Exponential growthPurpose
The indicator plots an exponential curve based on historical price data and supports toggling between exponential regression and linear logarithmic regression. It also provides offset bands around the curve for additional insights.
Key Inputs
1. yxlogreg and dlogreg:
These are the "Endwert" (end value) and "Startwert" (start value) for calculating the slope of the logarithmic regression.
2. bars:
Specifies how many historical bars are considered in the calculation.
3.offsetchannel:
Adds an adjustable percentage-based offset to create upper and lower bands around the main exponential curve.
Default: 1 (interpreted as 10% bands).
4.lineareregression log.:
A toggle to switch between exponential function and linear logarithmic regression.
Default: false (exponential is used by default).
5.Dynamic Labels:
Creates a label showing the calculated regression values and historical bars count at the latest bar. The label is updated dynamically.
Use Cases
Exponential Growth Tracking:
Useful for assets or instruments exhibiting exponential growth trends.
Identifying Channels:
Helps identify support and resistance levels using the offset bands.
Switching Analysis Modes:
Flexibility to toggle between exponential and linear logarithmic analysis.
Recherche dans les scripts pour "curve"
2-Year - Fed Rate SpreadThe “2-Year - Fed Rate Spread” is a financial indicator that measures the difference between the 2-Year Treasury Yield and the Federal Funds Rate (Fed Funds Rate). This spread is often used as a gauge of market sentiment regarding the future direction of interest rates and economic conditions.
Calculation
• 2-Year Treasury Yield: This is the return on investment, expressed as a percentage, on the U.S. government’s debt obligations that mature in two years.
• Federal Funds Rate: The interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight.
The indicator calculates the spread by subtracting the Fed Funds Rate from the 2-Year Treasury Yield:
{2-Year - Fed Rate Spread} = {2-Year Treasury Yield} - {Fed Funds Rate}
Interpretation:
• Positive Spread: A positive spread (2-Year Treasury Yield > Fed Funds Rate) typically suggests that the market expects the Fed to raise rates in the future, indicating confidence in economic growth.
• Negative Spread: A negative spread (2-Year Treasury Yield < Fed Funds Rate) can indicate market expectations of a rate cut, often signaling concerns about an economic slowdown or recession. When the spread turns negative, the indicator’s background turns red, making it visually easy to identify these periods.
How to Use:
• Trend Analysis: Investors and analysts can use this spread to assess the market’s expectations for future monetary policy. A persistent negative spread may suggest a cautious approach to equity investments, as it often precedes economic downturns.
• Confirmation Tool: The spread can be used alongside other economic indicators, such as the yield curve, to confirm signals about the direction of interest rates and economic activity.
Research and Academic References:
The 2-Year - Fed Rate Spread is part of a broader analysis of yield spreads and their implications for economic forecasting. Several academic studies have examined the predictive power of yield spreads, including those that involve the 2-Year Treasury Yield and Fed Funds Rate:
1. Estrella, Arturo, and Frederic S. Mishkin (1998). “Predicting U.S. Recessions: Financial Variables as Leading Indicators.” The Review of Economics and Statistics, 80(1): 45-61.
• This study explores the predictive power of various financial variables, including yield spreads, in forecasting U.S. recessions. The authors find that the yield spread is a robust leading indicator of economic downturns.
2. Estrella, Arturo, and Gikas A. Hardouvelis (1991). “The Term Structure as a Predictor of Real Economic Activity.” The Journal of Finance, 46(2): 555-576.
• The paper examines the relationship between the term structure of interest rates (including short-term spreads like the 2-Year - Fed Rate) and future economic activity. The study finds that yield spreads are significant predictors of future economic performance.
3. Rudebusch, Glenn D., and John C. Williams (2009). “Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve.” Journal of Business & Economic Statistics, 27(4): 492-503.
• This research investigates why the yield curve, particularly spreads involving short-term rates like the 2-Year Treasury Yield, remains a powerful tool for forecasting recessions despite changes in monetary policy.
Conclusion:
The 2-Year - Fed Rate Spread is a valuable tool for market participants seeking to understand future interest rate movements and potential economic conditions. By monitoring the spread, especially when it turns negative, investors can gain insights into market sentiment and adjust their strategies accordingly. The academic research supports the use of such yield spreads as reliable indicators of future economic activity.
Dynamic Gradient Filter
Sigmoid Functions:
History and Mathematical Basis:
Sigmoid functions have a rich history in mathematics and are widely used in various fields, including statistics, machine learning, and signal processing.
The term "sigmoid" originates from the Greek words "sigma" (meaning "S-shaped") and "eidos" (meaning "form" or "type").
The sigmoid curve is characterized by its smooth S-shaped appearance, which allows it to map any real-valued input to a bounded output range, typically between 0 and 1.
The most common form of the sigmoid function is the logistic function:
Logistic Function (σ):
Defined as σ(x) = 1 / (1 + e^(-x)), where:
'x' is the input value,
'e' is Euler's number (approximately 2.71828).
This function was first introduced by Belgian mathematician Pierre François Verhulst in the 1830s to model population growth with limiting factors.
It gained popularity in the early 20th century when statisticians like Ronald Fisher began using it in regression analysis.
Specific Sigmoid Functions Used in the Indicator:
sig(val):
The 'sig' function in this indicator is a modified version of the logistic function, clamping a value between 0 and 1 on the sigmoid curve.
siga(val):
The 'siga' function adjusts values between -1 and 1 on the sigmoid curve, offering a centered variation of the sigmoid effect.
sigmoid(val):
The 'sigmoid' function provides a standard implementation of the logistic function, calculating the sigmoid value of the input data.
Adaptive Smoothing Factor:
The ' adaptiveSmoothingFactor(gradient, k)' function computes a dynamic smoothing factor for the filter based on the gradient of the price data and the user-defined sensitivity parameter 'k' .
Gradient:
The gradient represents the rate of change in price, calculated as the absolute difference between the current and previous close prices.
Sensitivity (k):
The 'k' parameter adjusts how quickly the filter reacts to changes in the gradient. Higher values of 'k' lead to a more responsive filter, while lower values result in smoother outputs.
Usage in the Indicator:
The "close" value refers to the closing price of each period in the chart's time frame
The indicator calculates the gradient by measuring the absolute difference between the current "close" price and the previous "close" price.
This gradient represents the strength or magnitude of the price movement within the chosen time frame.
The "close" value plays a pivotal role in determining the dynamic behavior of the "Dynamic Gradient Filter," as it directly influences the smoothing factor.
What Makes This Special:
The "Dynamic Gradient Filter" indicator stands out due to its adaptive nature and responsiveness to changing market conditions.
Dynamic Smoothing Factor:
The indicator's dynamic smoothing factor adjusts in real-time based on the rate of change in price (gradient) and the user-defined sensitivity '(k)' parameter.
