Inverse Fisher Transform on SMI (Stochastic Momentum Index)Inverse Fisher Transform on SMI (Stochastic Momentum Index)
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity. The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
Cerca negli script per "indicators"
Infinite EMA with Alpha Control♾️ Infinite EMA with Alpha Control
What Makes This EMA "Infinite"?
Unlike traditional EMA indicators that are limited to typical periods (1-5000), this Infinite EMA breaks all boundaries. You can create EMAs with periods of 1,000, 10,000, or even 1,000,000 bars - that's why it's called "infinite"! Also Infinite EMA starts working immediately from the very first bar on your chart
Why This EMA is "Infinite":
1. Mathematically: When N → ∞, alpha → 0, meaning infinitely long "memory"
2. Practically: You can set any period - even 100,000 bars
3. Flexibility: Alpha allows precise control over the "forgetting speed"
How Does It Work?
The magic lies in the Alpha parameter. While regular EMAs use fixed formulas, this indicator gives you direct control over the EMA's "memory" through Alpha values:
• High Alpha (0.1-0.2): Fast reaction, short memory
• Medium Alpha (0.01-0.05): Balanced response
• Low Alpha (0.0001-0.001): Extremely slow reaction, very long memory
• Ultra-low Alpha (0.000001): Almost frozen in time
The Mathematical Formula:
Alpha = 2 / (Period + 1)
This means you can achieve any EMA period by adjusting Alpha, giving you infinite flexibility!
Expanded "Infinite EMA" Table:
Period EMA (N) - Alpha (Rounded) - Alpha (Exact) - Description
10 - 0.1818 - 0.181818... - Fast EMA
20 - 0.0952 - 0.095238... - Short-term
50 - 0.0392 - 0.039215... - Medium-term
100 - 0.0198 - 0.019801... - Long-term
200 - 0.0100 - 0.009950... - Standard long-term
500 - 0.0040 - 0.003996... - Very long-term
1,000 - 0.0020 - 0.001998... - Super long-term
2,000 - 0.0010 - 0.000999... - Ultra long-term
5,000 - 0.0004 - 0.000399... - Mega long-term
10,000 - 0.0002 - 0.000199... - Giga long-term
25,000 - 0.00008 - 0.000079... - Century-scale EMA
50,000 - 0.00004 - 0.000039... - Practically motionless
100,000 - 0.00002 - 0.000019... - "Glacial" EMA
500,000 - 0.000004 - 0.000003... - Geological timescale
1,000,000 - 0.000002 - 0.000001... - Approaching constant
5,000,000 - 0.0000004 - 0.0000003... - Virtually static
10,000,000 - 0.0000002 - 0.0000001... - Nearly flat line
100,000,000 - 0.00000002 - 0.00000001... - Mathematical infinity
Formula: Alpha = 2/(N+1) where N is the EMA period
Key Features:
Dual EMA System: Run fast and slow EMAs simultaneously
Crossover Signals: Automatic buy/sell signals with customizable alerts
Alpha Control: Direct mathematical control over EMA behavior
Infinite Periods: From 1 to 100,000,000+ bars
Visual Customization: Colors, fills, backgrounds, signal sizes
Instant Start: Works accurately from the very first bar
Update Intervals: Control calculation frequency for noise reduction
Why Choose Infinite EMA?
1. Unlimited Flexibility: Any period you can imagine
2. Mathematical Precision: Direct alpha control for exact behavior
3. Professional Grade: Suitable for all trading styles
4. Easy to Use: Simple settings with powerful results
5. No Warm-up Period: Accurate values from bar #1
Simple Explanation:
Think of EMA as a "memory system":
• High Alpha = Short memory (forgets quickly, reacts fast)
• Low Alpha = Long memory (remembers everything, moves slowly)
With Infinite EMA, you can set the "memory length" to anything from seconds to centuries!
⚡ Instant Start Feature - EMA from First Bar
Immediate Calculation from Bar #1
Unlike traditional EMA indicators that require a "warm-up period" of N bars before showing accurate values, Infinite EMA starts working immediately from the very first bar on your chart.
How It Works:
Traditional EMA Problem:
• Standard 200-period EMA: Needs 200+ bars to become accurate
• First 200 bars: Shows incorrect/unstable values
• Result: Large portions of historical data are unusable
Infinite EMA Solution:
Bar #1: EMA = Current Price (perfect starting point)
Bar #2: EMA = Alpha × Price + (1-Alpha) × Previous EMA
Bar #3: EMA = Alpha × Price + (1-Alpha) × Previous EMA
...and so on
Key Benefits:
No Warm-up Period: Start trading signals from day one
Full Chart Coverage: Every bar has a valid EMA value
Historical Accuracy: Backtesting works on entire dataset
New Markets: Works perfectly on newly listed assets
Short Datasets: Effective even with limited historical data
Practical Impact:
Scenario Traditional EMA Infinite EMA
New cryptocurrency Unusable for first 200 days ✅ Works from day 1
Limited data (< 200 bars) Inaccurate values ✅ Fully functional
Backtesting Must skip first 200 bars ✅ Test entire history
Real-time trading Wait for stabilization ✅ Trade immediately
Technical Implementation:
if barstate.isfirst
EMA := currentPrice // Perfect initialization
else
EMA := alpha × currentPrice + (1-alpha) × previousEMA
This smart initialization ensures mathematical accuracy from the very first calculation, eliminating the traditional EMA "ramp-up" problem.
Why This Matters:
For Backesters: Use 100% of available data
For Live Trading: Get signals immediately on any timeframe
For Researchers: Analyze complete datasets without gaps
Bottom Line: Infinite EMA is ready to work the moment you add it to your chart - no waiting, no warm-up, no exceptions!
Unlike traditional EMAs that require a "warm-up period" of 200+ bars before showing accurate values, Infinite EMA starts working immediately from bar #1.
This breakthrough eliminates the common problem where the first portion of your chart shows unreliable EMA data. Whether you're analyzing a newly listed cryptocurrency, working with limited historical data, or backtesting strategies, every single bar provides mathematically accurate EMA values.
No more waiting periods, no more unusable data sections - just instant, reliable trend analysis from the moment you apply the indicator to any chart.
🔄 Update Interval Bars Feature
The Update Interval feature allows you to control how frequently the EMA recalculates, providing flexible noise filtering without changing the core mathematics.
Set to 1 for standard behavior (updates every bar), or increase to 5-10 for smoother signals that update less frequently. Higher intervals reduce market noise and false signals but introduce slightly more lag. This is particularly useful on volatile timeframes where you want the EMA's directional bias without every minor price fluctuation affecting the calculation.
Perfect for swing traders who prefer cleaner, more stable trend lines over hyper-responsive indicators.
Conclusion
The Infinite EMA transforms the traditional EMA from a fixed-period tool into a precision instrument with unlimited flexibility. By understanding the Alpha-Period relationship, traders can create custom EMAs that perfectly match their trading style, timeframe, and market conditions.
The "infinite" nature comes from the ability to set any period imaginable - from ultra-fast 2-bar EMAs to glacially slow 10-million-bar EMAs, all controlled through a single Alpha parameter.
________________________________________
Whether you're a beginner looking for simple trend following or a professional researcher analyzing century-long patterns, Infinite EMA adapts to your needs. The power of infinite periods is now in your hands! 🚀
Go forward to the horizon. When you reach it, a new one will open up.
- J. P. Morgan
Shock Detector: Price Jerk with Std-Dev BandsDetect sudden shocks in market behaviour
This indicator measures the jerk of price – the third derivative of price with respect to time (rate of change of acceleration). It highlights sudden accelerations and decelerations in price movement that are often invisible with standard momentum or volatility indicators.
Per-bar or time-scaled derivatives (choose whether calculations are based on bars or actual seconds).
Features
Log-price option for more stable readings across different price levels.
Optional smoothing with EMA to reduce noise.
Line or column view for flexible visualization.
Standard deviation bands (±1σ and ±2σ), centered either on zero or the rolling mean.
Auto window selection (1 day to 4 weeks), adaptive to chart timeframe.
Color-coded jerk: green for positive, red for negative.
Optional filled bands for easy visual context of normal vs. extreme jerk moves.
How to Use
Use jerk to identify sudden shifts in market dynamics, where price movement is not just changing direction but changing its acceleration.
Bands help highlight when jerk values are statistically unusual compared to recent history.
Combine with trend or momentum indicators for potential early warning of breakouts, reversals, or exhaustion.
Why it’s useful
Most indicators measure price, velocity (returns), or acceleration (momentum). This goes one step further to look at jerk, giving you a tool to spot “shock” movements in the market. By framing jerk within standard deviation bands, it’s easy to see whether current moves are ordinary or exceptional.
Developed with the assistance of ChatGPT (OpenAI).
Close Above/Below Prev 2 Candle Strategy (Any Timeframe)Title: Close Above/Below Previous 2 Candle Strategy (Any Timeframe)
Description:
This strategy identifies potential breakout and trend continuation signals by analyzing the closing price relative to the highs and lows of the previous two candles. It works on any chart timeframe, making it versatile for intraday, swing, and daily trading.
How it works:
Long Entry (Bullish Signal): Triggered when the current candle closes above the highs of the previous two candles.
Short Entry (Bearish Signal): Triggered when the current candle closes below the lows of the previous two candles.
Visual Indicators:
Green triangles above the bar indicate bullish signals.
Red triangles below the bar indicate bearish signals.
Strategy Features:
Works on any timeframe, from 1-minute charts to daily/weekly charts.
Configurable risk/reward ratio for automatic stop-loss and take-profit levels.
Alerts trigger immediately when the condition is met, helping traders react to potential breakouts.
Provides clean visual signals for easy chart reading and decision-making.
Benefits:
Reduces noise by focusing on candle close confirmations.
Versatile and suitable for intraday, swing, and long-term trading.
Easy to combine with other indicators or strategies.
Volume Based Analysis V 1.00
Volume Based Analysis V1.00 – Multi-Scenario Buyer/Seller Power & Volume Pressure Indicator
Description:
1. Overview
The Volume Based Analysis V1.00 indicator is a comprehensive tool for analyzing market dynamics using Buyer Power, Seller Power, and Volume Pressure scenarios. It detects 12 configurable scenarios combining volume-based calculations with price action to highlight potential bullish or bearish conditions.
When used in conjunction with other technical tools such as Ichimoku, Bollinger Bands, and trendline analysis, traders can gain a deeper and more reliable understanding of the market context surrounding each signal.
2. Key Features
12 Configurable Scenarios covering Buyer/Seller Power convergence, divergence, and dominance
Advanced Volume Pressure Analysis detecting when both buy/sell volumes exceed averages
Global Lookback System ensuring consistency across all calculations
Dominance Peak Module for identifying strongest buyer/seller dominance at structural pivots
Real-time Signal Statistics Table showing bullish/bearish counts and volume metrics
Fully customizable inputs (SMA lengths, multipliers, timeframes)
Visual chart markers (S01 to S12) for clear on-chart identification
3. Usage Guide
Enable/Disable Scenarios: Choose which signals to display based on your trading strategy
Fine-tune Parameters: Adjust SMA lengths, multipliers, and lookback periods to fit your market and timeframe
Timeframe Control: Use custom lower timeframes for refined up/down volume calculations
Combine with Other Indicators:
Ichimoku: Confirm volume-based bullish signals with cloud breakouts or trend confirmation
Bollinger Bands: Validate divergence/convergence signals with overbought/oversold zones
Trendlines: Spot high-probability signals at breakout or retest points
Signal Tables & Peaks: Read buy/sell volume dominance at a glance, and activate the Dominance Peak Module to highlight key turning points.
