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Renko RSIThis is live and non-repainting Renko RSI tool. The tool has it’s own engine and not using integrated function of Trading View. Renko charts ignore time and focus solely on price changes that meet a minimum requirement. Time is not a factor on Renko chart but as you can see with this script Renko RSI created on time chart. Renko chart provide several advantages, some of them are filtering insignificant price movements and noise, focusing on important price movements and making support/resistance levels much easier to identify. As source Closing price or High/Low can be used. Traditional or ATR can be used for scaling. If ATR is chosen then there is rounding algorithm according to mintick value of the security. For example if mintick value is 0.001 and brick size (ATR/Percentage) is 0.00124 then box size becomes 0.001. And also while using dynamic brick size (ATR), box size changes only when Renko closing price changed. Renko RSI is calculated by own Renko RSI algorithm. Alerts added: Renko RSI moved below Overbought level Renko RSI moved above Overbought level Renko RSI moved below Oversold level Renko RSI moved above Oversold level RSI length is 2 by default, you can set as you wish. You better to use this script with the following one: Enjoy!
Pine Script® indicator
by LonesomeTheBlue
18
BitMEX pump catcher - MACDThis is a modified version of the BitMEX pump catcher by Jomy . I have tweaked the algorithm to use the difference in MACD to get the correct direction of entries rather than using direction of candles which are not always indicative of trend direction. These changes increase net profit, profitable trades, while reducing drawdown. Below is a copy and paste of Jomy's explanation of the algorithm. What is going on here? This strategy is pretty simple. We start by measuring a very long chunk of volume history on BitMEX:XBTUSD 1 hour chart to find out if the current volume is high or low. At 1.0 the indicator is showing we are at 100% of normal historical volume . The blue line is a measure of recent volume! This indicator gets interested when the volume drops below 90% of the regular volume (0.9), and then comes back up over 90%. There's usually a pump of increased price activity during this time. When the 0.9 line is crossed by the blue line, the indicator surveys the last 2 bars of price action to figure out which way we're going, long or short. Green is long. Red is short. To exit the trade we use a 7 period fast ema of the volume crossing under an 11 ema slower period which shows declining interest in the market signifying an end to the pump or dump. The profit factor is quite high with 5x leverage, but historically we see 50% drawdown -- very risky. 1x leverage looks nice and tight with very low drawdown. Play with the inputs to see what matches your own risk profile. I would not recommend taking this into much lower timeframes as trading fees are not included in the profit calculations. Please don't get burned trading on stupid high leverage. This indicator is probably not going to work well on alts, as Bitcoin FOMO build up and behavior is different. This whole indicator is tuned to Bitcoin , and attempts to trade only the meatiest part of the market moves. Jomy should get full credit to this indicator
Pine Script® strategy
by ahancock
27
[Autoview][BackTest] Blank R0.13BThis is a fork of JustUncleL's Dual MA Ribbons R0.13 It is now a blank template for making new strategies / alerts for autoview The changes are as follows: Removed actual algo Establish functions for long Signal, long Close Signal and short Signal, short Close Signal to minimize the places code must be edited to update / replace algos Make allow Long and allow short and invert trade directions independent options Added support for alternate candle types Added autoset backtest period feature, and optional coloring Moved strategy calls in to functions so they can all be commented out or activated / disabled in a single block at the top of the script
Pine Script® strategy
by yatrader2
1
[Autoview][Alerts]Blank R0.13BThis is a fork of JustUncleL's Dual MA Ribbons R0.13 It is now a blank template for making new strategies / alerts for autoview The changes are as follows: Removed actual algo Establish functions for long Signal, long Close Signal and short Signal, short Close Signal to minimize the places code must be edited to update / replace algos Make allow Long and allow short and invert trade directions independent options Added support for alternate candle types Added autoset backtest period feature, and optional coloring Moved strategy calls in to functions so they can all be commented out or activated / disabled in a single block at the top of the script