This adaptability allows the filter to respond promptly to both minor fluctuations and significant price movements.
Smoothed Price Action:
The final output of the filter is a smoothed representation of the price action, aiding traders in identifying trends and potential reversals.
Customizable Sensitivity:
Traders can adjust the 'Sensitivity' parameter '(k)' to suit their preferred trading style, making the indicator versatile for various strategies.
Visual Clarity:
The plotted "Dynamic Gradient Filter" line on the chart provides a clear visual guide, enhancing the understanding of market dynamics.
Usage:
Traders and analysts can utilize the "Dynamic Gradient Filter" to:
Identify trends and reversals in price movements.
Filter out noise and highlight significant price changes.
Fine-tune trading strategies by adjusting the sensitivity parameter.
Enhance visual analysis with a dynamically adjusting filter line on the chart.
Literature:
en.wikipedia.org
medium.com
en.wikipedia.org
Machine Learning using Neural Networks | EducationalThe script provided is a comprehensive illustration of how to implement and execute a simplistic Neural Network (NN) on TradingView using PineScript.
It encompasses the entire workflow from data input, weight initialization, implicit neuron calculation, feedforward computation, backpropagation for weight adjustments, generating predictions, to visualizing the Mean Squared Error (MSE) Loss Curve for monitoring the training phase.
In the visual example above, you can see that the prediction is not aligned with the actual value. This is intentional for demonstrative purposes, and by incrementing the Epochs or Learning Rate, you will see these two values converge as the accuracy increases.
Hyperparameters:
Learning Rate, Epochs, and the choice between Simple Backpropagation and a verbose version are declared as script inputs, allowing users to tailor the training process.
Initialization:
Random initialization of weight matrices (w1, w2) is performed to ensure asymmetry, promoting effective gradient updates. A seed is added for reproducibility.
Utility Functions:
Functions for matrix randomization, sigmoid activation, MSE loss calculation, data normalization, and standardization are defined to streamline the computation process.
Neural Network Computation:
The feedforward function computes the hidden and output layer values given the input.
Two variants of the backpropagation function are provided for weight adjustment, with one offering a more verbose step-by-step computation of gradients.
A wrapper train_nn function iterates through epochs, performing feedforward, loss computation, and backpropagation in each epoch while logging and collecting loss values.
Training Invocation:
The input data is prepared by normalizing it to a value between 0 and 1 using the maximum standardized value, and the training process is invoked only on the last confirmed bar to preserve computational resources.
Output Forecasting and Visualization:
Post training, the NN's output (predicted price) is computed, standardized and visualized alongside the actual price on the chart.
The MSE loss between the predicted and actual prices is visualized, providing insight into the prediction accuracy.
Optionally, the MSE Loss Curve is plotted on the chart, illustrating the loss trajectory through epochs, assisting in understanding the training performance.
Customizable Visualization:
Various inputs control visualization aspects like Chart Scaling, Chart Horizontal Offset, and Chart Vertical Offset, allowing users to adapt the visualization to their preference.
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The following is this Neural Network structure, consisting of one hidden layer, with two hidden neurons.
Through understanding the steps outlined in my code, one should be able to scale the NN in any way they like, such as changing the input / output data and layers to fit their strategy ideas.
Additionally, one could forgo the backpropagation function, and load their own trained weights into the w1 and w2 matrices, to have this code run purely for inference.
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While this demonstration does create a “prediction”, it is on historical data. The purpose here is educational, rather than providing a ready tool for non-programmer consumers.
Normally in Machine Learning projects, the training process would be split into two segments, the Training and the Validation parts. For the purpose of conveying the core concept in a concise and non-repetitive way, I have foregone the Validation part. However, it is merely the application of your trained network on new data (feedforward), and monitoring the loss curve.
Essentially, checking the accuracy on “unseen” data, while training it on “seen” data.
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I hope that this code will help developers create interesting machine learning applications within the Tradingview ecosystem.
RAS.V2 Strength Index OscillatorHeavily modified version of my previous "Relative Aggregate Strength Oscillator" -Added high/low lines, alma curves,, lrc bands, changed candle calculations + other small things. Replaces the standard RSI indicator with something a bit more insightful.
Credits to @wolneyyy - 'Mean Deviation Detector - Throw Out All Other Indicators ' And @algomojo - 'Responsive Coppock Curve'
And the default Relative Strength Index
The candles are the average of the MFI ,CCI ,MOM and RSI candles, they seemed similar enough in style to me so I created candles out of each and the took the sum of all the candle's OHLC values and divided by 4 to get an average, same as v1 but with some tweaks. Previous Peaks and Potholes visible with the blue horizontal lines which adjust when a new boundary is established. Toggle alma waves or smalrc curves or both to your liking. This indicator is great for calling out peaks and troughs in realtime, although is best when combined with other trusted indicators to get a consensus.
hayatguzel trendycurveENG
If we are wondering how the trendlines drawn on the hayatguzel indicator look like on the graph, we should use this indicator. Trendlines that are linear in Hg (hayatguzel) are actually curved in the graph.
"hayatguzel curve" indicator has capable of plotting horizontal levels but not trendlines in hg indicator. But "hayatguzel trendycurve" indicator has capable of plotting (on the chart) trendlines in hg.
First of all, we start by determining the coordinates from the trendlines drawn in hg. The coordinate of trendline beginings is x1,y1. In the continuation of the trendline, the coordinate of the second point taken from anywhere on the trendline is defined as x2,y2. In order to find the x1 and x2 values, the gray bar index chart must be open. After reading the values, the bar index chart can be turned off in the settings. The x coordinates of the trendlines will be the values in this gray bar index graph. You can read these coordinates from the gray numbers in the hg-trendycurve setting at the top left of the graph. The y values are the y axis values in the hg indicator.
It should be noted that the ema value in the hayatguzel trendycurve indicator must be the same as the ema value in the hg indicator.
Hayatguzel trendycurve indicator is not an indicator that can be used on its own, it should be used together with hayatguzel indicator.
TR
Hayatguzel indikatöründe çizilen trendline'ların grafik üzerine nasıl göründüğünü merak ediyorsak bu indikatörü kullanmalıyız. Hg'de doğrusal olan trendline'lar doğal olarak grafikte eğriseller.
Hayatguzel curve indikatöründe hg'deki sadece yatay seviyeler grafiğe dökülürken bu hayatguzel trendycurve indikatörü ile hg'deki trendline'lar da grafiğe dökülebiliyor.
