60, 90, 120, 150, 180)
Returns: Correlation value between -1 and 1
Application: Long-term relationship analysis between assets, markets, or indicators
MCorrelation() - Medium-term Correlation
Creator: unicorpusstocks
Parameters:
Input: First time series
Compare: Second time series
Logic: Calculates the average of correlations across 6 different periods (15, 30, 45, 60, 75, 90)
Returns: Correlation value between -1 and 1
Application: Medium-term relationship analysis with higher sensitivity
assetBeta() - Beta Coefficient
Creator: unicorpusstocks
Parameters:
measuredSymbol: The asset to be measured
baseSymbol: The reference asset (e.g., market index)
Logic:
Calculates Beta across 4 different time horizons (50, 100, 150, 200 periods)
Beta = Correlation × (Asset Standard Deviation / Market Standard Deviation)
Returns the average of all 4 Beta values
Returns: Beta value (typically 0-2, can be higher/lower)
Interpretation:
Beta = 1: Asset moves in sync with the market
Beta > 1: Asset more volatile than market
Beta < 1: Asset less volatile than market
Beta < 0: Asset moves inversely to the market
💡 Usage Examples
Example 1: Multi-Indicator Consensus
pinescriptimport unicorpusstocks/MyIndicatorLibrary/1 as lib
// Combine multiple indicators
signal1 = lib.BBPct(20, 2.0, close)
signal2 = lib.RSI(14, close, 5)
signal3 = lib.TRAMA(close, 50)
// Consensus signal: At least 2 of 3 must agree
consensus = (signal1 + signal2 + signal3)
strongBuy = consensus >= 2
strongSell = consensus <= -2
Example 2: Correlation-Filtered Trading
pinescriptimport unicorpusstocks/MyIndicatorLibrary/1 as lib
// Only trade when strong correlation with market exists
spy = request.security("SPY", timeframe.period, close)
correlation = lib.MCorrelation(close, spy)
trendSignal = lib.NorosTrendRibbonEMA(50, close)
// Only bullish signals with positive correlation
tradeBuy = trendSignal == 1 and correlation > 0.5
tradeSell = trendSignal == -1 and correlation > 0.5
Example 3: Beta-Adjusted Position Sizing
pinescriptimport unicorpusstocks/MyIndicatorLibrary/1 as lib
spy = request.security("SPY", timeframe.period, close)
beta = lib.assetBeta(close, spy)
// Adjust position size based on Beta
basePositionSize = 100
adjustedSize = basePositionSize / beta // Less size with high Beta
⚙️ Technical Details
Normalization Standard
Bullish: 1
Bearish: -1
Neutral: 0 (only for selected indicators)
Advantages of Normalization
Simple Aggregation: Signals can be added/averaged
Consistent Interpretation: No confusion about different scales
Strategy Development: Simplified logic for backtesting
Combinability: Seamlessly mix different indicator types
Performance Considerations
All functions are optimized for Pine Script v5
Proper use of var for state management
Efficient array operations where needed
Minimal recursive calls
📋 License
This code is subject to the Mozilla Public License 2.0. More details at: mozilla.org
🎯 Use Cases
This library is ideal for:
Quantitative Traders: Systematic strategy development with unified signals
Multi-Timeframe Analysis: Consensus across different timeframes
Portfolio Managers: Beta and correlation analysis for diversification
Algo Traders: Machine learning with standardized features
Retail Traders: Simplified signal interpretation without deep technical knowledge
🔧 Installation
pinescriptimport unicorpusstocks/MyIndicatorLibrary/1
Then use the functions with your chosen alias:
pinescriptlib.BBPct(20, 2.0, close)
lib.RSI(14, close, 5)
// etc.
⚠️ Important Notes
All indicators are lagging, as is typical for trend-following indicators
Signals should be combined with additional analysis (volume, support/resistance, etc.)
Backtesting is recommended before starting live trading with these signals
Different assets and timeframes may require different parameter optimizations
This library provides a solid foundation for professional trading system design with the flexibility to develop your own complex strategies while abstracting away technical complexity.