4. Example Scenarios & Suggested Images
Image #1 – S01 Bullish Convergence Above Zero
S01 activated, Buyer Power > 0, both buyer power slope & price slope positive, above-average buy volume. Show S01 ↑ marker below bar.
Image #2 – Combined with Ichimoku
Display a bullish scenario where price breaks above Ichimoku cloud while S01 or S09 bullish signal is active. Highlight both the volume-based marker and Ichimoku cloud breakout.
Image #3 – Combined with Bollinger Bands & Trendlines
Show a bearish S10 signal at the upper Bollinger Band near a descending trendline resistance. Highlight the confluence of the volume pressure signal with the band touch and trendline rejection.
Image #4 – Dominance Peak Module
Pivot low with green ▲ Bull Peak and pivot high with red ▼ Bear Peak, showing strong dominance counts.
Image #5 – Statistics Table in Action
Bottom-left table showing buy/sell volume, averages, and bullish/bearish counts during an active market phase.
5. Feedback & Collaboration
Your feedback and suggestions are welcome — they help improve and refine this system. If you discover interesting use cases or have ideas for new features, please share them in the script’s comments section on TradingView.
6. Disclaimer
This script is for educational purposes only. It is not financial advice. Past performance does not guarantee future results. Always do your own analysis before making trading decisions.
Tip: Use this tool alongside trend confirmation indicators for the most robust signal interpretation.
caracalla ema long short signal📌 Indicator Name
caracalla ema long short signal
This script generates long and short trading signals using multiple technical indicators: EMAs, MACD, RSI, Stochastic, and volume.
🔧 Indicators Used
1. Exponential Moving Averages (EMA)
ema5, ema20, ema60, ema120 — used to determine overall trend direction.
2. Trend Confirmation (MA Alignment)
Bullish alignment: ema5 > ema20 > ema60 > ema120
Bearish alignment: ema5 < ema20 < ema60 < ema120
3. Crossover Signals
Golden Cross: ema5 crosses above ema20
Dead Cross: ema5 crosses below ema20
4. MACD
Standard parameters: 12, 26, 9
MACD Long: MACD line crosses above signal line
MACD Short: MACD line crosses below signal line
5. RSI & Stochastic
RSI(14): checks momentum
Stochastic (%K, %D)
Bullish: RSI > 50 and Stochastic %K crosses above %D
Bearish: RSI < 50 and Stochastic %K crosses below %D
6. Volume Filter
20-period simple average volume
Volume Up: Current volume > 120% of average
Volume Down: Current volume < 80% of average
✅ Signal Logic
📈 Long Signal (longSignal)
Triggered when 3 or more of the following are true:
EMA bullish alignment
Golden cross
MACD bullish crossover
RSI > 50 and Stochastic bullish crossover
High volume
📉 Short Signal (shortSignal)
Triggered when 3 or more of the following are true:
EMA bearish alignment
Dead cross
MACD bearish crossover
RSI < 50 and Stochastic bearish crossover
Low volume
📊 Visual Elements
Long Signal: Green “롱” label below the candle
Short Signal: Red “숏” label above the candle
EMA Lines:
EMA5 (Blue)
EMA20 (Orange)
EMA60 (Green)
EMA120 (Red)
Ease of Movement Z-Score Trend | DextraGeneral Description:
The "Ease of Movement Z-Score Trend | Dextra" (EOM-Z Trend) is an innovative technical analysis tool that combines the Ease of Movement (EOM) concept with Z-Score to measure how easily price moves relative to volume, while identifying market trends with intuitive visualization. This indicator is designed to help traders detect uptrend and downtrend phases with precision, enhanced by candle coloring for direct trend representation on the chart.
Key Features
Ease of Movement (EOM): Measures how easily price moves based on the change in the midpoint price and volume, normalized with Z-Score for statistical analysis.
Z-Score Normalization: Provides an indication of deviations from the mean, enabling the identification of overbought or oversold conditions.
Adjustable Thresholds: Users can customize upper and lower thresholds to define trend boundaries.
Candle Coloring: Visual trend representation with green (uptrend), red (downtrend), and gray (neutral) candles.
Flexibility: Adjustable for different timeframes and assets.
How It Works
The indicator operates through the following steps:
EOM Calculation:
hl2 = (high + low) / 2: Calculates the average midpoint price per bar.
eom = ta.sma(10000 * ta.change(hl2) * (high - low) / volume, length): EOM is computed as the smoothed average of the price midpoint change multiplied by the price range per unit volume, scaled by 10,000, over length bars (default 20).
Z-Score Calculation:
mean_eom = ta.sma(eom, z_length): Average EOM over z_length bars (default 93).
std_dev_eom = ta.stdev(eom, z_length): Standard deviation of EOM.
z_score = (eom - mean_eom) / std_dev_eom: Z-Score indicating how far EOM deviates from its mean in standard deviation units.
Trend Detection:
upperthreshold (default 1.03) and lowerthreshold (default -1.63): Thresholds to classify uptrend (if Z-Score > upperthreshold) and downtrend (if Z-Score < lowerthreshold).
eom_is_up and eom_is_down: Logical variables for trend status.
Visualization:
plot(z_score, ...): Z-Score line plotted with green (uptrend), red (downtrend), or gray (neutral) coloring.
plotcandle(...): Candles colored green, red, or gray based on trend.
hline(...): Dashed lines marking the thresholds.
Input Settings
EOM Length (default 20): Period for calculating EOM, determining sensitivity to price changes.
Z-Score Lookback Period (default 93): Period for calculating the Z-Score mean and standard deviation.
Uptrend Threshold (default 1.03): Minimum Z-Score value to classify an uptrend.
Downtrend Threshold (default -1.93): Maximum Z-Score value to classify a downtrend.
How to Use
Installation: Add the indicator via the "Indicators" menu in TradingView and search for "EOM-Z Trend | Dextra".
Customization:
Adjust EOM Length and Z-Score Lookback Period based on the timeframe (e.g., 20 and 93 for daily timeframes).
Set Uptrend Threshold and Downtrend Threshold according to preference or asset characteristics (e.g., lower to 0.8 and -1.5 for volatile markets).
Interpretation:
Uptrend (Green): Z-Score above upperthreshold, indicating strong upward price movement.
Downtrend (Red): Z-Score below lowerthreshold, indicating significant downward movement.
Neutral (Gray): Conditions between thresholds, suggesting a sideways market.
Use candle coloring as the primary visual guide, combined with the Z-Score line for confirmation.
Advantages
Intuitive Visualization: Candle coloring simplifies trend identification without deep analysis.
Flexibility: Customizable parameters allow adaptation to various markets.
Statistical Analysis: Z-Score provides a robust perspective on price deviations from the norm.
No Repainting: The indicator uses historical data and does not alter values after a bar closes.
Limitations
Volume Dependency: Requires accurate volume data; an error occurs if volume is unavailable.
Market Context: Effectiveness depends on properly tuned thresholds for specific assets.
Lack of Additional Signals: No built-in alerts or supplementary confirmation indicators.
Recommendations
Ideal Timeframe: Daily (1D) or (2D) for stable trends.
Combination: Pair with others indicators for signal validation.
Optimization: Test thresholds on historical data of the traded asset for optimal results.
Important Notes
This indicator relies entirely on internal TradingView data (high, low, close, volume) and does not integrate on-chain data. Ensure your data provider supports volume to avoid errors. This version (1.0) is the initial release, with potential future updates including features like alerts or multi-timeframe analysis.
Volume Data Table (Real-time & Historical Volume Analysis)Volume Data Table (Real-time & Historical Volume Analysis)
Overview:
The Volume Data Table indicator is a powerful tool designed to provide concise, real-time, and historical volume insights directly on your chart. It aggregates critical volume metrics into an organized, customizable table, making it incredibly easy to identify unusual volume activity, sudden surges, or sustained interest in a particular asset.
This indicator is perfect for traders who rely on volume analysis to confirm price movements, spot potential reversals, or gauge market conviction.
Key Features & How It Works:
Real-time Volume Metrics:
The table prominently displays the volume data for the current (last) candle, including:
Time: The precise time of the current candle's close, formatted in IST (Indian Standard Time - UTC+5:30) for your convenience.
Volume: The total volume for the current candle, smartly formatted in K (Thousands) or M (Millions) for readability.
Change % (Chg%): The percentage change in volume compared to the immediately preceding candle. This helps you quickly spot sudden increases or decreases in trading activity.
Vs 4-Avg % (vs4Avg%): The percentage change in volume compared to the average volume of the last 4 preceding candles. This is crucial for identifying volume surges or drops relative to recent historical activity, which can signal significant market events.
Configurable Historical Data:
Beyond the current candle, you can customize how many previous candles' volume data you wish to display. A simple input setting allows you to choose from 1 to 20 historical rows, giving you flexibility to review recent volume trends. Each historical row also provides its own "Change %" and "Vs 4-Avg %" for detailed analysis of past candle activity.
Intuitive Color-Coding:
Percentage change values are intuitively color-coded for instant visual cues:
Green: Indicates a positive (increase) in volume percentage.
Red: Indicates a negative (decrease) in volume percentage.
Clean & Organized Table Display:
The indicator presents all this data in a neat, easy-to-read table positioned at the top-right of your chart. The table automatically adjusts its height based on the number of historical rows you choose, ensuring a compact and efficient use of screen space.
Ideal Use Cases:
Volume Confirmation: Quickly confirm the conviction behind price movements. A strong price move on high "Vs 4-Avg %" volume often indicates higher reliability.
Spotting Abnormal Volume: Identify candles with unusually high or low volume compared to their recent average, which can precede or accompany significant price action.
Momentum Analysis: Understand if buying/selling pressure is increasing or decreasing over recent periods.
Scalping & Day Trading: The real-time updates and concise format make it highly effective for fast-paced short-term decision-making.
Complements Other Indicators: Use it alongside price action, candlestick patterns, or other technical indicators for a more robust analysis.
Customization Options:
Number of Historical Rows: Adjust Number of Historical Rows from 1 to 20 to tailor the depth of your historical volume review.
Important Disclaimer:
This indicator is a technical analysis tool and should be used as part of a comprehensive trading strategy. It is not financial advice. Trading in financial markets involves substantial risk, and you could lose money. Always perform your own research and risk management.
Step Channel Momentum Trend [ChartPrime]OVERVIEW
Step Channel Momentum Trend is a momentum-based price filtering system that adapts to market structure using pivot levels and ATR volatility. It builds a dynamic channel around a stepwise midline derived from swing highs and lows. The system colors price candles based on whether price remains inside this channel (low momentum) or breaks out (strong directional flow). This allows traders to clearly distinguish ranging conditions from trending ones and take action accordingly.
