Indicator
Iteratively Reweighted Least Squares (IRLS) [Jamallo]Author's Note: This script is published as a unique mathematical contribution to PulseWire's open-source public library. It is intended to introduce a novel application of a robust statistical method for the community and developers to study, adapt, and build upon, rather than to serve as a standalone, out-of-the-box trading strategy.
Introduction
Almost all moving averages and smoothing filters in technical analysis treat historical price data equally or apply a fixed mathematical decay (like an EMA). The problem? A massive, anomalous wick or a sudden volatility spike will inevitably drag the average away from the true underlying market consensus.
Enter Iteratively Reweighted Least Squares (IRLS) .
IRLS is a robust statistical method that calculates a "consensus" price by actively identifying and down-weighting outliers. Instead of letting a large wick distort the line, the algorithm assigns less weight to prices that deviate furthest from the current estimate. The result is a filter that cuts through noise, ignores price-distant spikes, and naturally locks onto the dominant, high-density price levels.
How It Works
The indicator uses the Hardy weight function to determine how heavily each historical candle influences the current estimate. On every bar, the algorithm checks the distance of each sample from the current consensus and iteratively refines the line until it converges on a robust mean. Epsilon — the outlier rejection scale — is derived dynamically from the average High–Low range, keeping the filter dimensionless and consistent across all instruments and timeframes.
Parameters
Window Size (N) : The rolling lookback window of historical samples the kernel considers. Larger values produce a smoother, slower-responding line.
Sparsity (s/N) : The core behavioral control. Dictates the fraction of the window allowed to "vote" on the estimate.
Low Sparsity (e.g., 0.1) : Only the 10% of samples closest to the current estimate participate. Produces a snappy, selective line that locks tightly onto the most dominant price cluster.
High Sparsity (e.g., 1.0) : All samples participate, resulting in a smoother, more conventional robust mean.
Gamma (ε scale) : Controls the strength of outlier rejection. Lower values enforce harsh, median-like rejection. Higher values soften the rejection toward a standard weighted mean.
Iterations : The number of reweighting convergence passes per bar. 2–3 is sufficient for practical convergence.
Potential Applications
The Hardy IRLS filter provides a unique lens into market structure by shifting the focus from simple time-averaged prices to spatial price consensus. Because it rejects price-distant wicks and noise spikes by design, it can serve as a foundation for:
Custom trailing stops
Dynamic support and resistance trackers
Baseline trend or regime filters
Feel free to inspect the open-source code, experiment with extreme sparsity and gamma settings, and integrate the IRLS core into your own quantitative projects.
References
Li Shuang, "Sparse Representation of Hardy Function by Iteratively Reweighted Least Squares," 2020 International Symposium on Computer Engineering and Intelligent Communications (ISCEIC), IEEE, 2020. DOI: 10.1109/ISCEIC51027.2020.00020
Indicator
Trend Sniper v2.5 - Haar Wavelet Edition [Jamallo]Author's Note:
The previous Trend Sniper v2.5 was built around a 2-Pole Butterworth Super Smoother with Parkinson historical volatility driving the trailing stops. This edition replaces that entire core with a Maximal Overlap Discrete Wavelet Transform (MODWT) using Haar basis functions and a Vervoort ATR trailing stop . Where the Butterworth produced smooth, continuous curves, the Haar wavelet produces structural steps — only updating when true market movement exceeds the calculated noise energy floor. Same Trend Sniper framework, completely different engine under the hood.
Intro
Trend Sniper v2.5 - Haar Wavelet Edition the Maximal Overlap Discrete Wavelet Transform (MODWT) using Haar basis functions. The result is a structural, step-based signal line that ignores minor price fluctuations entirely and only updates when true market movement exceeds a dynamically calculated noise threshold. Combined with a Vervoort ATR trailing stop, dual SuperTrend envelopes, and KAMA midpoint, this indicator provides a complete trend-following framework built on signal processing principles rather than traditional moving average logic.
Breakdown
Haar Wavelet Signal Line (MODWT + Adaptive Deadband)
The core of this indicator is a 5-level cascaded MODWT Haar wavelet decomposition applied to smoothed Heikin-Ashi price. At each level, price is split into a smooth coefficient (trend) and a detail coefficient (noise). The user selects a decomposition level (1–5), controlling the structural scale — from 2-bar micro-structure up to 32-bar macro-structure.