Öncelikle hg'de çizilen trendline'lardan koordinatları belirlemek ile işe başlıyoruz. Trendline'ların başladığı yerin koordinatı x1,y1'dir. Trendline'ın devamında trendline üzerinde herhangi bir yerden alınan ikinci noktanın koordinatı da x2,y2 olarak tanımlandı. x1 ve x2 değerlerini bulabilmek için gri bar index grafiğinin açık olması gerekmektedir. Değerleri okuduktan sonra bar index grafiği ayarlardan kapatılabilir. Trendline'ların x koordinatları bu gri renkli bar index grafiğindeki değerler olacaktır. Bu koordinatları grafikte sol üstte bulunan hg-trendycurve ayalarındaki gri sayılardan okuyabilirsiniz. y değerleri ise hg indikatöründeki y ekseni değerleridir.
Unutulmamalı ki hayatguzel trendycurve indikatöründeki ema değeri hg indikatöründeki ema değeri ile aynı olmalıdır.
Hayatguzel trendycurve indikatörü kendi başına kullanılabilecek bir indikatör olmayıp hayatguzel indikatörü ile beraber kullanılması gerekmektedir.
Momentum Strategy (BTC/USDT; 1h) - MACD (with source code)Good morning traders.
It's been a while from my last publication of a strategy and today I want to share with you this small piece of script that showed quite interesting result across bitcoin and other altcoins.
The macd indicator is an indicator built on the difference between a fast moving average and a slow moving average: this difference is generally plottted with a blue line while the orange line is simply a moving average computed on this difference.
Usually this indicator is used in technical analysis for getting signals of buy and sell respectively when the macd crosses above or under its moving average: it means that the distance of the fast moving average (the most responsive one) from the slower one is getting lower than what it-used-to-be in the period considered: this could anticipate a cross of the two moving averages and you want to anticipate this potential trend reversal by opening a long position
Of course the workflow is specularly the same for opening short positions (or closing long positions)
What this strategy does is simply considering the moving average computed on macd and applying a linear regression on it: in this way, even though the signal can be sligthly delayed, you reduce noise plotting a smooth curve.
Then, it simply checks the maximums and the minimums of this curve detecting whenever the changes of the values start to be negative or positive, so it opens a short position (closes long) on the maximum on this curve and it opens a long position (closes short) on the minimum.
Of course, I set an option for using this strategy in a conventional way working on the crosses between macd and its moving average. Alternatively you can use this workflow if you prefer.
In conclusion, you can use a tons of moving averages: I made a function in pine in order to allw you to use any moving average you want for the two moving averages on which the macd is based or for the moving average computed on the macd
PLEASE, BE AWARE THAT THIS TRADING STRATEGY DOES NOT GUARANTEE ANY KIND OF SUCCESS IN ADVANCE. YOU ARE THE ONE AND ONLY RESPONSIBLE OF YOUR OWN DECISIONS, I DON'T TAKE ANY RESPONSIBILITY ASSOCIATED WITH THEM. IF YOU RUN THIS STRATEGY YOU ACCEPT THE POSSIBILITY OF LOOSING MONEY, ALL OF MY PUBBLICATIONS ARE SUPPOSED TO BE JUST FOR EDUCATIONAL PURPOSES.
IT IS AT YOUR OWN RISK WHETHER TO USE IT OR NOT
But if you make money out of this, please consider to buy me a beer 😜
Happy Trading!
Market Meanness Index-Price ChangesThis is the Market Mean index. It is used to identify if the market is really trending or if it is range bound(random). In theory, a random sample will be mean reverting 75% of the time. This indicator checks to see what how much the market is mean reverting and converts it to a percentage. If the index is around 75 or higher than the price curve of the market is range bound and there is no trend from a statistical standpoint. If the index is below 75 this means the price curve of the market is in fact trending in a direction as the market is not reverting as much as it should if it were truly following a random/range bound price curve.
chanlun缠论 - 笔与中枢Overview
The Chanlun (缠论) Strokes & Central Zones indicator is an advanced technical analysis tool based on Chinese Chan Theory (Chanlun Theory). It automatically identifies market structure through "strokes" (笔) and "central hubs" (中枢), providing traders with a systematic framework for understanding price movements, trend structure, and potential reversal zones.
Theoretical Foundation
Chan Theory is a sophisticated price action methodology that breaks down market movements into hierarchical structures:
Local Extremes: Swing highs and lows identified through lookback periods
Strokes (笔): Valid price movements between opposite extremes that meet specific criteria
Central Hubs (中枢): Consolidation zones formed by overlapping strokes, representing key support/resistance areas
Key Components
1. Local Extreme Detection
Identifies swing highs and lows using a configurable lookback period (default: 5 bars)
Only considers extremes within the specified calculation range
Forms the foundation for stroke construction
2. Stroke (笔) Identification
The indicator applies a multi-stage filtering process to identify valid strokes:
Stage 1 - Extreme Consolidation:
Merges consecutive extremes of the same type (high or low)
Keeps only the most extreme value (highest high or lowest low)
Stage 2 - Stroke Validation:
Ensures minimum bar gap between strokes (default: 4 bars)
Alternative validation: 2+ bars with >1% price change
Eliminates noise and insignificant price movements
Color Coding:
White Lines: Regular up/down strokes
Yellow Lines: Strokes that form part of a central hub
Customizable width and colors for different stroke types
3. Central Hub (中枢) Formation
A central hub forms when at least 3 consecutive strokes have overlapping price ranges:
Formation Rules:
Stroke 1:
Stroke 2:
Stroke 3:
Hub Upper = MIN(High1, High2, High3)
Hub Lower = MAX(Low1, Low2, Low3)
Valid if: Hub Upper > Hub Lower
Hub Extension:
Subsequent strokes that overlap with the hub extend it
Hub ends when a stroke no longer overlaps
Creates rectangular zones on the chart
Visual Representation:
Green rectangular boxes: Mark the time and price range of each central hub
Dashed extension lines: Show the latest hub boundaries extending to the right
Price labels on axis: Display exact hub upper and lower boundary values
4. Extreme Point Markers (Optional)
Red markers for tops (▼)
Green markers for bottoms (▲)
Marks every validated stroke extreme point
Useful for detailed structure analysis
5. Information Table (Optional)
Displays real-time statistics:
Symbol name
Current timeframe
Lookback period setting
Minimum gap setting
Total stroke count
Parameter Settings
Performance Settings
Max Bars to Calculate (3600): Limits historical calculation to improve performance
Local Extreme Lookback Period (5): Bars used to identify swing highs/lows
Min Gap Bars (4): Minimum bars required between valid strokes
Display Settings
Show Strokes: Toggle stroke line visibility
Show Central Hub: Toggle hub box visibility
Show Hub Extension Lines: Toggle dashed boundary lines
Show Extreme Point Marks: Toggle top/bottom markers
Show Info Table: Toggle statistics table
Color Settings
Full customization of:
Up/down stroke colors and widths
Hub stroke colors and widths
Hub border and background colors