⯁ STRUCTURAL MIDLNE (STEP CHANNEL CORE)
The midline acts as the backbone of the trend system and is based on structure rather than smoothing.
Calculated as the average of the most recent confirmed Pivot High and Pivot Low.
The result is a step-like horizontal line that only updates when new pivot points are confirmed.
This design avoids lag and makes the line "snap" to recent structural shifts.
It reflects the equilibrium level between recent bullish and bearish control.
This unique step logic creates clear regime shifts and prevents noise from distorting trend interpretation.
⯁ DYNAMIC VOLATILITY BANDS (ATR FILTERING)
To detect momentum strength, the script constructs upper and lower bands using the ATR (Average True Range):
The distance from the midline is determined by ATR × multiplier (default: 200-period ATR × 0.6).
These bands adjust dynamically to volatility, expanding in high-ATR environments and contracting in calm markets.
The area between upper and lower bands represents a neutral or ranging market state.
Breakouts outside the bands are treated as significant momentum shifts.
This filtering approach ensures that only meaningful breakouts are visually emphasized — not every candle fluctuation.
⯁ MOMENTUM-BASED CANDLE COLORING
The system visually transforms price candles into momentum indicators:
When price (hl2) is above the upper band, candles are green → bullish momentum.
When price is below the lower band, candles are red → bearish momentum.
When price is between the bands, candles are orange → low or no momentum (range).
The candle body, wick, and border are all colored uniformly for visual clarity.
This gives traders instant feedback on when momentum is expanding or fading — ideal for breakout, pullback, or trend-following strategies.
⯁ PIVOT-BASED SWING ANCHORS
Each confirmed pivot is plotted as a label ⬥ directly on the chart:
They also serve as potential manual entry zones, SL/TP anchors, or confirmation points.
⯁ MOMENTUM STATE LABEL
To reinforce the current market mode, a live label is displayed at the most recent candle:
Displays either:
“ Momentum Up ” when price breaks above the upper band.
“ Momentum Down ” when price breaks below the lower band.
“ Range ” when price remains between the bands.
Label color matches the candle color for quick identification.
Automatically updates on each bar close.
This helps discretionary traders filter trades based on market phase.
USAGE
Use the green/red zones to enter with momentum and ride trending moves.
Use the orange zone to stay out or fade ranges.
The step midline can act as a breakout base, pullback anchor, or bias reference.
Combine with other indicators (e.g., order blocks, divergences, or volume) to build high-confluence systems.
CONCLUSION
Step Channel Momentum Trend gives traders a clean, adaptive framework for identifying trend direction, volatility-based breakouts, and ranging environments — all from structural logic and ATR responsiveness. Its stepwise midline provides clarity, while its dynamic color-coded candles make momentum shifts impossible to miss. Whether you’re scalping intraday momentum or managing swing entries, this tool helps you trade with the market’s rhythm — not against it.
light_logLight Log - A Defensive Programming Library for Pine Script
Overview
The Light Log library transforms Pine Script development by introducing structured logging and defensive programming patterns typically found in enterprise languages like C#. This library addresses a fundamental challenge in Pine Script: the lack of sophisticated error handling and debugging tools that developers expect when building complex trading systems.
At its core, Light Log provides three transformative capabilities that work together to create more reliable and maintainable code. First, it wraps all native Pine Script types in error-aware containers, allowing values to carry validation state alongside their data. Second, it offers a comprehensive logging system with severity levels and conditional rendering. Third, it includes defensive programming utilities that catch errors early and make code self-documenting.
The Philosophy of Errors as Values
Traditional Pine Script error handling relies on runtime errors that halt execution, making it difficult to build resilient systems that can gracefully handle edge cases. Light Log introduces a paradigm shift by treating errors as first-class values that flow through your program alongside regular data.
When you wrap a value using Light Log's type system, you're not just storing data – you're creating a container that can carry both the value and its validation state. For example, when you call myNumber.INT() , you receive an INT object that contains both the integer value and a Log object that can describe any issues with that value. This approach, inspired by functional programming languages, allows errors to propagate through calculations without causing immediate failures.
Consider how this changes error handling in practice. Instead of a calculation failing catastrophically when it encounters invalid input, it can produce a result object that contains both the computed value (which might be na) and a detailed log explaining what went wrong. Subsequent operations can check has_error() to decide whether to proceed or handle the error condition gracefully.
The Typed Wrapper System
Light Log provides typed wrappers for every native Pine Script type: INT, FLOAT, BOOL, STRING, COLOR, LINE, LABEL, BOX, TABLE, CHART_POINT, POLYLINE, and LINEFILL. These wrappers serve multiple purposes beyond simple value storage.
Each wrapper type contains two fields: the value field v holds the actual data, while the error field e contains a Log object that tracks the value's validation state. This dual nature enables powerful programming patterns. You can perform operations on wrapped values and accumulate error information along the way, creating an audit trail of how values were processed.
The wrapper system includes convenient methods for converting between wrapped and unwrapped values. The extension methods like INT() , FLOAT() , etc., make it easy to wrap existing values, while the from_INT() , from_FLOAT() methods extract the underlying values when needed. The has_error() method provides a consistent interface for checking whether any wrapped value has encountered issues during processing.
The Log Object: Your Debugging Companion
The Log object represents the heart of Light Log's debugging capabilities. Unlike simple string concatenation for error messages, the Log object provides a structured approach to building, modifying, and rendering diagnostic information.
Each Log object carries three essential pieces of information: an error type (info, warning, error, or runtime_error), a message string that can be built incrementally, and an active flag that controls conditional rendering. This structure enables sophisticated logging patterns where you can build up detailed diagnostic information throughout your script's execution and decide later whether and how to display it.
The Log object's methods support fluent chaining, allowing you to build complex messages in a readable way. The write() and write_line() methods append text to the log, while new_line() adds formatting. The clear() method resets the log for reuse, and the rendering methods ( render_now() , render_condition() , and the general render() ) control when and how messages appear.
Defensive Programming Made Easy
Light Log's argument validation functions transform how you write defensive code. Instead of cluttering your functions with verbose validation logic, you can use concise, self-documenting calls that make your intentions clear.
The argument_error() function provides strict validation that halts execution when conditions aren't met – perfect for catching programming errors early. For less critical issues, argument_log_warning() and argument_log_error() record problems without stopping execution, while argument_log_info() provides debug visibility into your function's behavior.
These functions follow a consistent pattern: they take a condition to check, the function name, the argument name, and a descriptive message. This consistency makes error messages predictable and helpful, automatically formatting them to show exactly where problems occurred.
Building Modular, Reusable Code
Light Log encourages a modular approach to Pine Script development by providing tools that make functions more self-contained and reliable. When functions validate their inputs and return wrapped values with error information, they become true black boxes that can be safely composed into larger systems.
The void_return() function addresses Pine Script's requirement that all code paths return a value, even in error handling branches. This utility function provides a clean way to satisfy the compiler while making it clear that a particular code path should never execute.
The static log pattern, initialized with init_static_log() , enables module-wide error tracking. You can create a persistent Log object that accumulates information across multiple function calls, building a comprehensive diagnostic report that helps you understand complex behaviors in your indicators and strategies.
Real-World Applications
In practice, Light Log shines when building sophisticated trading systems. Imagine developing a complex indicator that processes multiple data streams, performs statistical calculations, and generates trading signals. With Light Log, each processing stage can validate its inputs, perform calculations, and pass along both results and diagnostic information.
For example, a moving average calculation might check that the period is positive, that sufficient data exists, and that the input series contains valid values. Instead of failing silently or throwing runtime errors, it can return a FLOAT object that contains either the calculated average or a detailed explanation of why the calculation couldn't be performed.
Strategy developers benefit even more from Light Log's capabilities. Complex entry and exit logic often involves multiple conditions that must all be satisfied. With Light Log, each condition check can contribute to a comprehensive log that explains exactly why a trade was or wasn't taken, making strategy debugging and optimization much more straightforward.
Performance Considerations
While Light Log adds a layer of abstraction over raw Pine Script values, its design minimizes performance impact. The wrapper objects are lightweight, containing only two fields. The logging operations only consume resources when actually rendered, and the conditional rendering system ensures that production code can run with logging disabled for maximum performance.
The library follows Pine Script best practices for performance, using appropriate data structures and avoiding unnecessary operations. The var keyword in init_static_log() ensures that persistent logs don't create new objects on every bar, maintaining efficiency even in real-time calculations.
Getting Started
Adopting Light Log in your Pine Script projects is straightforward. Import the library, wrap your critical values, add validation to your functions, and use Log objects to track important events. Start small by adding logging to a single function, then expand as you see the benefits of better error visibility and code organization.
Remember that Light Log is designed to grow with your needs. You can use as much or as little of its functionality as makes sense for your project. Even simple uses, like adding argument validation to key functions, can significantly improve code reliability and debugging ease.
Transform your Pine Script development experience with Light Log – because professional trading systems deserve professional development tools.
Light Log Technical Deep Dive: Advanced Patterns and Architecture
Understanding Errors as Values
The concept of "errors as values" represents a fundamental shift in how we think about error handling in Pine Script. In traditional Pine Script development, errors are events – they happen at a specific moment in time and immediately interrupt program flow. Light Log transforms errors into data – they become information that flows through your program just like any other value.
This transformation has profound implications. When errors are values, they can be stored, passed between functions, accumulated, transformed, and inspected. They become part of your program's data flow rather than exceptions to it. This approach, popularized by languages like Rust with its Result type and Haskell with its Either monad, brings functional programming's elegance to Pine Script.
Consider a practical example. Traditional Pine Script might calculate a momentum indicator like this:
momentum = close - close
If period is invalid or if there isn't enough historical data, this calculation might produce na or cause subtle bugs. With Light Log's approach:
calculate_momentum(src, period)=>
result = src.FLOAT()
if period <= 0
result.e.write("Invalid period: must be positive", true, ErrorType.error)
result.v := na
else if bar_index < period
result.e.write("Insufficient data: need " + str.tostring(period) + " bars", true, ErrorType.warning)
result.v := na
else
result.v := src - src
result.e.write("Momentum calculated successfully", false, ErrorType.info)
result
Now the function returns not just a value but a complete computational result that includes diagnostic information. Calling code can make intelligent decisions based on both the value and its associated metadata.
The Monad Pattern in Pine Script
While Pine Script lacks the type system features to implement true monads, Light Log brings monadic thinking to Pine Script development. The wrapped types (INT, FLOAT, etc.) act as computational contexts that carry both values and metadata through a series of transformations.
The key insight of monadic programming is that you can chain operations while automatically propagating context. In Light Log, this context is the error state. When you have a FLOAT that contains an error, operations on that FLOAT can check the error state and decide whether to proceed or propagate the error.
This pattern enables what functional programmers call "railway-oriented programming" – your code follows a success track when all is well but can switch to an error track when problems occur. Both tracks lead to the same destination (a result with error information), but they take different paths based on the validity of intermediate values.
Composable Error Handling
Light Log's design encourages composition – building complex functionality from simpler, well-tested components. Each component can validate its inputs, perform its calculation, and return a result with appropriate error information. Higher-level functions can then combine these results intelligently.