Pine Script® indicator
by yatrader2
3
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
Pine Script® indicator
by jayy
16
Volume Range EventsChanges in the feelings (positive, negative, neutral) in the market concerning the valuation of an instrument are often preceded with sudden outbursts of buying and selling frenzies. The aim of this indicator is to report such outbursts. We can see them as expansions of volume, sometimes 10 times more than usual. and as extensions of the trading range, also sometimes 10 times more than usual (e.g. usual range is 10 cent suddenly a whole dollar.) The changes are calculated in such a way that these fit between plus and minus 100 percent, the bars are scaled in some sort of logarithmic way. The Emoline is the same as the one in the True Balance of Power indicator, which I already published ONLY RISES ARE EVENTS Sometimes analysts are tempted to give meaning to low volume or small ranges. These simply mean that the market has little interest in trading this instrument. I believe that in such cases the trader needs to wait for expansion and extension events to happen, then he can make a better guess of where the market is heading. As events often mark the beginning or ending of a trend, this indicator provides an early and clear signal, because it doesn’t bother us about non-events. WHAT IS USUAL? If the algorithm would use an average as a normal to scale volume or range events, then previous peaks will act as spoilers by making the average so high that a following peak is scaled too small. I developed a function, usual() , that kicks out all extremes of a ‘population of values’ and which returns the average of the non-extreme values. It can be called with any serial. This function is called by both algorithms that report volume and range peaks, which guarantees that the results are really comparable. As this function has a fixed look back of 8 periods, we might state that ‘usual’ is a short lived relative value. I think this doesn’t matter for the practical use of the indicator. COLORING AND INTERPRETATION I follow the categories in the ‘Better Volume Indicator’, published by LeazyBear, these are: 1. Climactic Volumes, event >40 % (this means peak is 1.5 X usual) LIME: Climax Buying Volume, direction up, range event also > 30 % RED: Climax Selling Volume, direction down, range event also > 30 % AQUA: Climax Churning Volume, both directions, range event < 30% 2. Smaller Volumes, event <40 % GREEN: Supportive Volume, both directions, if combined with range event BLUE: Churning Volume, both directions, if not combined with range event (Professional Trading) 3. Just Range Events BLACK histogram bars (Amateurish Trading)
Pine Script® indicator
by eykpunter
7
BUY & SELL VOLUME TO PRICE PRESSURE by @XeL_ArjonaBUY & SELL PRICE TO VOLUME PRESSURE By Ricardo M Arjona @XeL_Arjona DISCLAIMER: The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is. Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of: Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by: Stocks & Commodities V. 21:10 (68-72): "Bull And Bear Balance Indicator by Vadim Gimelfarb" Normalisation (Filter) from Karthik Marar's VSA work: karthikmarar.blogspot.mx Buy to Sell Convergence / Divergence and Volume Pressure Counterforce Histogram Ideas by: @XeL_Arjona WHAT IS THIS? The following indicators try to acknowledge in a K-I-S-S approach to the eye (Keep-It-Simple-Stupid), the two most important aspects of nearly every trading vehicle: -- PRICE ACTION IN RELATION BY IT'S VOLUME -- Volume Pressure Histogram: Columns plotted in positive are considered the dominant Volume Force for the given period. All "negative" columns represents the counterforce Vol.Press against the dominant. Buy to Sell Convergence / Divergence: It's a simple adaptation of the popular "Price Percentage Oscillator" or MACD but taking Buying Pressure against Selling Pressure Averages, so given a Positive oscillator reading (>0) represents Bullish dominant Trend and a Negative reading (<0) a Bearish dominant Trend. Histogram is the diff between RAW Volume Pressures Convergence/Divergence minus Normalised ones (Signal) which helps as a confirmation. Volume bars are by default plotted from RAW Volume Pressure algorithms, but they can be as well filtered with Karthik Marar's approach against a "Total Volume Average" in favor to clean day to day noise like HFT. ALL NEW IDEAS OR MODIFICATIONS to these indicators are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter: @XeL_Arjona Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. -- 2015
Pine Script® indicator
by xel_arjona
39