Extension line colors
Trading Applications
Trend Structure Analysis
Uptrend: Series of higher highs and higher lows connected by strokes
Downtrend: Series of lower highs and lower lows connected by strokes
Consolidation: Formation of central hubs indicating range-bound movement
Support and Resistance Identification
Central Hub Zones: Act as strong support/resistance areas
Hub Upper Boundary: Resistance level in consolidation, support after breakout
Hub Lower Boundary: Support level in consolidation, resistance after breakdown
Price tends to react at these levels due to market structure memory
Breakout Trading
Bullish Breakout: Price closes above hub upper boundary
Previous resistance becomes support
Entry on retest of upper boundary
Stop loss below hub zone
Bearish Breakdown: Price closes below hub lower boundary
Previous support becomes resistance
Entry on retest of lower boundary
Stop loss above hub zone
Reversal Detection
Hub Formation After Trend: Signals potential trend exhaustion
Multiple Hub Levels: Create probability zones for reversals
Stroke Count: Excessive strokes within hub suggest weakening momentum
Position Management
Use hub boundaries for stop loss placement
Scale out positions at hub edges
Re-enter on retests of broken hub levels
Interpretation Guide
Strong Trending Market
Long, clear strokes with minimal overlap
Few or no central hubs forming
Strokes consistently in same direction
Wide spacing between extremes
Consolidating Market
Multiple central hubs forming
Short, overlapping strokes
Yellow hub strokes dominate the chart
Narrow price range
Trend Transition
Hub formation after extended trend
Stroke direction changes frequently
Hub boundaries being tested repeatedly
Potential reversal zone
Advanced Usage Techniques
Multi-Timeframe Analysis
Higher Timeframe: Identify major hub zones for overall market structure
Lower Timeframe: Find precise entry points within larger structure
Alignment: Trade when lower timeframe strokes align with higher timeframe hub breaks
Hub Quality Assessment
Wide Hubs: Strong consolidation, higher probability support/resistance
Narrow Hubs: Weak consolidation, may break easily
Extended Hubs: More strokes = stronger zone
Isolated Hubs: Single hub = potential pivot point
Stroke Analysis
Stroke Length: Longer strokes = stronger momentum
Stroke Speed: Fewer bars per stroke = explosive moves
Stroke Clustering: Many short strokes = indecision
Best Practices
Parameter Optimization
Adjust lookback period based on timeframe and volatility
Lower periods (3-4): More strokes, more noise, faster signals
Higher periods (7-10): Fewer strokes, cleaner structure, slower signals
Confirmation Strategy
Don't trade on strokes alone
Combine with volume analysis
Use candlestick patterns at hub boundaries
Wait for breakout confirmation
Risk Management
Always place stops outside hub zones
Use hub width to size positions (wider hub = smaller position)
Exit if price re-enters broken hub from wrong direction
Avoid Common Pitfalls
Don't trade within central hubs (range-bound, unpredictable)
Don't ignore higher timeframe hub structures
Don't chase strokes after they've extended far from hub
Don't trust single-stroke hubs (need 3+ strokes for validity)
Performance Considerations
Max Bars Limit: Set to 3600 to balance detail with performance
Safe Distance Calculation: Only draws objects within 2000 bars of current price
Object Cleanup: Automatically removes old drawing objects to prevent memory issues
Efficient Arrays: Uses indexed arrays for fast lookup and processing
Ideal Market Conditions
Best Performance:
Liquid markets with clear structure (major forex pairs, indices, large-cap stocks)
Trending markets with periodic consolidations
Medium to high volatility for clear stroke formation
Less Effective:
Extremely choppy, directionless markets
Very low timeframes (< 5 minutes) with excessive noise
Illiquid instruments with erratic price action
Integration with Other Indicators
Complementary Tools:
Volume Profile: Confirm hub significance with volume nodes
Moving Averages: Use for trend bias within stroke structure
RSI/MACD: Momentum confirmation at hub boundaries
Fibonacci Retracements: Hub levels often align with Fib levels
Advantages
✓ Objective Structure: Removes subjectivity from market structure analysis
✓ Visual Clarity: Color-coded strokes and clear hub zones
✓ Multi-Timeframe Applicable: Works on all timeframes from minutes to months
✓ Complete Framework: Provides entry, exit, and risk management levels
✓ Theoretical Foundation: Based on proven Chan Theory methodology
✓ Customizable: Extensive parameter and visual customization options
Limitations
⚠ Learning Curve: Requires understanding of Chan Theory principles
⚠ Lag Factor: Strokes confirm after price movements complete
⚠ Parameter Sensitivity: Different settings produce significantly different results
⚠ Choppy Market Struggles: Can generate excessive hubs in range-bound conditions
⚠ Computation Intensive: May slow down on lower-end systems with max bars setting
Optimization Tips
Timeframe Selection
Scalping: 5-15 minute charts, lookback period 3-4
Day Trading: 15-60 minute charts, lookback period 4-5
Swing Trading: 4-hour to daily charts, lookback period 5-7
Position Trading: Daily to weekly charts, lookback period 7-10
Volatility Adjustment
High volatility: Increase minimum gap bars to reduce noise
Low volatility: Decrease lookback period to capture smaller moves
Visual Optimization
Use contrasting colors for different market conditions
Adjust line widths based on chart resolution
Toggle markers off for cleaner appearance once familiar with structure
Quick Start Guide
For Beginners:
Start with default settings (5 lookback, 4 min gap)
Enable "Show Info Table" to track stroke count
Focus on identifying clear hub formations
Practice waiting for price to break hub boundaries before trading
For Advanced Users:
Optimize lookback and gap parameters for your instrument
Use hub strokes (yellow) to identify key consolidation zones
Combine with multiple timeframes for confirmation
Develop entry rules based on hub breakout/retest patterns
This indicator provides a complete structural framework for understanding market behavior through the lens of Chan Theory, offering traders a systematic approach to identifying high-probability trading opportunities.
ZenAlgo - ADXThis open-source indicator builds upon the official Average Directional Index (ADX) implementation by TradingView. It preserves the core logic of the original ADX while introducing additional visualization features, configurability, and analytical overlays to assist with directional strength analysis.
Core Calculation
The script computes the ADX, +DI, and -DI based on smoothed directional movement and true range over a user-defined length. The smoothing is performed using Wilder’s method, as in the original implementation.
True Range is calculated from the current high, low, and previous close.
Directional Movement components (+DM, -DM) are derived by comparing the change in highs and lows between consecutive bars.
These values are then smoothed, and the +DI and -DI are expressed as percentages of the smoothed True Range.
The difference between +DI and -DI is normalized to derive DX, which is further smoothed to yield the ADX value.
The indicator includes a selectable signal line (SMA or EMA) applied to the ADX for crossover-based visualization.