An adaptive deadband then wraps the smooth coefficient: the average absolute detail energy is measured over a lookback window and scaled by a multiplier. The signal line only steps to a new value when the smooth coefficient moves beyond this noise-energy threshold. This creates the characteristic "staircase" behavior — flat holds during noise, clean steps on real moves. The signal line colors by its own step direction: bull when it steps up, bear when it steps down.
Vervoort ATR Trailing Stop
A Sylvain Vervoort-style trailing stop is anchored directly to the Haar wavelet signal line rather than raw price. The stop distance is calculated as ATR × multiplier. In an uptrend, the stop ratchets upward and never retreats; in a downtrend, it ratchets downward. The stop flips when price closes through it. Because it's anchored to the structural wavelet line instead of noisy price, it produces cleaner, more decisive flip points.
The trailing stop uses independent CMO (Chande Momentum Oscillator) + deadband hysteresis for its coloring — it only changes color when confirmed momentum cleanly breaches the CMO threshold, preventing color flicker during consolidation.
Dual SuperTrend Envelopes
Two SuperTrend calculations using smoothed Heikin-Ashi ATR create the outer structure:
Slow SuperTrend (default mult 9.0) — the wide envelope defining macro trend boundaries
Fast SuperTrend (default mult 6.0) — combined with the signal line to create the Fast Trigger dots
The Fast Trigger is the midpoint of the fast SuperTrend and the Haar signal, plotted as orange circles for quick visual reference of momentum alignment.
KAMA Midpoint & 4-State Fill
A Kaufman Adaptive Moving Average smooths the midpoint between the slow SuperTrend and the Haar signal. The fill between the KAMA midpoint and the signal line uses four distinct color states based on whether price is above/below the slow SuperTrend and whether the signal is above/below the fast trigger — providing an immediate visual read on trend alignment and momentum phase.
End
The wavelet decomposition reveals the true step-by-step nature of price movement by mathematically separating signal from noise — use it alongside your own risk management and confluence analysis. Trade the structure, not the noise. Indicator
Two Poles Trend Finder MTF [BigBeluga]🔵 OVERVIEW
Two Poles Trend Finder MTF is a refined trend-following overlay that blends a two-pole Gaussian filter with a multi-timeframe dashboard. It provides a smooth view of price dynamics along with a clear summary of trend directions across multiple timeframes—perfect for traders seeking alignment between short and long-term momentum.
🔵 CONCEPTS
Two-Pole Filter: A smoothing algorithm that responds faster than traditional moving averages but avoids the noise of short-term fluctuations.
var float f = na
var float f_prev1 = na
var float f_prev2 = na
// Apply two-pole Gaussian filter
if bar_index >= 2
f := math.pow(alpha, 2) * source + 2 * (1 - alpha) * f_prev1 - math.pow(1 - alpha, 2) * f_prev2
else
f := source // Warm-up for first bars
// Shift state
f_prev2 := f_prev1
f_prev1 := f
Trend Detection Logic: Trend direction is determined by comparing the current filtered value with its value n bars ago (shifted comparison).
MTF Alignment Dashboard: Trends from 5 configurable timeframes are monitored and visualized as colored boxes:
• Green = Uptrend
• Magenta = Downtrend
Summary Arrow: An average trend score from all timeframes is used to plot an overall arrow next to the asset name.
🔵 FEATURES
Two-Pole Gaussian Filter offers ultra-smooth trend curves while maintaining responsiveness.
Multi-Timeframe Trend Detection:
• Default: 1H, 2H, 4H, 12H, 1D (fully customizable)
• Each timeframe is assessed independently using the same trend logic.
Visual Trend Dashboard positioned at the bottom-right of the chart with color-coded trend blocks.
Dynamic Summary Arrow shows overall market bias (🢁 / 🢃) based on majority of uptrends/downtrends.
Bold + wide trail plot for the filter value with gradient coloring based on directional bias.
🔵 HOW TO USE
Use the multi-timeframe dashboard to identify aligned trends across your preferred trading horizons.
Confirm trend strength or weakness by observing filter slope direction .
Look for dashboard consensus (e.g., 4 or more timeframes green] ) as confirmation for breakout, continuation, or trend reentry strategies.
Combine with volume or price structure to enhance entry timing.