BUY & SELL VOLUME TO PRICE PRESSURE by @XeL_ArjonaBUY & SELL PRICE TO VOLUME PRESSURE By Ricardo M Arjona @XeL_Arjona DISCLAIMER: The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is. Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of: Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by: Stocks & Commodities V. 21:10 (68-72): "Bull And Bear Balance Indicator by Vadim Gimelfarb" Normalisation (Filter) from Karthik Marar's VSA work: karthikmarar.blogspot.mx Buy to Sell Convergence / Divergence and Volume Pressure Counterforce Histogram Ideas by: @XeL_Arjona WHAT IS THIS? The following indicators try to acknowledge in a K-I-S-S approach to the eye (Keep-It-Simple-Stupid), the two most important aspects of nearly every trading vehicle: -- PRICE ACTION IN RELATION BY IT'S VOLUME -- Volume Pressure Histogram: Columns plotted in positive are considered the dominant Volume Force for the given period. All "negative" columns represents the counterforce Vol.Press against the dominant. Buy to Sell Convergence / Divergence: It's a simple adaptation of the popular "Price Percentage Oscillator" or MACD but taking Buying Pressure against Selling Pressure Averages, so given a Positive oscillator reading (>0) represents Bullish dominant Trend and a Negative reading (<0) a Bearish dominant Trend. Histogram is the diff between RAW Volume Pressures Convergence/Divergence minus Normalised ones (Signal) which helps as a confirmation. Volume bars are by default plotted from RAW Volume Pressure algorithms, but they can be as well filtered with Karthik Marar's approach against a "Total Volume Average" in favor to clean day to day noise like HFT. ALL NEW IDEAS OR MODIFICATIONS to these indicators are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter: @XeL_Arjona Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. -- 2015
Pine Script® indicator
by xel_arjona
12
BUY & SELL VOLUME PRESSURE by @XeL_ArjonaBUY & SELL PRICE TO VOLUME PRESSURE By Ricardo M Arjona @XeL_Arjona DISCLAIMER: The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is. Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of: Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by: Stocks & Commodities V. 21:10 (68-72): "Bull And Bear Balance Indicator by Vadim Gimelfarb" Normalisation (Filter) from Karthik Marar's VSA work: karthikmarar.blogspot.mx Buy to Sell Convergence / Divergence and Volume Pressure Counterforce Histogram Ideas by: @XeL_Arjona WHAT IS THIS? The following indicators try to acknowledge in a K-I-S-S approach to the eye (Keep-It-Simple-Stupid), the two most important aspects of nearly every trading vehicle: -- PRICE ACTION IN RELATION BY IT'S VOLUME -- Volume Pressure Histogram: Columns plotted in positive are considered the dominant Volume Force for the given period. All "negative" columns represents the counterforce Vol.Press against the dominant. Buy to Sell Convergence / Divergence: It's a simple adaptation of the popular "Price Percentage Oscillator" or MACD but taking Buying Pressure against Selling Pressure Averages, so given a Positive oscillator reading (>0) represents Bullish dominant Trend and a Negative reading (<0) a Bearish dominant Trend. Histogram is the diff between RAW Volume Pressures Convergence/Divergence minus Normalised ones (Signal) which helps as a confirmation. Volume bars are by default plotted from RAW Volume Pressure algorithms, but they can be as well filtered with Karthik Marar's approach against a "Total Volume Average" in favor to clean day to day noise like HFT. ALL NEW IDEAS OR MODIFICATIONS to these indicators are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter: @XeL_Arjona Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. -- 2015
Pine Script® indicator
by xel_arjona
13
DTC Intra+DTC Intra+ Complete Indian Intraday Trading Indicator What This Indicator Does: DTC Intra+ is a comprehensive intraday trading indicator designed specifically for Indian markets. It provides real-time session analysis, volume profiling, and technical insights that work consistently across all timeframes. Key Features: Multi-Timeframe Data Consistency Solves the common problem where indicators show different values on different timeframes Gap percentage, ADR (Average Daily Range), and Burst values remain consistent whether viewing 1-minute or daily charts Uses proprietary algorithms to fetch daily data and apply it accurately to intraday calculations Intelligent Session Detection Automatically detects and displays three Indian market sessions: Morning (9:15-11:00 AM), Mid-Day (11:00-1:30 PM), Afternoon (1:30-3:30 PM) Creates visual session boxes that extend dynamically and finalize at session boundaries Each session maintains distinct