Visualization Enhancements
Several plots and conditions have been added to improve interpretability:
Color-coded histograms and lines visualize DI relative to a configurable threshold (default: 25). Colors follow the ZenAlgo color scheme.
Dynamic opacity and gradient coloring are used for both ADX and DI components, allowing users to distinguish weak/moderate/strong directional trends visually.
Mirrored ADX is internally calculated for certain overlays but not directly plotted.
The script also provides small circles and diamonds to highlight:
Crossovers between ADX and its signal line.
DI crossing above or below the 25 threshold.
Rising ADX confirmed by rising DI values, with point size reflecting ADX strength.
Divergence Detection
The indicator includes optional detection of fractal-based divergences on the DI curve:
Regular and hidden bullish and bearish divergences are identified based on relative fractal highs/lows in both price and DI.
Detected divergences are optionally labeled with 'R' (Regular) or 'H' (Hidden), and color-coded accordingly.
Fractal points are defined using 5-bar patterns to ensure consistency and reduce false positives.
ADX/DI Table
When enabled, a floating table displays live values and summaries:
ADX value , trend direction (rising/falling), and qualitative strength.
DI composite , trend direction, and relative strength.
Contextual power dynamics , describing whether bulls or bears are gaining or losing strength.
The background colors of the table reflect current trend strength and direction.
Interpretation Guidelines
ADX indicates the strength of a trend, regardless of its direction. Values below 20 are often considered weak, while those above 40 suggest strong trending conditions.
+DI and -DI represent bullish and bearish directional movements, respectively. Crossovers between them are used to infer trend direction.
When ADX is rising and either +DI or -DI is dominant and increasing, the trend is likely strengthening.
Divergences between DI and price may suggest potential reversals but should be interpreted cautiously and not in isolation.
The threshold line (default 25) provides a basic filter for ignoring low-strength conditions. This can be adjusted depending on the market or timeframe.
Added Value over Existing Indicators
Fully color-graded ADX and DI display for better visual clarity.
Optional signal MA over ADX with crossover markers.
Rich contextual labeling for both divergence and threshold events.
Power dynamics commentary and live table help users contextualize current momentum.
Customizable options for smoothing type, divergence display, table position, and visual offsets.
These additions aim to improve situational awareness without altering the fundamental meaning of ADX/DI values.
Limitations and Disclaimers
As with any ADX-based tool, this indicator does not indicate market direction alone —it measures strength, not trend bias.
Divergence detection relies on fractal patterns and may lag or produce false positives in sideways markets.
Signal MA crossovers and DI threshold breaks are not entry signals , but contextual markers that may assist with timing or filtering other systems.
The table text and labels are for visual assistance and do not replace proper technical analysis or market context.
RMSD Trend [InvestorUnknown]RMSD Trend is a trend-following indicator that utilizes Root Mean Square Deviation (RMSD) to dynamically construct a volatility-weighted trend channel around a selected moving average. This indicator is designed to enhance signal clarity, minimize noise, and offer quantitative insights into market momentum, ideal for both discretionary and systematic traders.
How It Works
At its core, RMSD Trend calculates a deviation band around a selected moving average using the Root Mean Square Deviation (similar to standard deviation but with squared errors), capturing the magnitude of price dispersion over a user-defined period. The logic is simple:
When price crosses above the upper deviation band, the market is considered bullish (Risk-ON Long).
When price crosses below the lower deviation band, the market is considered bearish (Risk-ON Short).
If price stays within the band, the market is interpreted as neutral or ranging, offering low-risk decision zones.
The indicator also generates trend flips (Long/Short) based on crossovers and crossunders of the price and the RMSD bands, and colors candles accordingly for enhanced visual feedback.
Features
7 Moving Average Types: Choose between SMA, EMA, HMA, DEMA, TEMA, RMA, and FRAMA for flexibility.
Customizable Source Input: Use price types like close, hl2, ohlc4, etc.
Volatility-Aware Channel: Adjustable RMSD multiplier determines band width based on volatility.
Smart Coloring: Candles and bands adapt their colors to reflect trend direction (green for bullish, red for bearish).
Intra-bar Repainting Toggle: Option to allow more responsive but repaintable signals.
Speculation Fill Zones: When price exceeds the deviation channel, a semi-transparent fill highlights potential momentum surges.
Backtest Mode
Switching to Backtest Mode unlocks a robust suite of simulation features:
Built-in Equity Curve: Visualizes both strategy equity and Buy & Hold performance.
Trade Metrics Table: Displays the number of trades, win rates, gross profits/losses, and long/short breakdowns.
Performance Metrics Table: Includes key stats like CAGR, drawdown, Sharpe ratio, and more.
Custom Date Range: Set a custom start date for your backtest.
Trade Sizing: Simulate results using position sizing and initial capital settings.
Signal Filters: Choose between Long & Short, Long Only, or Short Only strategies.
Alerts
The RMSD Trend includes six built-in alert conditions:
LONG (RMSD Trend) - Trend flips from Short to Long
SHORT (RMSD Trend) - Trend flips from Long to Short
RISK-ON LONG (RMSD Trend) - Price crosses above upper RMSD band
RISK-OFF LONG (RMSD Trend) - Price falls back below upper RMSD band
RISK-ON SHORT (RMSD Trend) - Price crosses below lower RMSD band
RISK-OFF SHORT (RMSD Trend) - Price rises back above lower RMSD band
Use Cases
Trend Confirmation: Confirms directional bias with RMSD-weighted confidence zones.
Breakout Detection: Highlights moments when price breaks free from historical volatility norms.
Mean Reversion Filtering: Avoids false signals by incorporating RMSD’s volatility sensitivity.
Strategy Development: Backtest your signals or integrate with a broader system for alpha generation.
Settings Summary
Display Mode: Overlay (default) or Backtest Mode
Average Type: Choose from SMA, EMA, HMA, DEMA, etc.
Average Length: Lookback window for moving average
RMSD Multiplier: Band width control based on RMS deviation
Source: Input price source (close, hl2, ohlc4, etc.)
Intra-bar Updating: Real-time updates (may repaint)
Color Bars: Toggle bar coloring by trend direction
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Past performance, including backtest results, is not indicative of future results. Use with caution and always test thoroughly before live deployment.
Dskyz (DAFE) AI Adaptive Regime - Beginners VersionDskyz (DAFE) AI Adaptive Regime - Pro: Revolutionizing Trading for All
Introduction
In the fast-paced world of financial markets, traders need tools that can keep up with ever-changing conditions while remaining accessible. The Dskyz (DAFE) AI Adaptive Regime - Pro is a groundbreaking TradingView strategy that delivers advanced, AI-driven trading capabilities to everyday traders. Available on TradingView (TradingView Scripts), this Pine Script strategy combines sophisticated market analysis with user-friendly features, making it a standout choice for both novice and experienced traders.