CM_MACD_Ult_MTF + Entry SignalsThis script is an enhanced and updated version of the classic CM_Ult_MacD_MTF originally created by ChrisMoody.
It preserves the full functionality, look, and behavior of the original multi-timeframe MACD, including:
Multi-timeframe MACD calculation
4-color histogram based on momentum direction
Optional MACD and Signal line display
Optional crossover dots
Color-changing MACD line on signal cross
Zero-line reference
This upgraded version adds entry signals based on MACD/Signal crossovers:
New Features Added
LONG @ price label when MACD crosses above Signal
SHORT @ price label when MACD crosses below Signal
Labels appear directly at the crossover point
Full support for Pine Script® v6, making it compatible with TradingView’s latest publishing requirements
Why this version?
The original script was written in an older Pine version and was no longer publishable.
This version keeps the full visual identity and logic of the classic MACD while adding modern compatibility and helpful trading signals.
Credits
Original concept and visual framework: ChrisMoody
Added features, Pine v6 migration, and enhancements: tgambinox
TASC 2025.12 The One Euro Filter█ OVERVIEW
This script implements the One Euro filter, developed by Georges Casiez, Nicolas Roussel, and Daniel Vogel, and adapted by John F. Ehlers in his article "Low-Latency Smoothing" from the December 2025 edition of the TASC Traders' Tips . The original creators gave the filter its name to suggest that it is cheap and efficient, like something one might purchase for a single Euro.
█ CONCEPTS
The One Euro filter is an EMA-based low-pass filter that adapts its smoothing factor (alpha) based on the absolute values of smoothed rates of change in the source series. It was designed to filter noisy, high-frequency signals in real time with low latency. Ehlers simplifies the filter for market analysis by calculating alpha in terms of bar periods rather than time and frequency, because periods are naturally intuitive for a discrete financial time series.
In his article, Ehlers demonstrates how traders can apply the adaptive One Euro filter to a price series for simple low-latency smoothing. Additionally, he explains that traders can use the filter as a smoothed oscillator by applying it to a high-pass filter. In essence, similar to other low-pass filters, traders can apply the One Euro filter to any custom source to derive a smoother signal with reduced noise and low lag.
This script applies the One Euro filter to a specified source series, and it applies the filter to a two-pole high-pass filter or other oscillator, depending on the selected "Osc type" option. By default, it displays the filtered source series on the main chart pane, and it shows the oscillator and its filtered series in a separate pane.
█ INPUTS
Source: The source series for the first filter and the selected oscillator.
Min period: The minimum cutoff period for the smoothing calculation.
Beta: Controls the responsiveness of the filter. The filter adds the product of this value and the smoothed source change to the minimum period to determine the filter's smoothing factor. Larger values cause more significant changes in the maximum cutoff period, resulting in a smoother response.
Osc type: The type of oscillator to calculate for the pane display. By default, the indicator calculates a high-pass filter. If the selected type is "None", the indicator displays the "Source" series and its filtered result in a separate pane rather than showing the filter on the main chart. With this setting, users can pass plotted values from another indicator and view the filtered result in the pane.
Period: The length for the selected oscillator's calculation.
MTF Checklist DashboardMTF Checklist Dashboard
Overview
The MTF Checklist Dashboard is an advanced multi-timeframe analysis tool that provides traders with a comprehensive visual dashboard to analyze market conditions across six customizable timeframes simultaneously. This indicator combines multiple technical analysis methods, including Opening Range Breakouts (ORB), VWAP, EMAs, and daily price levels, to generate high-probability confluence-based trading signals.
Unlike traditional single-timeframe indicators, this dashboard displays all critical information in one organized table, allowing traders to instantly identify when multiple timeframes align for optimal entry and exit opportunities.