colors and labels for easy identification Advanced Volume Analysis Calculates Relative Volume (RVol) using 21-period moving average for volume strength assessment Colors candles based on volume strength: high/moderate bullish and bearish volume patterns Customizable volume thresholds (150% and 200% of average volume) for precise signal generation Pattern Recognition System Identifies mini-coil consolidation patterns with customizable styling options Maintains visual persistence across timeframes and chart updates Configurable lookback periods and pattern validation algorithms Technical Analysis Tools Four customizable Moving Averages (10, 20, 50, 200) with multiple calculation types (SMA, EMA, WMA, HMA) VWAP integration with theme-adaptive styling Gap analysis with customizable thresholds (1% and 2%+) and visual alerts Theme-Adaptive Interface Automatically detects and adapts to dark or light chart themes Professional color schemes optimized for both theme types Customizable transparency and styling for all visual elements Information Dashboard Dynamic information table displaying Gap %, RVol, ADR, Burst, Sector, Industry, Theme, and Session data Real-time sector and industry classification from TradingView data Burst Ranker with descriptive labels (GREAT, GOOD, LOW) based on historical performance analysis How It Works: Session Management: The indicator uses time-based detection algorithms to identify Indian market sessions, creating visual boxes that extend dynamically and finalize at session boundaries. Each session maintains its own color scheme and label system. Data Consistency Engine: Proprietary cross-timeframe calculation system ensures that daily metrics display consistently across all timeframes by fetching daily data and applying it to intraday calculations. Volume Profiling: Custom volume analysis algorithms calculate relative volume strength and apply color coding to candles based on volume thresholds and price direction, providing immediate visual feedback on market activity. Pattern Detection: Advanced consolidation pattern recognition system that identifies mini-coil formations using customizable parameters and maintains visual persistence across chart updates. How To Use: Apply to any Indian stock chart (BSE, NSDL) on intraday timeframes Session times are pre-configured for Indian markets but can be customized Moving Averages can be adjusted to your preferred lengths and calculation types Volume thresholds can be modified based on your trading strategy Monitor the information panel for real-time market insights Use session boxes to identify optimal trading windows Who This Is For: Indian intraday traders seeking comprehensive market analysis Traders who need consistent data across multiple timeframes Volume-based traders requiring real-time volume strength analysis Technical analysts needing session-based market structure insights Busy professionals who want market insights without constant chart monitoring What Makes It Unique: Unlike basic session indicators, DTC Intra+ provides cross-timeframe data consistency, advanced volume profiling, and comprehensive Indian market analysis in a single, theme-adaptive interface. The proprietary algorithms ensure accurate daily metrics on intraday charts, making it essential for serious Indian market traders who need reliable, consistent data across all timeframes. The Bottom Line: This indicator transforms how you view Indian intraday markets by providing consistent, reliable data across all timeframes while offering advanced session analysis, volume profiling, and pattern recognition. It's designed specifically for Indian market characteristics and trading patterns, giving you the tools to trade with confidence and precision.
Pine Script® indicator
by rohit_trades212
1
Lorentzian Key Support and Resistance Level Detector [mishy]🧮 Lorentzian Key S/R Levels Detector Advanced Support & Resistance Detection Using Mathematical Clustering The Problem Traditional S/R indicators fail because they're either subjective (manual lines), rigid (fixed pivots), or break when price spikes occur. Most importantly, they don't tell you where prices actually spend time, just where they touched briefly. The Solution: Lorentzian Distance Clustering This indicator introduces a novel approach by using Lorentzian distance instead of traditional Euclidean distance for clustering. This is groundbreaking for financial data analysis. Data Points Clustering: 🔬 Why Euclidean Distance Fails in Trading Traditional K-means uses Euclidean distance: • Formula: distance = (price_A - price_B)² • Problem: Squaring amplifies differences exponentially • Real impact: One 5% price spike has 25x more influence