Consider building a complex trading signal from multiple indicators:
generate_signal(src, fast_period, slow_period, signal_period) =>
log = init_static_log(ErrorType.info)
// Calculate components with error tracking
fast_ma = calculate_ma(src, fast_period)
slow_ma = calculate_ma(src, slow_period)
// Check for errors in components
if fast_ma.has_error()
log.write_line("Fast MA error: " + fast_ma.e.message, true)
if slow_ma.has_error()
log.write_line("Slow MA error: " + slow_ma.e.message, true)
// Proceed with calculation if no errors
signal = 0.0.FLOAT()
if not (fast_ma.has_error() or slow_ma.has_error())
macd_line = fast_ma.v - slow_ma.v
signal_line = calculate_ma(macd_line, signal_period)
if signal_line.has_error()
log.write_line("Signal line error: " + signal_line.e.message, true)
signal.e := log
else
signal.v := macd_line - signal_line.v
log.write("Signal generated successfully")
else
signal.e := log
signal.v := na
signal
This composable approach makes complex calculations more reliable and easier to debug. Each component is responsible for its own validation and error reporting, and the composite function orchestrates these components while maintaining comprehensive error tracking.
The Static Log Pattern
The init_static_log() function introduces a powerful pattern for maintaining state across function calls. In Pine Script, the var keyword creates variables that persist across bars but are initialized only once. Light Log leverages this to create logging objects that can accumulate information throughout a script's execution.
This pattern is particularly valuable for debugging complex strategies where you need to understand behavior across multiple bars. You can create module-level logs that track important events:
// Module-level diagnostic log
diagnostics = init_static_log(ErrorType.info)
// Track strategy decisions across bars
check_entry_conditions() =>
diagnostics.clear() // Start fresh each bar
diagnostics.write_line("Bar " + str.tostring(bar_index) + " analysis:")
if close > sma(close, 20)
diagnostics.write_line("Price above SMA20", false)
else
diagnostics.write_line("Price below SMA20 - no entry", true, ErrorType.warning)
if volume > sma(volume, 20) * 1.5
diagnostics.write_line("Volume surge detected", false)
else
diagnostics.write_line("Normal volume", false)
// Render diagnostics based on verbosity setting
if debug_mode
diagnostics.render_now()
Advanced Validation Patterns
Light Log's argument validation functions enable sophisticated precondition checking that goes beyond simple null checks. You can implement complex validation logic while keeping your code readable:
validate_price_data(open_val, high_val, low_val, close_val) =>
argument_error(na(open_val) or na(high_val) or na(low_val) or na(close_val),
"validate_price_data", "OHLC values", "contain na values")
argument_error(high_val < low_val,
"validate_price_data", "high/low", "high is less than low")
argument_error(close_val > high_val or close_val < low_val,
"validate_price_data", "close", "is outside high/low range")
argument_log_warning(high_val == low_val,
"validate_price_data", "high/low", "are equal (no range)")
This validation function documents its requirements clearly and fails fast with helpful error messages when assumptions are violated. The mix of errors (which halt execution) and warnings (which allow continuation) provides fine-grained control over how strict your validation should be.
Performance Optimization Strategies
While Light Log adds abstraction, careful design minimizes overhead. Understanding Pine Script's execution model helps you use Light Log efficiently.
Pine Script executes once per bar, so operations that seem expensive in traditional programming might have negligible impact. However, when building real-time systems, every optimization matters. Light Log provides several patterns for efficient use:
Lazy Evaluation: Log messages are only built when they'll be rendered. Use conditional logging to avoid string concatenation in production:
if debug_mode
log.write_line("Calculated value: " + str.tostring(complex_calculation))
Selective Wrapping: Not every value needs error tracking. Wrap values at API boundaries and critical calculation points, but use raw values for simple operations:
// Wrap at boundaries
input_price = close.FLOAT()
validated_period = validate_period(input_period).INT()
// Use raw values internally
sum = 0.0
for i = 0 to validated_period.v - 1
sum += close
Error Propagation: When errors occur early, avoid expensive calculations:
process_data(input) =>
validated = validate_input(input)
if validated.has_error()
validated // Return early with error
else
// Expensive processing only if valid
perform_complex_calculation(validated)
Integration Patterns
Light Log integrates smoothly with existing Pine Script code. You can adopt it incrementally, starting with critical functions and expanding coverage as needed.
Boundary Validation: Add Light Log at the boundaries of your system – where user input enters and where final outputs are produced. This catches most errors while minimizing changes to existing code.
Progressive Enhancement: Start by adding argument validation to existing functions. Then wrap return values. Finally, add comprehensive logging. Each step improves reliability without requiring a complete rewrite.
Testing and Debugging: Use Light Log's conditional rendering to create debug modes for your scripts. Production users see clean output while developers get detailed diagnostics:
// User input for debug mode
debug = input.bool(false, "Enable debug logging")
// Conditional diagnostic output
if debug
diagnostics.render_now()
else
diagnostics.render_condition() // Only shows errors/warnings
Future-Proofing Your Code
Light Log's patterns prepare your code for Pine Script's evolution. As Pine Script adds more sophisticated features, code that uses structured error handling and defensive programming will adapt more easily than code that relies on implicit assumptions.
The type wrapper system, in particular, positions your code to take advantage of potential future features or more sophisticated type inference. By thinking in terms of wrapped values and error propagation today, you're building code that will remain maintainable and extensible tomorrow.
Light Log doesn't just make your Pine Script better today – it prepares it for the trading systems you'll need to build tomorrow.
Library "light_log"
A lightweight logging and defensive programming library for Pine Script.
Designed for modular and extensible scripts, this utility provides structured runtime validation,
conditional logging, and reusable `Log` objects for centralized error propagation.
It also introduces a typed wrapping system for all native Pine values (e.g., `INT`, `FLOAT`, `LABEL`),
allowing values to carry errors alongside data. This enables functional-style flows with built-in
validation tracking, error detection (`has_error()`), and fluent chaining.
Inspired by structured logging patterns found in systems like C#, it reduces boilerplate,
enforces argument safety, and encourages clean, maintainable code architecture.
method INT(self, error_type)
Wraps an `int` value into an `INT` struct with an optional log severity.
Namespace types: series int, simple int, input int, const int
Parameters:
self (int) : The raw `int` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: An `INT` object containing the value and a default Log instance.
method FLOAT(self, error_type)
Wraps a `float` value into a `FLOAT` struct with an optional log severity.
Namespace types: series float, simple float, input float, const float
Parameters:
self (float) : The raw `float` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `FLOAT` object containing the value and a default Log instance.
method BOOL(self, error_type)
Wraps a `bool` value into a `BOOL` struct with an optional log severity.
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
self (bool) : The raw `bool` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `BOOL` object containing the value and a default Log instance.
method STRING(self, error_type)
Wraps a `string` value into a `STRING` struct with an optional log severity.
Namespace types: series string, simple string, input string, const string
Parameters:
self (string) : The raw `string` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `STRING` object containing the value and a default Log instance.
method COLOR(self, error_type)
Wraps a `color` value into a `COLOR` struct with an optional log severity.
Namespace types: series color, simple color, input color, const color
Parameters:
self (color) : The raw `color` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `COLOR` object containing the value and a default Log instance.
method LINE(self, error_type)
Wraps a `line` object into a `LINE` struct with an optional log severity.
Namespace types: series line
Parameters:
self (line) : The raw `line` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `LINE` object containing the value and a default Log instance.
method LABEL(self, error_type)
Wraps a `label` object into a `LABEL` struct with an optional log severity.
Namespace types: series label
Parameters:
self (label) : The raw `label` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `LABEL` object containing the value and a default Log instance.
method BOX(self, error_type)
Wraps a `box` object into a `BOX` struct with an optional log severity.
Namespace types: series box
Parameters:
self (box) : The raw `box` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `BOX` object containing the value and a default Log instance.
method TABLE(self, error_type)
Wraps a `table` object into a `TABLE` struct with an optional log severity.
Namespace types: series table
Parameters:
self (table) : The raw `table` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `TABLE` object containing the value and a default Log instance.
method CHART_POINT(self, error_type)
Wraps a `chart.point` value into a `CHART_POINT` struct with an optional log severity.
Namespace types: chart.point
Parameters:
self (chart.point) : The raw `chart.point` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `CHART_POINT` object containing the value and a default Log instance.
method POLYLINE(self, error_type)
Wraps a `polyline` object into a `POLYLINE` struct with an optional log severity.
Namespace types: series polyline, series polyline, series polyline, series polyline
Parameters:
self (polyline) : The raw `polyline` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `POLYLINE` object containing the value and a default Log instance.
method LINEFILL(self, error_type)
Wraps a `linefill` object into a `LINEFILL` struct with an optional log severity.
Namespace types: series linefill
Parameters:
self (linefill) : The raw `linefill` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `LINEFILL` object containing the value and a default Log instance.
method from_INT(self)
Extracts the integer value from an INT wrapper.
Namespace types: INT
Parameters:
self (INT) : The wrapped INT instance.
Returns: The underlying `int` value.
method from_FLOAT(self)
Extracts the float value from a FLOAT wrapper.
Namespace types: FLOAT
Parameters:
self (FLOAT) : The wrapped FLOAT instance.
Returns: The underlying `float` value.
method from_BOOL(self)
Extracts the boolean value from a BOOL wrapper.
Namespace types: BOOL
Parameters:
self (BOOL) : The wrapped BOOL instance.
Returns: The underlying `bool` value.
method from_STRING(self)
Extracts the string value from a STRING wrapper.
Namespace types: STRING
Parameters:
self (STRING) : The wrapped STRING instance.
Returns: The underlying `string` value.
method from_COLOR(self)
Extracts the color value from a COLOR wrapper.
Namespace types: COLOR
Parameters:
self (COLOR) : The wrapped COLOR instance.
Returns: The underlying `color` value.
method from_LINE(self)
Extracts the line object from a LINE wrapper.
Namespace types: LINE
Parameters:
self (LINE) : The wrapped LINE instance.
Returns: The underlying `line` object.
method from_LABEL(self)
Extracts the label object from a LABEL wrapper.
Namespace types: LABEL
Parameters:
self (LABEL) : The wrapped LABEL instance.
Returns: The underlying `label` object.
method from_BOX(self)
Extracts the box object from a BOX wrapper.
Namespace types: BOX
Parameters:
self (BOX) : The wrapped BOX instance.
Returns: The underlying `box` object.
method from_TABLE(self)
Extracts the table object from a TABLE wrapper.
Namespace types: TABLE
Parameters:
self (TABLE) : The wrapped TABLE instance.
Returns: The underlying `table` object.
method from_CHART_POINT(self)
Extracts the chart.point from a CHART_POINT wrapper.
Namespace types: CHART_POINT
Parameters:
self (CHART_POINT) : The wrapped CHART_POINT instance.
Returns: The underlying `chart.point` value.
method from_POLYLINE(self)
Extracts the polyline object from a POLYLINE wrapper.
Namespace types: POLYLINE
Parameters:
self (POLYLINE) : The wrapped POLYLINE instance.