Key Features
Multi-Timeframe Analysis
Analyzes up to 6 timeframes simultaneously (default: 1m, 5m, 15m, 30m, 1h, 4h)
Fully customizable timeframe selection via comma-separated input
Color-coded cells for instant visual recognition (green=bullish, red=bearish, yellow=neutral)
Technical Indicators Tracked
Current and previous candle direction
Opening Range Breakout (ORB) positioning with custom period
VWAP relationship (above/below)
200 EMA positioning
Daily and previous day high/low proximity
EMA crossovers (9 vs 21, both vs 200)
Advanced Signal Filtering System
Confluence scoring: Requires multiple timeframes to align (3-6 timeframes)
Higher timeframe confirmation: Ensures 30m/1h/4h agreement
Volume filter: Confirms signals with above-average volume (1.5x default)
ATR volatility filter: Validates sufficient market movement
Session timing: Restricts signals to optimal trading hours (EST)
Momentum confirmation: Requires recent directional strength
Range positioning: Blocks signals near daily extremes
Candle strength: Validates strong directional candles (60%+ body ratio)
Visual Signals
Optional entry arrows (above/below bars)
Background color highlighting
Organized dashboard with real-time price levels
ORB range, current day, and previous day summary rows
Alert Conditions
JSON-formatted alerts for automated trading integration
Separate alerts for long entry, short entry, long exit, and short exit
Compatible with webhook automation systems
How To Use
Dashboard Interpretation
The dashboard displays a color-coded table with the following columns:
TF: Timeframe being analyzed
C: Current candle (Green=bullish, Red=bearish)
P: Previous candle (Green=bullish, Red=bearish)
ORB: Opening Range Breakout position (A=Above, B=Below, W=Within)
VWAP: Price vs VWAP (A=Above, B=Below)
E200: Price vs 200 EMA (A=Above, B=Below)
D Hi/Lo: Proximity to current day high/low (Hi/Lo/Mid)
PD Hi/Lo: Proximity to previous day high/low (Hi/Lo/Mid)
9 vs 21: EMA 9 vs EMA 21 relationship (A=9 above 21, B=9 below 21)
9&21 v200: Both EMAs vs 200 EMA (>>=both above, <<=both below, <>=mixed)
Signal Generation
Long Entry Signal triggers when:
Minimum number of timeframes show bullish alignment (default: 5 of 6)
Higher timeframes (30m/1h/4h) confirm direction (default: 2 of 3)
Price breaks above ORB high with sufficient distance
Volume exceeds average by specified multiplier
ATR shows adequate volatility
Trade occurs during optimal session hours
Recent momentum is upward
Price not too close to daily high
Strong bullish candle forms
Short Entry Signal uses opposite conditions
Exit Signals trigger when opposing timeframe confluence reaches threshold (default: 3 timeframes)
Recommended Workflow
Select your asset and primary trading timeframe
Observe the dashboard - Look for rows showing mostly green (bullish) or red (bearish)
Wait for alignment - The indicator will show arrows when confluence requirements are met
Check the bottom rows - Review ORB levels and daily ranges for context
Set alerts - Enable TradingView alerts using the built-in alert conditions
Manage risk - Use appropriate position sizing and stop losses based on ORB range or daily ATR
Settings Guide
Basic Settings
Timeframes: Enter comma-separated values (e.g., "1,5,15,30,60,240")
Show Header: Toggle column headers on/off
ORB Minutes: Set opening range period (default: 15 minutes)
Near % for daily highs/lows: Define proximity threshold (default: 0.20%)
Use close for comparisons: Compare using close vs current price
Dashboard Position: Choose from 9 screen positions
Confluence Filters
Minimum Timeframes Aligned: Set required confluence (3-6, default: 5)
Require Higher Timeframe Confirmation: Toggle HTF requirement on/off
Min Higher Timeframes: Specify HTF agreement needed (1-3, default: 2)
Volume Filter
Volume Confirmation: Enable/disable volume filtering
Volume vs Average: Set multiplier threshold (default: 1.5x)
Volume Average Length: Period for volume average (default: 20 bars)
Volatility Filter (ATR)
Volatility Filter: Enable/disable ATR confirmation
ATR Length: Calculation period (default: 14)
Min ATR vs Average: Required ATR level (default: 0.5x = 50%)
ORB Filters
ORB Breakout Distance Required: Toggle distance requirement
Min Breakout % Beyond ORB: Additional breakout threshold (default: 0.10%)
Session Filter
Trade Only During Best Hours: Enable time-based filtering