than a 1% move • Result: Clusters get pulled toward outliers, missing real support/resistance zones Example scenario: Prices: ← flash spike Euclidean: Centroid gets dragged toward 150 Actual S/R zone: Around 100 (where prices actually trade) ⚡ Lorentzian Distance: The Game Changer Our approach uses Lorentzian distance: • Formula: distance = log(1 + (price_difference)² / σ²) • Breakthrough: Logarithmic compression keeps outliers in check • Real impact: Large moves still matter, but don't dominate • Result: Clusters focus on where prices actually spend time Same example with Lorentzian: Prices: ← flash spike Lorentzian: Centroid stays near 100 (real trading zone) Outlier (150): Acknowledged but not dominant 🧠 Adaptive Intelligence The σ parameter isn't fixed,it's calculated from market disturbance/entropy: • High volatility: σ increases, making algorithm more tolerant of large moves • Low volatility: σ decreases, making algorithm more sensitive to small changes • Self-calibrating: Adapts to any instrument or market condition automatically Why this matters: Traditional methods treat a 2% move the same whether it's in a calm or volatile market. Lorentzian adapts the sensitivity based on current market behavior. 🎯 Automatic K-Selection (Elbow Method) Instead of guessing how many S/R levels to draw, the indicator: • Tests 2-6 clusters and calculates WCSS (tightness measure) • Finds the "elbow" - where adding more clusters stops helping much • Uses sharpness calculation to pick the optimal number automatically Result: Perfect balance between detail and clarity. How It Works 1. Collect recent closing prices 2. Calculate entropy to adapt to current market volatility 3. Cluster prices using Lorentzian K-means algorithm 4. Auto-select optimal cluster count via statistical analysis 5. Draw levels at cluster centers with deviation bands 📊 Manual K-Selection Guide (Using WCSS & Sharpness Analysis) When you disable auto-selection, use both WCSS and Sharpness metrics from the analysis table to choose manually: What WCSS tells you: • Lower WCSS = tighter clusters = better S/R levels • Higher WCSS = scattered clusters = weaker levels What Sharpness tells you: • Higher positive values = optimal elbow point = best K choice • Lower/negative values = poor elbow definition = avoid this K • Measures the "sharpness" of the WCSS curve drop-off Decision strategy using both metrics: K=2: WCSS = 150.42 | Sharpness = - | Selected = K=3: WCSS = 89.15 | Sharpness = 22.04 | Selected = ✓ ← Best choice K=4: WCSS = 76.23 | Sharpness = 1.89 | Selected = K=5: WCSS = 73.91 | Sharpness = 1.43 | Selected = Quick decision rules: • Pick K with highest positive Sharpness (indicates optimal elbow) • Confirm with significant WCSS drop (30%+ reduction is good) • Avoid K values with negative or very low Sharpness (<1.0) • K=3 above shows: Big WCSS drop (41%) + High Sharpness (22.04) = Perfect choice Why this works: The algorithm finds the "elbow" where adding more clusters stops being useful. High Sharpness pinpoints this elbow mathematically, while WCSS confirms the clustering quality. Elbow Method Visualization: Traditional clustering problems: ❌ Price spikes distort results ❌ Fixed parameters don't adapt ❌ Manual tuning is subjective ❌ No way to validate choices Lorentzian solution: ☑️ Outlier-resistant distance metric ☑️ Entropy-based adaptation to volatility ☑️ Automatic optimal K selection ☑️ Statistical validation via WCSS & Sharpness Features Visual: • Color-coded levels (red=highest resistance, green=lowest support) • Optional deviation bands showing cluster spread • Strength scores on labels: Each cluster shows a reliability score. • Higher scores (0.8+) = very strong S/R levels with tight price clustering • Lower scores (0.6-0.7) = weaker levels, use with caution • Based on cluster tightness and data point density • Clean line extensions and labels Analytics: • WCSS analysis table showing why K was chosen • Cluster metrics and statistics • Real-time entropy monitoring Control: • Auto/manual K selection toggle • Customizable sample size (20-500 bars) • Show/hide bands and metrics tables The Result You get mathematically validated S/R levels that focus on where prices actually cluster, not where they randomly spiked. The algorithm adapts to market conditions and removes guesswork from level selection. Best for: Traders who want objective, data-driven S/R levels without manual chart analysis. Credits: This script is for educational purposes and is inspired by the work of @ThinkLogicAI and an amazing mentor @DskyzInvestments . It demonstrates how Lorentzian geometrical concepts can be applied not only in ML classification but also quite elegantly in clustering.