Returns: The underlying `polyline` object.
method from_LINEFILL(self)
Extracts the linefill object from a LINEFILL wrapper.
Namespace types: LINEFILL
Parameters:
self (LINEFILL) : The wrapped LINEFILL instance.
Returns: The underlying `linefill` object.
method has_error(self)
Returns true if the INT wrapper has an active log entry.
Namespace types: INT
Parameters:
self (INT) : The INT instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the FLOAT wrapper has an active log entry.
Namespace types: FLOAT
Parameters:
self (FLOAT) : The FLOAT instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the BOOL wrapper has an active log entry.
Namespace types: BOOL
Parameters:
self (BOOL) : The BOOL instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the STRING wrapper has an active log entry.
Namespace types: STRING
Parameters:
self (STRING) : The STRING instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the COLOR wrapper has an active log entry.
Namespace types: COLOR
Parameters:
self (COLOR) : The COLOR instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the LINE wrapper has an active log entry.
Namespace types: LINE
Parameters:
self (LINE) : The LINE instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the LABEL wrapper has an active log entry.
Namespace types: LABEL
Parameters:
self (LABEL) : The LABEL instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the BOX wrapper has an active log entry.
Namespace types: BOX
Parameters:
self (BOX) : The BOX instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the TABLE wrapper has an active log entry.
Namespace types: TABLE
Parameters:
self (TABLE) : The TABLE instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the CHART_POINT wrapper has an active log entry.
Namespace types: CHART_POINT
Parameters:
self (CHART_POINT) : The CHART_POINT instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the POLYLINE wrapper has an active log entry.
Namespace types: POLYLINE
Parameters:
self (POLYLINE) : The POLYLINE instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the LINEFILL wrapper has an active log entry.
Namespace types: LINEFILL
Parameters:
self (LINEFILL) : The LINEFILL instance to check.
Returns: True if an error or message is active in the log.
void_return()
Utility function used when a return is syntactically required but functionally unnecessary.
Returns: Nothing. Function never executes its body.
argument_error(condition, function, argument, message)
Throws a runtime error when a condition is met. Used for strict argument validation.
Parameters:
condition (bool) : Boolean expression that triggers the runtime error.
function (string) : Name of the calling function (for formatting).
argument (string) : Name of the problematic argument.
message (string) : Description of the error cause.
Returns: Never returns. Halts execution if the condition is true.
argument_log_info(condition, function, argument, message)
Logs an informational message when a condition is met. Used for optional debug visibility.
Parameters:
condition (bool) : Boolean expression that triggers the log.
function (string) : Name of the calling function.
argument (string) : Argument name being referenced.
message (string) : Informational message to log.
Returns: Nothing. Logs if the condition is true.
argument_log_warning(condition, function, argument, message)
Logs a warning when a condition is met. Non-fatal but highlights potential issues.
Parameters:
condition (bool) : Boolean expression that triggers the warning.
function (string) : Name of the calling function.
argument (string) : Argument name being referenced.
message (string) : Warning message to log.
Returns: Nothing. Logs if the condition is true.
argument_log_error(condition, function, argument, message)
Logs an error message when a condition is met. Does not halt execution.
Parameters:
condition (bool) : Boolean expression that triggers the error log.
function (string) : Name of the calling function.
argument (string) : Argument name being referenced.
message (string) : Error message to log.
Returns: Nothing. Logs if the condition is true.
init_static_log(error_type, message, active)
Initializes a persistent (var) Log object. Ideal for global logging in scripts or modules.
Parameters:
error_type (series ErrorType) : Initial severity level (required).
message (string) : Optional starting message string. Default value of ("").
active (bool) : Whether the log should be flagged active on initialization. Default value of (false).
Returns: A static Log object with the given parameters.
method new_line(self)
Appends a newline character to the Log message. Useful for separating entries during chained writes.
Namespace types: Log
Parameters:
self (Log) : The Log instance to modify.
Returns: The updated Log object with a newline appended.
method write(self, message, flag_active, error_type)
Appends a message to a Log object without a newline. Updates severity and active state if specified.
Namespace types: Log
Parameters:
self (Log) : The Log instance being modified.
message (string) : The text to append to the log.
flag_active (bool) : Whether to activate the log for conditional rendering. Default value of (false).
error_type (series ErrorType) : Optional override for the severity level. Default value of (na).
Returns: The updated Log object.
method write_line(self, message, flag_active, error_type)
Appends a message to a Log object, prefixed with a newline for clarity.
Namespace types: Log
Parameters:
self (Log) : The Log instance being modified.
message (string) : The text to append to the log.
flag_active (bool) : Whether to activate the log for conditional rendering. Default value of (false).
error_type (series ErrorType) : Optional override for the severity level. Default value of (na).
Returns: The updated Log object.
method clear(self, flag_active, error_type)
Clears a Log object’s message and optionally reactivates it. Can also update the error type.
Namespace types: Log
Parameters:
self (Log) : The Log instance being cleared.
flag_active (bool) : Whether to activate the log after clearing. Default value of (false).
error_type (series ErrorType) : Optional new error type to assign. If not provided, the previous type is retained. Default value of (na).
Returns: The cleared Log object.
method render_condition(self, flag_active, error_type)
Conditionally renders the log if it is active. Allows overriding error type and controlling active state afterward.
Namespace types: Log
Parameters:
self (Log) : The Log instance to evaluate and render.
flag_active (bool) : Whether to activate the log after rendering. Default value of (false).
error_type (series ErrorType) : Optional error type override. Useful for contextual formatting just before rendering. Default value of (na).
Returns: The updated Log object.
method render_now(self, flag_active, error_type)
Immediately renders the log regardless of `active` state. Allows overriding error type and active flag.
Namespace types: Log
Parameters:
self (Log) : The Log instance to render.
flag_active (bool) : Whether to activate the log after rendering. Default value of (false).
error_type (series ErrorType) : Optional error type override. Allows dynamic severity adjustment at render time. Default value of (na).
Returns: The updated Log object.
render(self, condition, flag_active, error_type)
Renders the log conditionally or unconditionally. Allows full control over render behavior.
Parameters:
self (Log) : The Log instance to render.
condition (bool) : If true, renders only if the log is active. If false, always renders. Default value of (false).
flag_active (bool) : Whether to activate the log after rendering. Default value of (false).
error_type (series ErrorType) : Optional error type override passed to the render methods. Default value of (na).
Returns: The updated Log object.
Log
A structured object used to store and render logging messages.
Fields:
error_type (series ErrorType) : The severity level of the message (from the ErrorType enum).
message (series string) : The text of the log message.
active (series bool) : Whether the log should trigger rendering when conditionally evaluated.
INT
A wrapped integer type with attached logging for validation or tracing.
Fields:
v (series int) : The underlying `int` value.
e (Log) : Optional log object describing validation status or error context.
FLOAT
A wrapped float type with attached logging for validation or tracing.
Fields:
v (series float) : The underlying `float` value.
e (Log) : Optional log object describing validation status or error context.
BOOL
A wrapped boolean type with attached logging for validation or tracing.
Fields:
v (series bool) : The underlying `bool` value.
e (Log) : Optional log object describing validation status or error context.
STRING
A wrapped string type with attached logging for validation or tracing.
Fields:
v (series string) : The underlying `string` value.
e (Log) : Optional log object describing validation status or error context.
COLOR
A wrapped color type with attached logging for validation or tracing.
Fields:
v (series color) : The underlying `color` value.
e (Log) : Optional log object describing validation status or error context.
LINE
A wrapped line object with attached logging for validation or tracing.
Fields:
v (series line) : The underlying `line` value.
e (Log) : Optional log object describing validation status or error context.
LABEL
A wrapped label object with attached logging for validation or tracing.
Fields:
v (series label) : The underlying `label` value.
e (Log) : Optional log object describing validation status or error context.
BOX
A wrapped box object with attached logging for validation or tracing.
Fields:
v (series box) : The underlying `box` value.
e (Log) : Optional log object describing validation status or error context.
TABLE
A wrapped table object with attached logging for validation or tracing.
Fields:
v (series table) : The underlying `table` value.
e (Log) : Optional log object describing validation status or error context.
CHART_POINT
A wrapped chart point with attached logging for validation or tracing.
Fields:
v (chart.point) : The underlying `chart.point` value.
e (Log) : Optional log object describing validation status or error context.
POLYLINE
A wrapped polyline object with attached logging for validation or tracing.
Fields:
v (series polyline) : The underlying `polyline` value.
e (Log) : Optional log object describing validation status or error context.
LINEFILL
A wrapped linefill object with attached logging for validation or tracing.
Fields:
v (series linefill) : The underlying `linefill` value.
e (Log) : Optional log object describing validation status or error context.
Approximate Entropy Zones [PhenLabs]Version: PineScript™ v6
Description
This indicator identifies periods of market complexity and randomness by calculating the Approximate Entropy (ApEn) of price action. As the movement of the market becomes complex, it means the current trend is losing steam and a reversal or consolidation is likely near. The indicator plots high-entropy periods as zones on your chart, providing a graphical suggestion to anticipate a potential market direction change. This indicator is designed to help traders identify favorable times to get in or out of a trade by highlighting when the market is in a state of disarray.
Points of Innovation
Advanced Complexity Analysis: Instead of relying on traditional momentum or trend indicators, this tool uses Approximate Entropy to quantify the unpredictability of price movements.
Dynamic Zone Creation: It automatically plots zones on the chart during periods of high entropy, providing a clear and intuitive visual guide.
Customizable Sensitivity: Users can fine-tune the ‘Entropy Threshold’ to adjust how frequently zones appear, allowing for calibration to different assets and timeframes.
Time-Based Zone Expiration: Zones can be set to expire after a specific time, keeping the chart clean and relevant.
Built-in Zone Size Filter: Excludes zones that form on excessively large candles, filtering out noise from extreme volatility events.
On-Chart Calibration Guide: A persistent note on the chart provides simple instructions for adjusting the entropy threshold, making it easy for users to optimize the indicator’s performance.
Core Components
Approximate Entropy (ApEn) Calculation: The core of the indicator, which measures the complexity or randomness of the price data.
Zone Plotting: Creates visual boxes on the chart when the calculated ApEn value exceeds a user-defined threshold.
Dynamic Zone Management: Manages the lifecycle of the zones, from creation to expiration, ensuring the chart remains uncluttered.
Customizable Settings: A comprehensive set of inputs that allow users to control the indicator’s sensitivity, appearance, and time-based behavior.
Key Features
Identifies Potential Reversals: The high-entropy zones can signal that a trend is nearing its end, giving traders an early warning.
Works on Any Timeframe: The indicator can be applied to any chart timeframe, from minutes to days.
Customizable Appearance: Users can change the color and transparency of the zones to match their chart’s theme.
Informative Labels: Each zone can display the calculated entropy value and the direction of the candle on which it formed.
Visualization
Entropy Zones: Shaded boxes that appear on the chart, highlighting candles with high complexity.
Zone Labels: Text within each zone that displays the ApEn value and a directional arrow (e.g., “0.525 ↑”).
Calibration Note: A small table in the top-right corner of the chart with instructions for adjusting the indicator’s sensitivity.