Core Functionality
The strategy is built to adapt to different market regimes—trending, ranging, volatile, or quiet—using a robust set of technical indicators, including:
Moving Averages (MA): Fast and slow EMAs to detect trend direction.
Average True Range (ATR): For dynamic stop-loss and volatility assessment.
Relative Strength Index (RSI) and MACD: Multi-timeframe confirmation of momentum and trend.
Average Directional Index (ADX): To identify trending markets.
Bollinger Bands: For assessing volatility and range conditions.
Candlestick Patterns: Recognizes patterns like bullish engulfing, hammer, and double bottoms, confirmed by volume spikes.
It generates buy and sell signals based on a scoring system that weighs these indicators, ensuring trades align with the current market environment. The strategy also includes dynamic risk management with ATR-based stops and trailing stops, as well as performance tracking to optimize future trades.
What Sets It Apart
The Dskyz (DAFE) AI Adaptive Regime - Pro distinguishes itself from other TradingView strategies through several unique features, which we compare to common alternatives below:
| Feature | Dskyz (DAFE) | Typical TradingView Strategies|
|---------|-------------|------------------------------------------------------------|
| Regime Detection | Automatically identifies and adapts to **four** market regimes | Often static or limited to trend/range detection |
| Multi‑Timeframe Analysis | Uses higher‑timeframe RSI/MACD for confirmation | Rarely incorporates multi‑timeframe data |
| Pattern Recognition | Detects candlestick patterns **with volume confirmation** | Limited or no pattern recognition |
| Dynamic Risk Management | ATR‑based stops and trailing stops | Often uses fixed stops or basic risk rules |
| Performance Tracking | Adjusts thresholds based on past performance | Typically static parameters |
| Beginner‑Friendly Presets | Aggressive, Conservative, Optimized profiles | Requires manual parameter tuning |
| Visual Cues | Color‑coded backgrounds for regimes | Basic or no visual aids |
The Dskyz strategy’s ability to integrate regime detection, multi-timeframe analysis, and user-friendly presets makes it uniquely versatile and accessible, addressing the needs of everyday traders who want professional-grade tools without the complexity.
-Key Features and Benefits
[Why It’s Ideal for Everyday Traders
⚡The Dskyz (DAFE) AI Adaptive Regime - Pro democratizes advanced trading by offering professional-grade tools in an accessible package. Unlike many TradingView strategies that require deep technical knowledge or fail in changing market conditions, this strategy simplifies complex analysis while maintaining robustness. Its presets and visual aids make it easy for beginners to start, while its adaptive features and performance tracking appeal to advanced traders seeking an edge.
🔄Limitations and Considerations
Market Dependency: Performance varies by market and timeframe. Backtesting is essential to ensure compatibility with your trading style.
Learning Curve: While presets simplify use, understanding regimes and indicators enhances effectiveness.
No Guaranteed Profits: Like all strategies, success depends on market conditions and proper execution. The Reddit discussion highlights skepticism about TradingView strategies’ universal success (Reddit Discussion).
Instrument Specificity: Optimized for futures (e.g., ES, NQ) due to fixed tick values. Test on other instruments like stocks or forex to verify compatibility.
📌Conclusion
The Dskyz (DAFE) AI Adaptive Regime - Pro is a revolutionary TradingView strategy that empowers everyday traders with advanced, AI-driven tools. Its ability to adapt to market regimes, confirm signals across timeframes, and manage risk dynamically. sets it apart from typical strategies. By offering beginner-friendly presets and visual cues, it makes sophisticated trading accessible without sacrificing power. Whether you’re a novice looking to trade smarter or a pro seeking a competitive edge, this strategy is your ticket to mastering the markets. Add it to your chart, backtest it, and join the elite traders leveraging AI to dominate. Trade like a boss today! 🚀
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
Standard Deviation (fadi)The Standard Deviation indicator uses standard deviation to map out price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior.
These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day.
How Traders Use It
If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop.
If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation.
Settings
Higher Timeframe: Sets the Higher Timeframe to calculate the Standard Deviation for
Show Levels for the Last X Days: Displays levels for the specified number of days.
Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes.
Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average.
Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed.
Background Transparency: Turn on Background color derived from the level colors with the specified transparency
Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296).
Daily Standard Deviation (fadi)The Daily Standard Deviation indicator uses standard deviation to map out daily price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior.
These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day.
How Traders Use It
If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop.
If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation.
Settings
Open Hour: Sets the trading day’s start (default: 18:00 EST).
Show Levels for the Last X Days: Displays levels for the specified number of days.
Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes.
Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average.
Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed.
Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296).
MA Multi-Timeframe [ChartPrime]The MA Multi-Timeframe indicator is designed to provide multi-timeframe moving averages (MAs) for better trend analysis across different periods. This tool allows traders to monitor up to four different MAs on a single chart, each coming from a selectable timeframe and type (SMA, EMA, SMMA, WMA, VWMA). The indicator helps traders gauge both short-term and long-term price trends, allowing for a clearer understanding of market dynamics.
⯁ KEY FEATURES AND HOW TO USE
⯌ Multi-Timeframe Moving Averages :
The indicator allows traders to select up to four MAs, each from different timeframes. These timeframes can be set in the input settings (e.g., Daily, Weekly, Monthly), and each moving average can be displayed with its corresponding timeframe label directly on the chart.
Example of different timeframes for MAs:
⯌ Moving Average Types :
Users can choose from several types of moving averages, including SMA, EMA, SMMA, WMA, and VWMA, making the indicator adaptable to different strategies and market conditions. This flexibility allows traders to tailor the MAs to their preference.
Example of different types of MAs:
⯌ Dashboard Display :
The indicator includes a built-in dashboard that shows each MA, its timeframe, and whether the price is currently above or below that MA. This dashboard provides a quick overview of the trend across different timeframes, allowing traders to determine whether the overall trend is up or down.
Example of trend overview via the dashboard:
⯌ Polyline Representation :
Each MA is plotted using polylines to avoid plot functions and create a curves across up to 4000 bars back, ensuring that historical data is visualized clearly for a deeper analysis of how the price interacts with these levels over time.
if barstate.islast
for i = 0 to 4000
cp.push(chart.point.from_index(bar_index , ma ))
polyline.delete(polyline.new(cp, curved = false, line_color = color, line_style = style) )
Example of polylines for moving averages:
⯌ Customization Options :
Traders can customize the length of the MAs for all timeframes using a single input. The color, style (solid, dashed, dotted) of each moving average are also customizable, giving users full control over the visual appearance of the indicator on their chart.
Example of custom MA styles:
⯁ USER INPUTS
MA Type : Select the type of moving average for each timeframe (SMA, EMA, SMMA, WMA, VWMA).
Timeframe : Choose the timeframe for each moving average (e.g., Daily, Weekly, Monthly).