Session 1: First trading window (default: 0930-1130 EST)
Session 2: Second trading window (default: 1400-1530 EST)
Momentum Filter
Recent Momentum Required: Enable directional momentum check
Lookback Bars: Period for momentum comparison (default: 3 bars)
Daily Range Filter
Block Signals Near Daily Extremes: Prevent entries at extremes
Distance from High/Low %: Minimum distance required (default: 2.0%)
Candle Filter
Strong Directional Candle: Require candle strength
Min Candle Body %: Body-to-range ratio threshold (default: 60%)
Visual Signals
Show Entry Signals: Master toggle for visual signals
Show Arrows: Display entry arrows on chart
Background Color: Enable background highlighting
Best Practices
Start with default settings and adjust based on your trading style and asset volatility
Higher confluence requirements (5-6 timeframes) produce fewer but higher-quality signals
Enable all filters for conservative trading; disable some for more frequent signals
Use the dashboard as confirmation alongside your existing trading strategy
Backtest on your specific instruments before live trading
Consider market conditions—trending vs ranging markets may require different settings
Alerts
This indicator includes four alert conditions with JSON formatting for webhook integration:
Long Entry Signal: Triggers when all long conditions are met
Short Entry Signal: Triggers when all short conditions are met
Long Exit Signal: Triggers when opposing confluence reaches exit threshold
Short Exit Signal: Triggers when opposing confluence reaches exit threshold
Alert messages include ticker symbol, action (buy/sell), price, and quantity for automated trading systems.
Important Notes
This indicator works best on liquid instruments with clear price action
Highly volatile markets may require adjusted ATR and ORB distance settings
Session times are in EST timezone—adjust if trading non-US markets
The ORB calculation requires sufficient price history for the day
Signals are generated in real-time but should be confirmed at candle close
Limitations
Maximum of 6 timeframes can be analyzed due to TradingView's security call limits
ORB calculations may not work correctly on instruments with gaps or irregular sessions
The indicator is most effective during regular market hours when volume and volatility are adequate
Lower timeframes (1m, 5m) may produce more false signals in choppy conditions
License
Mozilla Public License 2.0 (MPL-2.0)
This indicator is licensed under the Mozilla Public License 2.0. You are free to use, modify, and distribute this code under the terms of the MPL-2.0. The full license text is available at mozilla.org
Key license provisions:
You may use this code commercially
You may modify and distribute modified versions
Modified versions must be released under the same license
You must include the original license notice in any distributions
No trademark rights are granted
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results. Trading involves substantial risk of loss. Always:
Practice proper risk management
Test thoroughly on paper/demo accounts before live trading
Use appropriate position sizing
Never risk more than you can afford to lose
Consult with a financial advisor for personalized advice
The creator assumes no liability for trading losses incurred using this indicator.
Version: 2.0
Pine Script Version: v6
Author: © EliasVictor
Previous Day & Week Highs and Lows 1.3Overlay indicator that plots horizontal lines for the previous day’s and previous week’s highs and lows. Lines extend until the next period starts, so you can see these levels throughout the current day or week.
The indicator detects new daily and weekly sessions and draws lines at the previous period’s high and low. Daily levels use green (high) and red (low); weekly levels use blue (high) and magenta (low). You can toggle daily/weekly independently, customize colors, and adjust line width. It works on intraday timeframes and helps identify support/resistance and track breakouts relative to prior periods.
Sentiment Heatmap with EMA Sentiment Heatmap with EMA Let’s build a script mini-LuxAlgo-style sentiment heatmap Enhanced Simple Sentiment Heatmap + Right-Side Legend Automatic legend on the right side
Just like professional indicators:
MAX GREED
GREED
NEUTRAL
FEAR
MAX FEAR
✔ Legend stays updated on the last bar
It moves automatically as price moves.