Usage Guidelines
Entropy Analysis
Source: The price data used for the ApEn calculation. (Default: close)
Lookback Length: The number of bars used in the ApEn calculation. (Default: 20, Range: 10-50)
Embedding Dimension (m): The length of patterns to be compared; a standard value for financial data. (Default: 2)
Tolerance Multiplier (r): Adjusts the tolerance for pattern matching; a larger value makes matching more lenient. (Default: 0.2)
Entropy Threshold: The ApEn value that must be exceeded to plot a zone. Increase this if too many zones appear; decrease it if too few appear. (Default: 0.525)
Time Settings
Analysis Timeframe: How long a zone remains on the chart after it forms. (Default: 1D)
Custom Period (Bars): The zone’s lifespan in bars if “Analysis Timeframe” is set to “Custom”. (Default: 1000)
Zone Settings
Zone Fill Color: The color of the entropy zones. (Default: #21f38a with 80% transparency)
Maximum Zone Size %: Filters out zones on candles that are larger than this percentage of their low price. (Default: 0.5)
Display Options
Show Entropy Label: Toggles the visibility of the text label inside each zone. (Default: true)
Label Text Position: The horizontal alignment of the text label. (Default: Right)
Show Calibration Note: Toggles the visibility of the calibration note in the corner of the chart. (Default: true)
Best Use Cases
Trend Reversal Trading: Identifying when a strong trend is likely to reverse or pause.
Breakout Confirmation: Using the absence of high entropy to confirm the strength of a breakout.
Ranging Market Identification: Periods of high entropy can indicate that a market is transitioning into a sideways or choppy phase.
Limitations
Not a Standalone Signal: This indicator should be used in conjunction with other forms of analysis to confirm trading signals.
Lagging Nature: Like all indicators based on historical data, ApEn is a lagging measure and does not predict future price movements with certainty.
Calibration Required: The effectiveness of the indicator is highly dependent on the “Entropy Threshold” setting, which needs to be adjusted for different assets and timeframes.
What Makes This Unique
Quantifies Complexity: It provides a numerical measure of market complexity, offering a different perspective than traditional indicators.
Clear Visual Cues: The zones make it easy to see when the market is in a state of high unpredictability.
User-Friendly Design: With features like the on-chart calibration note, the indicator is designed to be easy to use and optimize.
How It Works
Calculate Standard Deviation: The indicator first calculates the standard deviation of the source price data over a specified lookback period.
Calculate Phi: It then calculates a value called “phi” for two different pattern lengths (embedding dimensions ‘m’ and ‘m+1’). This involves comparing sequences of data points to see how many are “similar” within a certain tolerance (determined by the standard deviation and the ‘r’ multiplier).
Calculate ApEn: The Approximate Entropy is the difference between the two phi values. A higher ApEn value indicates greater irregularity and unpredictability in the data.
Plot Zones: If the calculated ApEn exceeds the user-defined ‘Entropy Threshold’, a zone is plotted on the chart.
Note: The “Entropy Threshold” is the most important setting to adjust. If you see too many zones, increase the threshold. If you see too few, decrease it.
ATR, ADX, RSI TableATR, ADX & RSI Dashboard (Color-Coded)
Overview
This indicator provides a clean, all-in-one dashboard that displays the current values for three of the most popular technical indicators: Average True Range (ATR), Average Directional Index (ADX), and Relative Strength Index (RSI).
To make analysis faster and more intuitive, the values in the table are dynamically color-coded based on key thresholds. This allows you to get an immediate visual summary of market volatility, trend strength, and momentum without cluttering your main chart area.
Features
The indicator displays a simple table in the bottom-right corner of your chart with the following color logic:
ATR (Volatility): Measures the average volatility of an asset.
Green: Low Volatility (ATR is less than 3% of the current price).
Orange: Moderate Volatility (ATR is between 3% and 5%).
Red: High Volatility (ATR is greater than 5%).
ADX (Trend Strength): Measures the strength of the underlying trend, regardless of its direction.
Red: Weak or Non-Trending Market (ADX is below 20).
Orange: Developing or Neutral Trend (ADX is between 20 and 25).
Green: Strong Trend (ADX is above 25).
RSI (Momentum): Measures the speed and change of price movements to identify overbought or oversold conditions.
Green: Potentially Oversold (RSI is below 40).
Orange: Neutral/Normal Conditions (RSI is between 40 and 70).
Red: Potentially Overbought (RSI is above 70).
How to Use
This tool is perfect for traders who want a quick, at-a-glance understanding of the current market state. Instead of analyzing three separate indicators, you can use this dashboard to:
Quickly confirm if a strong trend is present before entering a trade.
Assess volatility to adjust your stop-loss and take-profit levels.
Instantly spot potential overbought or oversold conditions.
Customization
All input lengths for the ATR, ADX, and RSI are fully customizable in the indicator's settings menu, allowing you to tailor the calculations to your specific trading style and timeframe.
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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• .
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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Money Risk Management with Trade Tracking
Overview
The Money Risk Management with Trade Tracking indicator is a powerful tool designed for traders on TradingView to simplify trade simulation and risk management. Unlike the TradingView Strategy Tester, which can be complex for beginners, this indicator provides an intuitive, beginner-friendly interface to evaluate trading strategies in a realistic manner, mirroring real-world trading conditions.
Built on the foundation of open-source contributions from LuxAlgo and TCP, this indicator integrates external indicator signals, overlays take-profit (TP) and stop-loss (SL) levels, and provides detailed money management analytics. It empowers traders to visualize potential profits, losses, and risk-reward ratios, making it easier to understand the financial outcomes of their strategies.
Key Features
Signal Integration: Seamlessly integrates with external long and short signals from other indicators, allowing traders to overlay TP/SL levels based on their preferred strategies.
Realistic Trade Simulation: Simulates trades as they would occur in real-world scenarios, accounting for initial capital, risk percentage, leverage, and compounding effects.
Money Management Dashboard: Displays critical metrics such as current capital, unrealized P&L, risk amount, potential profit, risk-reward ratio, and trade status in a customizable, beginner-friendly table.
TP/SL Visualization: Plots TP and SL levels on the chart with customizable styles (solid, dashed, dotted) and colors, along with optional labels for clarity.
Performance Tracking: Tracks total trades, win/loss counts, win rate, and profit factor, providing a clear overview of strategy performance.
Liquidation Risk Alerts: Warns traders if stop-loss levels risk liquidation based on leverage settings, enhancing risk awareness.
Benefits for Traders
Beginner-Friendly: Simplifies the complexities of the TradingView Strategy Tester, offering an intuitive interface for new traders to simulate and evaluate trades without confusion.
Real-World Insights: Helps traders understand the actual profit or loss potential of their strategies by factoring in capital, risk, and leverage, bridging the gap between theoretical backtesting and real-world execution.
Enhanced Decision-Making: Provides clear, real-time analytics on risk-reward ratios, unrealized P&L, and trade performance, enabling informed trading decisions.
Customizable and Flexible: Allows customization of TP/SL settings, table positions, colors, and sizes, catering to individual trader preferences.
Risk Management Focus: Encourages disciplined trading by highlighting risk amounts, potential profits, and liquidation risks, fostering better financial planning.
Why This Indicator Stands Out
Many traders struggle to translate backtested strategy results into real-world outcomes due to the abstract nature of percentage-based profitability metrics. This indicator addresses that challenge by providing a practical, user-friendly tool that simulates trades with real-world parameters like capital, leverage, and compounding. Its open-source nature ensures accessibility, while its integration with other indicators makes it versatile for various trading styles.
How to Use
Add to TradingView: Copy the Pine Script code into TradingView’s Pine Editor and add it to your chart.
Configure Inputs: Set your initial capital, risk percentage, leverage, and TP/SL values in the indicator settings. Select external long/short signal sources if integrating with other indicators.
Monitor Dashboards: Use the Money Management and Target Dashboard tables to track trade performance and risk metrics in real time.
Analyze Results: Review win rates, profit factors, and P&L to refine your trading strategy.
Credits
This indicator builds upon the open-source contributions of LuxAlgo and TCP , whose efforts in sharing their code have made this tool possible. Their dedication to the trading community is deeply appreciated.
3 Bar Reversal3 Bar Reversal
This pattern is described in John Carter's "Mastering the Trade"
The 3 Bar Reversal indicator is a simple but effective price action tool designed to highlight potential short-term reversals in market direction. It monitors consecutive bar behavior and identifies turning points based on a three-bar pattern. This tool can assist traders in spotting trend exhaustion or early signs of a reversal, particularly in scalping or short-term trading strategies.
How It Works
This indicator analyzes the relationship between consecutive bar closes:
It counts how many bars have passed since the price closed higher than the previous close (barssince(close >= close )) — referred to as an "up streak".
It also counts how many bars have passed since the price closed lower than the previous close (barssince(close <= close )) — known as a "down streak".
A reversal condition is met when:
There have been exactly 3 bars in a row moving in one direction (up or down), and
The 4th bar closes in the opposite direction.
When this condition is detected, the script performs two actions:
Plots a triangle on the chart to signal the potential reversal:
A green triangle below the bar for a possible long (buy) opportunity.
A red triangle above the bar for a possible short (sell) opportunity.
Triggers an alert condition so users can set notifications for when a reversal is detected.
Interpretation
Long Signal: The market has printed 3 consecutive lower closes, followed by a higher close — suggesting bullish momentum may be emerging.
Short Signal: The market has printed 3 consecutive higher closes, followed by a lower close — indicating possible bearish momentum.
These patterns are common in market retracements and can act as confirmation signals when used with other indicators such as RSI, MACD, support/resistance, or volume analysis.
Usage Examples
Scalping: Use the reversal signal to quickly enter short-term trades after a short-term exhaustion move.
Swing Trading: Combine this with trend indicators (e.g., moving averages) to time pullbacks within larger trends.
Confirmation Tool: Use this indicator alongside candlestick patterns or support/resistance zones to validate entry or exit points.
Alert Setup: Enable alerts based on the built-in alertcondition to receive instant notifications for potential trade setups.
Limitations
The 3-bar reversal logic does not guarantee a trend change; it signals potential reversals, which may need confirmation.
Best used in conjunction with broader context such as trend direction, market structure, or other technical indicators.
Supertrend with Volume Filter AlertSupertrend with Volume Filter Alert - Indicator Overview
What is the Supertrend Indicator?
The Supertrend indicator is a popular trend-following tool used by traders to identify the direction of the market and potential entry/exit points. It is based on the Average True Range (ATR), which measures volatility, and plots a line on the chart that acts as a dynamic support or resistance level. When the price is above the Supertrend line, it signals an uptrend (bullish), and when the price is below, it indicates a downtrend (bearish). The indicator is particularly effective in trending markets but can generate false signals during choppy or sideways conditions.
How This Script Works
The "Supertrend with Volume Filter Alert" enhances the classic Supertrend indicator by adding a customizable volume filter to improve signal reliability.