🔵 CONCLUSION
Two Poles Trend Finder MTF delivers a clean and intuitive trend-following solution with built-in multi-timeframe awareness. Whether you’re trading intra-day or positioning for swing setups, this tool helps filter out market noise and keeps you focused on directional consensus. Indicator
SuperTrend: Silent Shadow 🕶️ SuperTrend: Silent Shadow — Operate in trend. Vanish in noise.
Overview
SuperTrend: Silent Shadow is an enhanced trend-following system designed for traders who demand clarity in volatile markets and silence during indecision.
It combines classic Supertrend logic with a proprietary ShadowTrail engine and an adaptive Silence Protocol to filter noise and highlight only the cleanest signals.
Key Features
✅ Core Supertrend Logic
Built on Average True Range (ATR), this trend engine identifies directional bias with visual clarity. Lines adjust dynamically with price action and flip when meaningful reversals occur.
✅ ShadowTrail: Stepped Counter-Barrier
ShadowTrail doesn’t predict reversals — it reinforces structure.
When price is trending, ShadowTrail forms a stepped ceiling in downtrends and a stepped floor in uptrends. This visual containment zone helps define the edges of price behavior and offers a clear visual anchor for stop-loss placement and trade containment.
✅ Silence Protocol: Adaptive Noise Filtering
During low-volatility zones, the system enters “stealth mode”:
• Trend lines turn white to indicate reduced signal quality
• Fill disappears to reduce distraction
This helps avoid choppy entries and keeps your focus sharp when the market isn’t.
✅ Visual Support & Stop-Loss Utility
When trendlines flatten or pause, they naturally highlight price memory zones. These flat sections often align with:
• Logical stop-loss levels
• Prior support/resistance areas
• Zones of reduced volatility where price recharges or rejects
✅ Custom Styling
Full control over line colors, width, transparency, fill visibility, and silence behavior. Tailor it to your strategy and visual preferences.
How to Use
• Use Supertrend color to determine bias — flips mark momentum shifts
• ShadowTrail mirrors the primary trend as a structural ceiling/floor
• Use flat segments of both lines to identify consolidation zones or place stops
• White lines = low-quality signal → stand by
• Combine with RSI, volume, divergence, or your favorite tools for confirmation
Recommended For:
• Traders seeking clearer trend signals
• Avoiding false entries in sideways or silent markets
• Identifying key support/resistance visually
• Structuring stops around real market containment levels
• Scalping, swing, or position trading with adaptive clarity
Built by Sherlock Macgyver
Forged for precision. Designed for silence.
When the market speaks, you listen.
When it doesn’t — you wait in the shadows. Indicator
Smoothed Heiken Ashi Trend FilterThis indicator applies the Heiken Ashi technique with added smoothing and trend filtering to help reduce noise and improve trend detection.
Components of the Indicator:
Heiken Ashi Calculations:
Heiken Ashi Close (ha_close): This is the smoothed average of the current bar’s open, high, low, and close prices, calculated with a simple moving average (SMA) to filter out noise.
Heiken Ashi Open (ha_open): This is the average of the previous Heiken Ashi Open and the current Heiken Ashi Close. It’s also initialized to smooth the transition on the first bar.
Heiken Ashi High (ha_high) and Low (ha_low): These values are calculated as the highest and lowest values among the high, Heiken Ashi Open, and Heiken Ashi Close for each bar.
Smoothing and Noise Reduction:
Smoothing Length: The indicator applies a smoothing length to the Heiken Ashi Close, calculated with an SMA. This reduces minor fluctuations, giving a clearer view of the price action.
Minimum Body Size Filter: This filter calculates the body size of each Heiken Ashi candle and compares it to a percentage of the Average True Range (ATR). Only significant candles (those with larger bodies) are plotted, reducing weak or indecisive signals.
Trend Filtering with Moving Average:
The indicator uses a simple moving average (SMA) as a trend filter. By comparing the Heiken Ashi Close to the moving average:
Bullish Trend: The Heiken Ashi candle is green when it’s above the moving average.
Bearish Trend: The Heiken Ashi candle is red when it’s below the moving average.
How to Use This Indicator:
Trend Identification:
Green candles signify a bullish trend, while red candles signify a bearish trend.
The smoothing and trend filtering make it easier to identify sustained trends and avoid reacting to short-term fluctuations.