✔ Trend EMA included (optional) 9 EMA → White
20 EMA → Red
50 EMA → Yellow
100 EMA → Blue
200 EMA → Purple Alerts (e.g., “Max Fear – Buy Zone”)
✔ Liquidity line / support-resistance auto zones Full sentiment heatmap (Greed → Fear)
✔ Right-side legend like LuxAlgo
✔ All 5 EMAs added (my colors): EMA trend cloud (9/20, 20/50, 50/200)
Buy/Sell circles based on sentiment reversals Right-side legend: MAX GREED / GREED / NEUTRAL / FEAR / MAX FEAR
5 EMAs:
9 → White
20 → Red
50 → Yellow
100 → Blue
200 → Purple
Net Liquidity (WALCL - TGA - ON RRP)//@version=5
indicator("Net Liquidity (WALCL - TGA - ON RRP)", overlay=false, timeframe="W")
a = request.security("FRED:WALCL", "W", close) // Fed total assets (millions)
b = request.security("FRED:WTREGEN", "W", close) // TGA (millions)
c = request.security("FRED:RRPONTSYD","W", close) // ON RRP (millions)
netliq = (a - b - c) / 1000.0 // billions
plot(netliq, color=color.new(color.blue, 0), linewidth=2)
RSI Percentage - Current Candle Only - BHAFANTA FX
**Title:** RSI Percentage - Current Candle Only - BHAFANTA FX
**Description:**
This indicator displays the **Relative Strength Index (RSI)** as a percentage for the **current candle only**, giving traders an immediate view of market momentum. Perfect for short-term analysis and quick decision-making, it avoids clutter by showing only the most relevant RSI value.
**Key Features:**
* Shows **RSI percentage of the current candle** only
* Display is **clean and readable**, positioned above the current candle
* Adjustable RSI length and source for flexibility
* Designed for traders who want **fast, actionable insight** without visual clutter
**Use Case:**
* Ideal for **scalpers and intraday traders** who want to gauge overbought or oversold conditions quickly.
* Can be combined with other indicators like EMA, MACD, or trend filters for more robust strategies.
**Developer:** BHAFANTA FX
Smoothed VWAP Bands🎯 Best Smoothing Setting for Scalping (What You Should Use)
Style σ Smoothing Result
Fast scalping (1min) EMA 14 Very responsive, still filters noise
Balanced intraday (1–5min) EMA 20 Best overall reliability
Slow confirmation (5–15min) EMA 30 Eliminates nearly all fakeouts
✅ What We Are Actually Smoothing
You are NOT smoothing VWAP itself.
You are smoothing the standard deviation (σ) that creates the VWAP bands:
✔ What this does:
* Computes the raw standard deviation (σ) of price relative to VWAP
* Smooths that σ using EMA smoothing
* Builds ±1 and ±2 bands using the smoothed σ
* You get clean, stable bands that filter fakeouts
✔ Result:
* Bands do NOT twitch in chop
* Fakeouts are filtered
* Real breakouts show obvious expansion
Day Open ± Ø DailyRangeScript Function Description
This indicator draws two horizontal dashed lines during the Regular Trading Hours (RTH) session.
The upper line is calculated as the RTH Open price plus the average daily range (based on the last 10 days).
The lower line is calculated as the RTH Open price minus the average daily range.
🔍 How it works
Average Daily Range (ADR): The script requests daily candles and computes the 10‑day simple moving average of the daily range (High–Low). This value remains constant throughout the trading day.
RTH Detection: The script identifies the first bar of the RTH session (e.g., 09:00 local exchange time). The open price of this bar is stored as the RTH Open.
Line Creation: At the first RTH bar, two dashed lines are drawn:
Green line above the RTH Open (Open + ADR).
Red line below the RTH Open (Open – ADR).
Dynamic Extension: As new bars appear, the lines are automatically extended to the current bar, keeping their Y‑values constant. This ensures the levels remain visible throughout the session.
✅ What Users See
A green dashed line above the RTH Open, marking the typical upside boundary.
A red dashed line below the RTH Open, marking the typical downside boundary.
Both lines start at the first RTH bar and extend to the latest bar of the session.
This helps traders quickly assess whether price action is staying within or breaking beyond the typical daily range relative to the RTH Open.