Here's how it functions:
Supertrend Calculation:The Supertrend is calculated using the ATR over a user-defined period (default: 55) and a multiplier (default: 1.85). These parameters control the sensitivity of the indicator:A higher ATR period smooths out volatility, making the indicator less reactive to short-term price fluctuations.The multiplier determines the distance of the Supertrend line from the price, affecting how quickly it responds to trend changes.The script plots the Supertrend line in cyan for uptrends and red for downtrends, making it easy to visualize the market direction.
Volume Filter:A key feature of this script is the volume filter, which helps filter out false signals in choppy markets. The filter compares the current volume to the average volume over a lookback period (default: 20) and only triggers signals if the volume exceeds the average by a specified multiplier (default: 2.0).This ensures that trend changes are accompanied by significant market participation, increasing the likelihood of a genuine trend shift.
Signals and Alerts:
Buy signals (cyan triangle below the bar) are generated when the price crosses above the Supertrend line (indicating an uptrend) and the volume condition is met.Sell signals (red triangle above the bar) are generated when the price crosses below the Supertrend line (indicating a downtrend) and the volume condition is met.Alerts are set up for both buy and sell signals, notifying traders only when the volume filter confirms the trend change.
Customizable Settings for Multiple Markets
The default settings in this script (ATR Period: 55, ATR Multiplier: 1.85, Volume Lookback Period: 20, Volume Multiplier: 2.0) were carefully chosen to provide a balance of sensitivity and reliability across various markets, including stocks, indices (like the S&P 500), forex, and cryptocurrencies.
Here's why these settings work well:
ATR Period (55): A longer ATR period smooths out volatility, making the indicator less prone to whipsaws in volatile markets like crypto or forex, while still being responsive enough for trending markets like indices.
ATR Multiplier (1.85): This multiplier strikes a balance between capturing early trend changes and avoiding noise. A smaller multiplier would make the indicator too sensitive, while a larger one might miss early opportunities.
Volume Lookback Period (20): A 20-bar lookback for volume averaging provides a robust baseline for identifying significant volume spikes, adaptable to both short-term (e.g., daily charts) and longer-term (e.g., weekly charts) timeframes.
Volume Multiplier (2.0): Requiring volume to be at least 2x the average ensures that only high-conviction moves trigger signals, which is crucial for markets with varying liquidity levels.
These parameters are fully customizable, allowing traders to adjust the indicator to their specific market, timeframe, or trading style. For example, you might reduce the ATR period for faster-moving markets or increase the volume multiplier for more conservative signal filtering.
How the Volume Filter Reduces Bad Trades in Choppy Markets
One of the main drawbacks of the Supertrend indicator is its tendency to generate false signals during choppy or ranging markets, where price fluctuates without a clear trend. The volume filter in this script addresses this issue by ensuring that trend changes are backed by significant market activity:
In choppy markets, price movements often lack strong volume, leading to false breakouts or reversals. By requiring volume to be a multiple (default: 2x) of the average volume over the lookback period, the script filters out these low-volume, low-conviction moves.This reduces the likelihood of taking bad trades during sideways markets, as only trend changes with strong volume confirmation will trigger signals. For example, on a daily chart of the S&P 500, a buy signal will only fire if the price crosses above the Supertrend line and the volume on that day is at least twice the 20-day average, indicating genuine buying pressure.
Usage Tips
Markets and Timeframes: This indicator is versatile and can be used on various assets (stocks, indices, forex, crypto) and timeframes (1-minute, 1-hour, daily, etc.). Adjust the settings based on the market's volatility and your trading strategy.
Combine with Other Indicators: While the volume filter improves reliability, consider using additional indicators like RSI or MACD to confirm trends, especially in ranging markets.
Backtesting: Test the indicator on historical data for your chosen market to optimize the settings and ensure they align with your trading goals.
Alerts: Set up alerts for buy and sell signals to stay informed of high-probability trend changes without constantly monitoring the chart.
ConclusionThe "Supertrend with Volume Filter Alert" is a powerful tool for trend-following traders, combining the simplicity of the Supertrend indicator with a volume-based filter to enhance signal accuracy. Its customizable settings make it adaptable to multiple markets, while the volume filter helps reduce false signals in choppy conditions, allowing traders to focus on high-probability trades. Whether you're trading stocks, indices, forex, or crypto, this indicator can help you identify trends with greater confidence.
Multi VWAPsMulti VWAPs Inspired by Biran Shannon and his book:
"MAXIMUM TRADING GAINS WITH ANCHORED VWAP . The Perfect Combination of Price, Time & Volume."
(ISBN 9798986868004)
A comprehensive VWAP (Volume Weighted Average Price) indicator that combines multiple timeframes and sessions in one view. Perfect for day trading and swing trading across different markets.
Features:
• Multiple VWAP Timeframes:
- Daily VWAP
- Weekly VWAP
- Monthly VWAP
- Quarterly VWAP
- Yearly VWAP
• Session-specific VWAPs:
- London Session (3:00 AM - 11:30 AM NY time)
- New York Session (9:30 AM - 4:00 PM NY time)
• Additional Indicators:
- Midnight Price Line (Previous day's closing price)
- 5-Day Moving Average
- 50-Day Moving Average
• Customization Options:
- Toggle individual VWAPs and indicators
- Customize colors for each component
- Adjustable label positioning
- MA smoothing settings
- Option to show/hide previous day's midnight price
• Smart Features:
- Auto-adjusting calculations based on timeframe
- Clear session boundaries
- Optimized for all chart timeframes
- Clean label system
Perfect for:
• Day traders tracking multiple timeframe momentum
• Swing traders using longer-term VWAPs
• Session traders focusing on London/NY hours
• Multi-timeframe analysis
• Price action trading with VWAP support/resistance
This indicator combines essential trading tools in one clean interface, helping you make informed decisions without cluttering your chart.
Multi-Timeframe Continuity Custom Candle ConfirmationMulti-Timeframe Continuity Custom Candle Confirmation
Overview
The Timeframe Continuity Indicator is a versatile tool designed to help traders identify alignment between their current chart’s candlestick direction and higher timeframes of their choice. By coloring bars on the current chart (e.g., 1-minute) based on the directional alignment with selected higher timeframes (e.g., 10-minute, daily), this indicator provides a visual cue for confirming trends across multiple timeframes—a concept known as Timeframe Continuity. This approach is particularly useful for day traders, swing traders, and scalpers looking to ensure their trades align with broader market trends, reducing the risk of trading against the prevailing momentum.
Originality and Usefulness
This indicator is an original creation, built from scratch to address a common challenge in trading: ensuring that price action on a lower timeframe aligns with the trend on higher timeframes. Unlike many trend-following indicators that rely on moving averages, oscillators, or other lagging metrics, this script directly compares the bullish or bearish direction of candlesticks across timeframes. It introduces the following unique features:
Customizable Timeframes: Users can select from a range of higher timeframes (5m, 10m, 15m, 30m, 1h, 2h, 4h, 1d, 1w, 1M) to check for alignment, making it adaptable to various trading styles.
Neutral Candle Handling: The script accounts for neutral candles (where close == open) on the current timeframe by allowing them to inherit the direction of the higher timeframe, ensuring continuity in trend visualization.
Table: A table displays the direction of each selected timeframe and the current timeframe, helping identify direction in the event you don't want to color bars.
Toggles for Flexibility: Options to disable bar coloring and the debug table allow users to customize the indicator’s visual output for cleaner charts or focused analysis.
This indicator is not a mashup of existing scripts but a purpose-built tool to visualize timeframe alignment directly through candlestick direction, offering traders a straightforward way to confirm trend consistency.
What It Does
The Timeframe Continuity Indicator colors bars on your chart when the direction of the current timeframe’s candlestick (bullish, bearish, or neutral) aligns with the direction of the selected higher timeframes:
Lime: The current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes (e.g., 10m) are bullish.
Pink: The current bar is bearish or neutral, and all selected higher timeframes are bearish.
Default Color: If the directions don’t align (e.g., 1m bar is bearish but 10m is bullish), the bar remains the default chart color.
The indicator also includes a debug table (toggleable) that shows the direction of each selected timeframe and the current timeframe, helping traders diagnose alignment issues.
How It Works
The script uses the following methodology:
1. Direction Calculation: For each timeframe (current and selected higher timeframes), the script determines the candlestick’s direction:
Bullish (1): close > open / Bearish (-1): close < open / Neutral (0): close == open
Higher timeframe directions are fetched using Pine Script’s request.security function, ensuring accurate data retrieval.
2. Alignment Check: The script checks if all selected higher timeframes are uniformly bullish (full_bullish) or bearish (full_bearish).
o A higher timeframe must have a clear direction (bullish or bearish) to trigger coloring. If any selected timeframe is neutral, alignment fails, and no coloring occurs.
3. Coloring Logic: The current bar is colored only if its direction aligns with the higher timeframes:
Lime if the higher timeframes are bullish and the current bar is bullish or neutral.
Maroon if the higher timeframes are bearish and the current bar is bearish or neutral.
If the current bar’s direction opposes the higher timeframe (e.g., 1m bearish, 10m bullish), the bar remains uncolored.
Users can disable bar coloring entirely via the settings, leaving bars in their default chart color.
4. Direction Table:
A table in the top-right corner (toggleable) displays the direction of each selected timeframe and the current timeframe, using color-coded labels (green for bullish, red for bearish, gray for neutral).
This feature helps traders understand why a bar is or isn’t colored, making the indicator accessible to users unfamiliar with Pine Script.
How to Use
1. Add the Indicator: Add the "Timeframe Continuity Indicator" to your chart in TradingView (e.g., a 1m chart of SPY).
2. Configure Settings:
Timeframe Selection: Check the boxes for the higher timeframes you want to compare against (default: 10m). Options include 5m, 10m, 15m, 30m, 1h, 2h, 4h, 1D, 1W, and 1M. Select multiple timeframes if you want to ensure alignment across all of them (e.g., 10m and 1d).
Enable Bar Coloring: Default: true (bars are colored lime or maroon when aligned). Set to false to disable coloring and keep the default chart colors.
Show Table: Default: true (table is displayed in the top-right corner). Set to false to hide the table for a cleaner chart.
3. Interpret the Output:
Colored Bars: Lime bars indicate the current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes are bullish. Maroon bars indicate the current bar is bearish or neutral, and all selected higher timeframes are bearish. Uncolored bars (default chart color) indicate a mismatch (e.g., 1m bar is bearish while 10m is bullish) or no coloring if disabled.
Direction Table: Check the table to see the direction of each selected timeframe and the current timeframe.
4. Example Use Case:
On a 1m chart of SPY, select the 10m timeframe.
If the 10m timeframe is bearish, 1m bars that are bearish or neutral will color maroon, confirming you’re trading with the higher timeframe’s trend.
If a 1m bar is bullish while the 10m is bearish, it remains uncolored, signaling a potential misalignment to avoid trading.
Underlying Concepts
The indicator is based on the concept of Timeframe Continuity, a strategy used by traders to ensure that price action on a lower timeframe aligns with the trend on higher timeframes. This reduces the risk of entering trades against the broader market direction. The script directly compares candlestick directions (bullish, bearish, or neutral) rather than relying on lagging indicators like moving averages or RSI, providing a real-time, price-action-based confirmation of trend alignment. The handling of neutral candles ensures that minor indecision on the lower timeframe doesn’t interrupt the visualization of the higher timeframe’s trend.