MA Length : Set the length for the moving averages, which will be applied to all four MAs.
Line Style : Customize the style of each MA line (solid, dashed, or dotted).
Colors : Set the color for each MA for better visual distinction.
⯁ CONCLUSION
The MA Multi-Timeframe indicator is a versatile and powerful tool for traders looking to monitor price trends across multiple timeframes with different types of moving averages. The dashboard simplifies trend identification, while the customizable options make it easy to adapt to individual trading strategies. Whether you're analyzing short-term price movements or long-term trends, this indicator offers a comprehensive solution for tracking market direction.
Correlation AnalysisAs the name suggests, this indicator is a market correlation analysis tool.
It contains two main features:
- The Curve: represents the historic correlation coefficient between the current chart and the “Reference Market” input from the settings menu. It aims to give more depth to the current correlation values found in the second feature.
- The Screener: this second feature displays all correlation coefficient values between the (max) 20 markets inputs. You can use it to create several screeners for several market types (crypto, forex, metals, etc.) or even replicate your current portfolio of investments and gauge the correlation of its components.
Aside from these two previous features, you can visually plot the variation rate from one bar to another along with the covariance coefficient (both used in the correlation calculation). Finally, a simple “signal” moving average can be applied to the correlation coefficient .
I might add alerts to this script or even turn it into a strategy to do some backtesting. Do not hesitate to contact me or comment below if this is something you would be interested in or if you have any suggestions for improvement.
Enjoy!!
VHF Adaptive Linear Regression KAMAIntroduction
Heyo, in this indicator I decided to add VHF adaptivness, linear regression and smoothing to a KAMA in order to squeeze all out of it.
KAMA:
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low. KAMA will adjust when the price swings widen and follow prices from a greater distance. This trend-following indicator can be used to identify the overall trend, time turning points and filter price movements.
VHF:
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Linear Regression Curve:
A line that best fits the prices specified over a user-defined time period.
This is very good to eliminate bad crosses of KAMA and the pric.
Usage
You can use this indicator on every timeframe I think. I mostly tested it on 1 min, 5 min and 15 min.
Signals
Enter Long -> crossover(close, kama) and crossover(kama, kama )
Enter Short -> crossunder(close, kama) and crossunder(kama, kama )
Thanks for checking this out!
--
Credits to
▪️@cheatcountry – Hann Window Smoohing
▪️@loxx – VHF and T3
▪️@LucF – Gradient
Power Law S/RBerger's article on the Power Law Model for Bitcoin is a compelling read and gives the best evidence so far of the diminishing case for retracing below $3000, of a slowing market on a log-log plot, and reducing but continued volatility.
After seeing it acts as support routinely in the last 10 years, I put together a quick little script that plots his midline curve for Bitcoin. You can change the intercept and slope but will need to do your own calculations for other curves.
I hope you all like it.
Top Bottom Finder Public version- Jayy This script plots a 6 algos from the Coles/Hawkins "Midas Technical Analysis" book:
Top finder / Bottom Finder (Levine Algo by Bob English)* - onlinelibrary.wiley.com
MIDAS VWAP Gen-1) -
MIDAS VWAP average and deltas
VWAP (Gen-1) using a date or a bar n number can be initiated at bar 0 - useful for a new IPO
Standard Deviation of MIDAS VWAP
MIDAS Displacement Channels (Coles) - edmond.mires.co
An%20Anchored%20VWAP%20Channel%20For%20Congested%20Markets.pdf
* for better results with topfinder and bottomfinder use the companion TB-F Matcher script.
See wiki for a synopsis: en.wikipedia.org
Relevant info can be found in: Midas Technical Analysis: A VWAP Approach to Trading and Investing in Today’s Markets by
Andrew Coles, David G. Hawkins Copyright © 2011 by Andrew Coles and David G. Hawkins.
Appendix C: TradeStation Code for the MIDAS Topfinder/Bottomfinder Curves ported to Tradingview
This script requires a working understanding of "Midas Technical Analysis" Google "Midas Technical Analysis" and a variety of information will appear.
To find fit the curve as described in the Midas book a companion script is required that will after a few manual iterative inputs guide you to the appropriate D value for the for input into this program ( see the TB-F Matcher script). You might also try the Midas average and Deltas as described in the book. I have added the 2nd, 3rd and 4th multiples of Delta.
The advantage is that there is no curve fitting. You still need to select a starting point for Midas or the topfinder bottomfinder (TB_F)
or the VWAP.
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
See the notes in the script below
Cheers Jayy
D-Shape Breakout Signals [LuxAlgo]The D-Shape Breakout Signals indicator uses a unique and novel technique to provide support/resistance curves, a trailing stop loss line, and visual breakout signals from semi-circular shapes.
🔶 USAGE
D-shape is a new concept where the distance between two Swing points is used to create a semi-circle/arc, where the width is expressed as a user-defined percentage of the radius. The resulting arc can be used as a potential support/resistance as well as a source of breakouts.
Users can adjust this percentage (width of the D-shape) in the settings ( "D-Width" ), which will influence breakouts and the Stop-Loss line.
🔹 Breakouts of D-Shape
The arc of this D-shape is used for detecting breakout signals between the price and the curve. Only one breakout per D-shape can occur.
A breakout is highlighted with a colored dot, signifying its location, with a green dot being used when the top part of the arc is exceeded, and red when the bottom part of the arc is surpassed.
When the price reaches the right side of the arc without breaking the arc top/bottom, a blue-colored dot is highlighted, signaling a "Neutral Breakout".
🔹 Trailing Stop-Loss Line
The script includes a Trailing Stop-Loss line (TSL), which is only updated when a breakout of the D-Shape occurs. The TSL will return the midline of the D-Shape subject to a breakout.
The TSL can be used as a stop-loss or entry-level but can also act as a potential support/resistance level or trend visualization.
🔶 DETAILS
A D-shape will initially be colored green when a Swing Low is followed by a Swing High, and red when a Swing Low is followed by a Swing High.
A breakout of the upper side of the D-shape will always update the color to green or to red when the breakout occurs in the lower part. A Neutral Breakout will result in a blue-colored D-shape. The transparency is lowered in the event of a breakout.
In the event of a D-shape breakout, the shape will be removed when the total number of visible D-Shapes exceeds the user set "Minimum Patterns" setting. Any D-shape whose boundaries have not been exceeded (and therefore still active) will remain visible.
🔹 Trailing Stop-Loss Line
Only when a breakout occurs will the midline of the D-shape closest to the closing price potentially become the new Trailing Stop value.
The script will only consider middle lines below the closing price on an upward breakout or middle lines above the closing price when it concerns a downward breakout.
In an uptrend, with an already available green TSL, the potential new Stop-Loss value must be higher than the previous TSL value; while in a downtrend, the new TSL value must be lower.