Filtering Out Noise:
Minor price fluctuations and small-bodied candles (often resulting in indecisive signals) are filtered out, leaving only significant signals.
Adjustable Parameters:
Smoothing Length: Controls the degree of smoothing applied to the Heiken Ashi Close value. Increasing this value will make the Heiken Ashi candles smoother.
Minimum Body Size: This is a percentage of the ATR, used to filter out small or indecisive candles.
Trend Moving Average Length: Controls the period of the moving average used as a trend filter.
This Smoothed Heiken Ashi Trend Filter indicator is useful for identifying trends and filtering out noisy signals. By smoothing and filtering, it helps traders focus on the overall trend rather than minor price movements.
Let me know if there’s anything more you’d like to add or adjust! Indicator
Kaufman Adaptive Moving Average (KAMA) Strategy [TradeDots]"The Kaufman Adaptive Moving Average (KAMA) Strategy" is a trend-following system that leverages the adaptive qualities of the Kaufman Adaptive Moving Average (KAMA). This strategy is distinguished by its ability to adjust dynamically to market volatility, enhancing trading accuracy by minimizing the effects of false and delayed signals often associated with the Simple Moving Average (SMA).
HOW IT WORKS
This strategy is centered around use of the Kaufman Adaptive Moving Average (KAMA) indicator, which refines the principles of the Exponential Moving Average (EMA) with a superior smoothing technique.
KAMA distinguishes itself by its responsiveness to changes in market prices through an "Efficiency Ratio (ER)." This ratio is computed by dividing the recent absolute net price change by the cumulative sum of the absolute price changes over a specified period. The resulting ER value ranges between 0 and 1, where 0 indicates high market noise and 1 reflects stronger market momentum.
Using ER, we could get the smoothing constant (SC) for the moving average derived using the following formula:
fastest = 2/(fastma_length + 1)
slowest = 2/(slowma_length + 1)
SC = math.pow((ER * (fastest-slowest) + slowest), 2)
The KAMA line is then calculated by applying the SC to the difference between the current price and the previous KAMA.
APPLICATION
For entering long positions, this strategy initializes when there is a sequence of 10 consecutive rising KAMA lines. Conversely, a sequence of 10 consecutive falling KAMA lines triggers sell orders for long positions. The same logic applies inversely for short positions.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results. Strategy
Library
Heikin Ashi CountObjective:
This indicator aims to obtain an oscillator indicating the trend of a market by minimizing noise through the use of Heikin Ashi candles.
The idea is to make the oscillator tend towards 100 at each bullish Heikin Ashi candle, and inversely towards 0 when bearish.
The advantage is that this indicator has little noise compared to the RSI, but also little lag compared to the Schaff Trend Cycle, which are the two indicators that inspired me to create this one.
Usage:
As a general rule, below 15, HA Count indicates an oversell and above 85 an overbuy.
Setting the length for the candle count results in an indicator that is less sensitive when close to 1 and more sensitive when it is at 2 or higher.
Chosen as the default value, 1.15 seems to give the best indications, regardless of the market or time period.
Also it looks very similar to the values that the RSI could give set over 14 periods, so it can be used in the same way. Especially with regard to divergences.
---- FR ----
Objectif :
Cet indicateur vise à obtenir un oscillateur indicant la tendance d'un marché en minimisant le bruit grace à l'utilisation des bougies Heikin Ashi.
L'idée est de faire tendre l'oscillateur vers 100 à chaque bougie Heikin Ashi haussière, et inversement vers 0 lorsque baissière.
L'avantage est que cet indicateur a peu de bruit comparé au RSI, mais peu de lag aussi comparé au Schaff Trend Cycle, qui sont les deux indicateurs qui m'ont inspiré pour la création de celui-ci.
Utilisation :
En régle général, en dessous de 15 HA Count indique une sur-vente et au-dessus de 85 un sur-achat.
Le paramétrage de la longueur pour le comptage de bougie permet d'obtenir un indicateur moins sensible lorsque proche de 1 et plus sensible lorsqu'il est à 2 ou supérieur.
Choisie comme valeur par défaut, 1.15 semble donner les meilleures indications, peu importe le marché ou la période de temps.
En outre cela ressemble beaucoup aux valeurs que pourrait donner le RSI régler sur 14 périodes, ainsi il peut être utilisé de la même manière. Notamment pour ce qui est des divergences.
Indicator