Why This Indicator?
Simplicity: Directly compares candlestick directions, avoiding complex calculations or lagging indicators.
Flexibility: Customizable timeframes and toggles cater to various trading strategies.
Transparency: The debug table makes the indicator’s logic accessible to all users, not just those who can read Pine Script.
Practicality: Helps traders confirm trend alignment, a key factor in successful trading across timeframes.
[blackcat] L3 Adaptive Trend SeekerOVERVIEW
The indicator is designed to help traders identify dynamic trends in various markets efficiently. It employs advanced calculations including Dynamic Moving Averages (DMAs) and multiple moving averages to filter out noise and provide clear buy/sell signals 📈✨. By utilizing innovative algorithms that adapt to changing market conditions, this tool enables users to make informed decisions across different timeframes and asset classes.
This versatile indicator serves both novice and experienced traders seeking reliable ways to navigate volatile environments. Its primary objective is to simplify complex trend analysis into actionable insights, making it an indispensable addition to any trader’s arsenal ⚙️🎯.
FEATURES
Customizable Dynamic Moving Average: Calculates an adaptive moving average tailored to specific needs using customizable coefficients.
Trend Identification: Utilizes multi-period moving averages (e.g., short-term, medium-term, long-term) to discern prevailing trends accurately.
Crossover Alerts: Provides visual cues via labels when significant crossover events occur between key indicators.
Adjusted MA Plots: Displays steplines colored according to the current trend direction (green for bullish, red for bearish).
Historical Price Analysis: Analyzes historical highs and lows over specified periods, ensuring robust trend identification.
Conditional Signals: Generates bullish/bearish conditions based on predefined rules enhancing decision-making efficiency.
HOW TO USE
Script Installation:
Copy the provided code and add it under Indicators > Add Custom Indicator within TradingView.
Choose an appropriate name and enable it on your desired charts.
Parameter Configuration:
Adjust the is_trend_seeker_active flag to activate/deactivate the core functionality as needed.
Modify other parameters such as smoothing factors if more customized behavior is required.
Interpreting Trends:
Observe the steppled lines representing the long-term/trend-adjusted moving averages:
Green indicates a bullish trend where prices are above the dynamically calculated threshold.
Red signifies a bearish environment with prices below respective levels.
Pay attention to labels marked "B" (for Bullish Crossover) and "S" (for Bearish Crossover).
Signal Integration:
Incorporate these generated signals within broader strategies involving support/resistance zones, volume data, and complementary indicators for stronger validity.
Use crossover alerts responsibly by validating them against recent market movements before execution.
Setting Up Alerts:
Configure alert notifications through TradingView’s interface corresponding to crucial crossover events ensuring timely responses.
Backtesting & Optimization:
Conduct extensive backtests applying diverse datasets spanning varied assets/types verifying robustness amidst differing conditions.
Refine parameters iteratively improving overall effectiveness and minimizing false positives/negatives.
EXAMPLE SCENARIOS
Swing Trading: Employ the stepline crossovers coupled with momentum oscillators like RSI to capitalize on intermediate trend reversals.
Day Trading: Leverage rapid adjustments offered by short-medium term MAs aligning entries/exits alongside intraday volatility metrics.
LIMITATIONS
The performance hinges upon accurate inputs; hence regular recalibration aligning shifting dynamics proves essential.
Excessive reliance solely on this indicator might lead to missed opportunities especially during sideways/choppy phases necessitating additional filters.
Always consider combining outputs with fundamental analyses ensuring holistic perspectives while managing risks effectively.
NOTES
Educational Resources: Delve deeper into principles behind dynamic moving averages and their significance in technical analysis bolstering comprehension.
Risk Management: Maintain stringent risk management protocols integrating stop-loss/profit targets safeguarding capital preservation.
Continuous Learning: Stay updated exploring evolving financial landscapes incorporating new methodologies enhancing script utility and relevance.
THANKS
Thanks to all contributors who have played vital roles refining and optimizing this script. Your valuable feedback drives continual enhancements paving way towards superior trading experiences!
Happy charting, and here's wishing you successful ventures ahead! 🌐💰!
Hamid Double RSIRSI with Moving Average and Another RSI
This script combines two Relative Strength Index (RSI) indicators with configurable moving averages. It allows traders to track momentum and market strength with adjustable periods for both the RSI and moving averages. The script also allows you to choose different data sources for each RSI, offering flexibility in analysis.
Features:
Two RSIs: One with a shorter period and another with a longer period .
Moving Averages: Each RSI has its own configurable moving average . The moving averages help smooth out the RSI and provide clearer trends.
Customizable Inputs: Adjust the RSI period and the length of the moving averages. You can also choose different sources for each RSI (e.g., close, open, high, low).
Mid Line: A horizontal line at 50, which is commonly used as the neutral level for the RSI. It helps identify whether the RSI is above or below neutral, indicating bullish or bearish conditions.
Overbought and Oversold Levels: Horizontal lines at 70 (overbought) and 30 (oversold) to highlight when the asset might be overbought or oversold according to the RSI.
How it works:
RSI Calculation: The script calculates two RSIs using different lengths
Moving Averages: A Simple Moving Average (SMA) is applied to both RSIs to smooth their values and help identify trends.
Overbought/Oversold Indicators: The script includes horizontal lines at 70 and 30 to show overbought and oversold conditions. The mid line is plotted at 50 to highlight neutral levels.
This indicator is useful for traders who want to compare the behavior of two RSIs over different time periods and use the moving averages to filter out noise. The ability to customize the source data for each RSI makes this script adaptable to different trading strategies.
Market Phases (ZigZag + MA + RSI)This script is a TradingView Pine Script that visualizes market phases using the ZigZag pattern, Moving Averages (MA), and the Relative Strength Index (RSI). It allows traders to identify key market conditions, such as accumulating, distributing, bullish, and bearish phases based on price movements and momentum indicators.
#### Components
1. ZigZag Settings:
- Depth: Controls the sensitivity of the ZigZag indicator. A higher value results in fewer price points being considered as reversals.
- Deviation: Defines the minimum percentage change needed to identify a ZigZag point, preventing small fluctuations from being registered.
- Backstep: Specifies the number of bars to look back for identifying highs and lows.
2. Moving Average Settings:
- MA Length: The number of periods used to calculate the moving average.
- MA Type: The type of moving average to use, either Simple Moving Average (SMA) or Exponential Moving Average (EMA).
3. RSI Settings:
- RSI Length: The period for calculating the RSI.
- Overbought Level: The threshold above which the asset is considered overbought.
- Oversold Level: The threshold below which the asset is considered oversold.
4. Calculations:
- Moving Average and RSI Calculation: The script calculates either an SMA or EMA and the RSI based on user-defined settings.
5. ZigZag Enhanced Calculation:
- It identifies swing highs and lows to determine the ZigZag points for improved trend analysis.
6. Trend Direction:
- The script checks the direction of the trend based on the latest ZigZag points.
7. Market Phase Determination:
- The script defines the market phase (Accumulation, Distribution, Bullish, Bearish) based on the trend direction and levels from the RSI and relationship with the moving average.
8. Background Colors:
- The background is tinted according to the identified market phase for visual clarity.
9. Labels and Plotting:
- Labels are generated at the last bar with the current phase and RSI value.
- The moving average and last ZigZag points are plotted on the chart for further reference.
### Conclusion
This script provides a comprehensive view of market conditions by integrating multiple indicators, helping traders make informed trading decisions based on market dynamics. The ability to visualize phases and key indicators aids in recognizing potential entry and exit points in trading strategies.
If you have any questions or need further modifications, feel free to ask!
Kase Permission StochasticOverview
The Kase Permission Stochastic indicator is an advanced momentum oscillator developed from Kase's trading methodology. It offers enhanced signal smoothing and filtering compared to traditional stochastic oscillators, providing clearer entry and exit signals with fewer false triggers.
How It Works
This indicator calculates a specialized stochastic using a multi-stage smoothing process:
Initial stochastic calculation based on high, low, and close prices
Application of weighted moving averages (WMA) for short-term smoothing
Progressive smoothing through differential factors
Final smoothing to reduce noise and highlight significant trend changes
The indicator oscillates between 0 and 100, with two main components:
Main Line (Green): The smoothed stochastic value
Signal Line (Yellow): A further smoothed version of the main line
Signal Generation
Trading signals are generated when the main line crosses the signal line:
Buy Signal (Green Triangle): When the main line crosses above the signal line
Sell Signal (Red Triangle): When the main line crosses below the signal line
Key Features
Multiple Smoothing Algorithms: Uses a combination of weighted and exponential moving averages for superior noise reduction
Clear Visualization: Color-coded lines and background filling
Reference Levels: Horizontal lines at 25, 50, and 75 for context
Customizable Colors: All visual elements can be color-customized
Customization Options
PST Length: Base period for the stochastic calculation (default: 9)
PST X: Multiplier for the lookback period (default: 5)
PST Smooth: Smoothing factor for progressive calculations (default: 3)
Smooth Period: Final smoothing period (default: 10)
Trading Applications
Trend Confirmation: Use crossovers to confirm entries in the direction of the prevailing trend
Reversal Detection: Identify potential market reversals when crossovers occur at extreme levels
Range-Bound Markets: Look for oscillations between overbought and oversold levels
Filter for Other Indicators: Use as a confirmation tool alongside other technical indicators
Best Practices
Most effective in trending markets or during well-defined ranges
Combine with price action analysis for better context
Consider the overall market environment before taking signals
Use longer settings for fewer but higher-quality signals
The Kase Permission Stochastic delivers a sophisticated approach to momentum analysis, offering a refined perspective on market conditions while filtering out much of the noise that affects standard oscillators.
[blackcat] L2 Gradient RSIVWAPOVERVIEW
The L2 Gradient RSIVWAP indicator offers traders a powerful tool for assessing market conditions by combining Relative Strength Index (RSI) with Volume Weighted Average Price (VWAP). It features dynamic coloring and clear buy/sell signals to enhance decision-making.
Customizable Inputs: Adjust key parameters such as RSI-VWAP length, oversold/overbought levels, and smoothing period.
Gradient Color Visualization: Provides intuitive gradient coloring to represent RSI-VWAP values.
Buy/Sell Indicators: On-chart labels highlight potential buying and selling opportunities.
Transparent Fills: Visually distinguishes overbought and oversold zones without obscuring other data.
Access the TradingView platform and select the chart where you wish to implement the indicator.
Go to “Indicators” in the toolbar and search for “ L2 Gradient RSIVWAP.”
Click “Add to Chart” to integrate the indicator into your chart.
Customize settings via the input options:
Toggle between standard RSI and RSI-based VWAP.
Set preferred lengths and thresholds for RSI-VWAP calculations.
Configure the smoothing period for ALMA.
Performance can vary based on asset characteristics like liquidity and volatility.
Historical backtests do not predict future market behavior accurately.
The ALMA function, developed by Arnaud Legoux, enhances response times relative to simple moving averages.
Buy and sell signals are derived from RSI-VWAP crossovers; consider additional factors before making trades.
Special thanks to Arnaud Legoux for creating the ALMA function.