The Stop-Loss line won't be updated when a "Neutral Breakout" occurs.
🔶 SETTINGS
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
🔹 D-Patterns
Minimum Patterns: Minimum amount of visible D-Shape patterns.
D-Width: Width of the D-Shape as a percentage of the distance between both Swing Points.
Included Swings: Include "Swing High" (followed by a Swing Low), "Swing Low" (followed by a Swing High), or "Both"
Style Historical Patterns: Show the "Arc", "Midline" or "Both" of historical patterns.
🔹 Style
Label Size/Colors
Connecting Swing Level: Shows a line connecting the first Swing Point.
Color Fill: colorfill of Trailing Stop-Loss
Savitzky-Golay Smoothing FilterThe Savitzky-Golay Filter is a polynomial smoothing filter.
This version implements 3rd degree polynomials using coefficients from Savitzky and Golay's table, specifically the coefficients for a 5-, 7-, 9-, 15- and 25-point window moving averages.
The filters are offset to the left by the number of coefficients (n-1)/2 so it smooths on top of the actual curve.
You can turn off some of the smoothing curves, as it can get cluttered displaying all at once.
Any feedback is very welcome.
Multi-Timeframe Recursive Zigzag [Trendoscope®]🎲 Welcome to the Advanced World of Zigzag Analysis
Embark on a journey through the most comprehensive and feature-rich Zigzag implementation you’ll ever encounter. Our Multi-Timeframe Recursive Zigzag Indicator is not just another tool; it's a groundbreaking advancement in technical analysis.
🎯 Key Features
Multi Time-Frame Support - One of the rare open-source Zigzag indicators with robust multi-timeframe capabilities, this feature sets our tool apart, enabling a broader and more dynamic market analysis.
Innovative Recursive Zigzag Algorithm - At its core is our unique Recursive Zigzag Algorithm, a pioneering development that powers multiple Zigzag levels, offering an intricate view of market movements. This proprietary algorithm is the backbone of our advanced pattern recognition indicators.
Sub-Waves and Micro-Waves Analysis - Dive deeper into market trends with our Sub-Waves and Micro-Waves feature. Sub-Waves reveal the interconnectedness of various Zigzag levels, while Micro-Waves offer insight into the fundamental waves at the base level.
Enhanced Indicator Tracking - Integrate and track your custom indicators or oscillators with the zigzag, capturing their values at each Zigzag level, complete with retracement ratios. This offers a comprehensive view of market dynamics.
Curved Zigzag Visualization - Experience a new way of visualizing market movements with our Curved Zigzag Display, employing Pine Script’s polyline feature for a more intuitive and visually appealing representation.
Built-in Customizable Alerts - Stay ahead with built-in alerts that can be customized via user input settings.
🎯 Practical Applications
Our Zigzag Indicator is designed with an understanding of its inherent nature - the last unconfirmed pivot that consistently repaints. This characteristic, while by design, directs its usage more towards pattern recognition rather than direct identification of market tops and bottoms. Here's how you can leverage the Zigzag Indicator:
Harmonic Patterns - Ideal for those familiar with harmonic patterns, this tool simplifies the manual spotting of complex XABCD, ABC, and ABCD patterns on charts.
Chart Patterns - Effortlessly identify patterns like Double/Triple Taps, Head and Shoulders, Inverse Head and Shoulders, and Cup and Handle patterns with enhanced clarity. Navigate through challenging patterns such as Triangles, Wedges, Flags, and Price Channels, where the Zigzag Indicator adds a layer of precision to your breakout strategy.
Elliott Wave Components - The indicator's detailed pivot highlighting aids in identifying key Elliott Wave components, enhancing your wave analysis and decision-making process.
🎲 Deep Dive into Indicator Features
Join us as we explore the intricate features of our indicator in more detail.
🎯 Multi-Timeframe Capability
Our indicator comes equipped with an input option for selecting the desired resolution. This unique feature allows users to view higher timeframe Zigzag patterns directly on their lower timeframe charts.
🎯 Recursive Multi Level Zigzag
Our advanced recursive approach creates multi-level Zigzags from lower-level data. For instance, the level 0 Zigzag forms the base, calculated from specified length and depth parameters, while level 1 Zigzag is derived using level 0 as its foundation, and so forth.
The indicator not only displays multiple Zigzag levels but also offers settings to emphasize specific levels for more detailed analysis.
🎯 Sub-Components and Micro-Components of Zigzag Wave
Sub-components within a Zigzag wave consist of the previous level's Zigzag pivots. Meanwhile, the micro-components are composed of the base level (Level 0) Zigzag pivots encapsulated within the wave.
🎯 Curved Zigzag
Experience a new perspective with our curved Zigzag display. This innovative feature utilizes the polyline curved option to automatically generate sinusoidal waves based on multiple points.
🎯 Indicator Tracking
Default indicators such as RSI, MFI, and OBV are included, alongside the ability to track one external indicator at each Zigzag pivot.
🎯 Customizable Alerts
Our indicator employs the `alert()` function for alert creation. While this means the absence of a customization text box in the alert settings, we've included a custom text area for users to create their own alert templates.
Template placeholders include:
{alertType} - type of alert. Either Confirmed Pivot Update or Last Pivot Update. Depends on the alert type selected in the inputs.
When Last Pivot Update type is selected, the alerts are triggered whenever there is a new Zigzag Pivot. This may also be a repaint of last unconfirmed pivot.
When Confirmed Pivot Update type is selected, the alerts are triggered only when a pivot becomes a confirmed pivot.
{level} - Zigzag level on which the alert is triggered.
{pivot} - Details of the last pivot or confirmed pivot including price, ratio, indicator values and ratios, subcomponent and micro-component pivots.
🎲 User Settings Overview
🎯 Zigzag and Generic Settings
This involves some generic zigzag calculation settings such as length, depth, and timeframe. And few display options such as theme, Highlight Level and Curved Zigzag. By default, zigzag calculation is done based on the latest real time bar. An option is provided to disable this and use only confirmed bars for the calculation.
Indicator Settings
Allows users to track one or more oscillators or volume indicators. Option to add any indicator via external input is provided.
🎯 Alert Settings
Has input fields required to select and customize alerts.
Log Regression Channel (Dezza Fixed v2)This custom indicator builds a curved Logarithmic Regression Channel designed for long-term Bitcoin and macro asset analysis. It performs a linear regression on the logarithm of price to estimate the market’s fair-value growth curve, then converts that back into price space to form upper and lower deviation bands.
It helps identify where price sits relative to its long-term exponential trend — showing potential overvaluation (upper band) or undervaluation (lower band) zones.
Best used on weekly or monthly charts to visualise market cycles and fair-value reversion. Adjustable inputs let you control lookback length, band width, and midline visibility.