Pine Script® indicator
by mishy_Champ
6
GTrader-ICT All In One-Comumnity VersionMeet the **GTrader-ICT All In One **, a comprehensive toolkit designed to integrate key Inner Circle Trader (ICT) concepts directly onto your chart. This powerful overlay indicator consolidates multiple essential tools, streamlining your technical analysis and helping you identify key temporal and price-based events. 📚 References & Inspiration This indicator stands on the shoulders of giants. With the help of **tradeforopp** and **LuxAlgo**. The concepts and some implementation details were referenced from the following excellent, publicly available scripts: ICT Killzones: The session drawing and pivot logic is adapted from tradeforopp ICT Macros: The macro detection and plotting functionality is inspired by the work of Lux Algo , particularly their widely-used indicators covering ICT concepts. 🎯 Core Features * **ICT Killzones:** Visualize critical trading sessions with customizable boxes. You can easily toggle and style the **Asia**, **London**, and **New York (AM, Lunch, PM)** sessions to focus on the liquidity and volatility that matter most to your strategy. * Fully customizable session times and colors. * Timezone support to align sessions with your local or preferred trading time (defaults to `America/New_York`). * **ICT Macros:** Automatically identify and plot specific, short-duration time windows where institutional algorithms are known to be active (e.g., `09:50-10:10`, `14:50-15:10`, etc.). * Plots the high/low range of the macro, providing clear levels of interest. * Utilizes 1-minute data for precision, even when viewing on 3-minute or 5-minute charts. 📚 Optimization over the other original indicators We add the custom input for macros session, users just need to input the from/to hour: minute format, and they will be converted into session objects in pinescript The macro draws function is optimized, removing redundant draws, leading to better performance Add "Distance from Macro Line to Chart" option Add "Session Drawings Limit" for better performance ⚠️ Notes on TradingView Warnings You may encounter some warnings from TradingView when using this script. These are generally expected due to the script's advanced, event-driven nature: 1. **Function Call Consistency:** The function 'box.new' should be called on each calculation for consistency, which may appear. This happens because drawing elements (like session boxes) are intentionally created only on the *first bar* of a new session, not on every single bar. This is a necessary design choice for performance and to prevent duplicate drawings. 2. **Potential for Repainting/Slow Load:** The **Macro** feature uses the `request.security_lower_tf()` function to get accurate 1-minute data. This can trigger warnings about performance or slow loading times. This is a known trade-off for achieving the precision required for the feature.
Pine Script® indicator
by GTrader_indicators
6
Machine Learning | Adaptive Trend Signals [Bitwardex]⚙️🧠Machine Learning | Adaptive Trend Signals 🔷Overview Machine Learning | Adaptive Trend Signals is a Pine Script™ v6 indicator designed to visualize market trends and generate signals through a combination of volatility clustering, Gaussian smoothing, and adaptive trend calculations. Built as an overlay indicator, it integrates advanced techniques inspired by machine learning concepts, such as K-Means clustering, to adapt to changing market conditions. The script is highly customizable, includes a backtesting module, and supports alert conditions, making it suitable for traders exploring trend-based strategies and developers studying volatility-driven indicator design. 🔷Functionality The indicator performs the following core functions: • Volatility Clustering: Uses K-Means clustering to categorize market volatility into high, medium, and low states, adjusting trend sensitivity accordingly. • Trend Calculation: Computes adaptive trend lines (SmartTrend) based on volatility-adjusted standard deviation, smoothed RSI, and ADX filters. • Signal Generation: Identifies potential buy and sell points through trend line crossovers and directional confirmation. • Backtesting Module: Tracks trade outcomes based on the SmartTrend3 value, displaying win rate and total trades. • Visualization: Plots trend lines with gradient colors and optional signal markers (bullish 🐮 and bearish 🐻). • Alerts: Provides configurable alerts for trend shifts and volatility state changes. 🔷Technical Methodology Volatility Clustering with K-Means The indicator employs a K-Means clustering algorithm to classify market volatility, measured via the Average True Range (ATR), into three distinct clusters: • Data Collection: Gathers ATR values over a user-defined training period (default: 100 bars). • Centroid Initialization: Sets initial centroids at the highest, lowest, and midpoint ATR values within the training period. • Iterative Clustering: Assigns ATR data points to the nearest centroid, recalculates centroid means, and repeats until convergence. • Dynamic Adjustment: Assigns a volatility state (high, medium, or low) based on the closest centroid, adjusting the trend factor (e.g., tighter for high volatility, wider for low volatility). This approach allows the indicator to adapt its sensitivity to varying market conditions, providing a data-driven foundation for trend calculations. 🔷Gaussian Smoothing To enhance signal clarity and reduce noise, the indicator applies Gaussian kernel smoothing to: • RSI: Smooths the Relative Strength Index (calculated from OHLC4) to filter short-term fluctuations. • SmartTrend: Smooths the primary trend line for a more stable output. The Gaussian kernel uses a sigma value derived from the user-defined smoothing length, ensuring mathematically consistent noise reduction. 🔷SmartTrend Calculation The pineSmartTrend function is the core of the indicator, producing three trend lines: • SmartTrend: The primary trend line, calculated using a volatility-adjusted standard deviation, smoothed RSI, and ADX conditions. • SmartTrend2: A secondary trend line with a wider factor (base factor * 1.382) for signal confirmation. SmartTrend3: The average of SmartTrend and SmartTrend2, used for plotting and backtesting. Key components of the calculation include: • Dynamic Standard Deviation: Scales based on ATR relative to its 50-period smoothed average, with multipliers (1.0 to 1.4) applied according to volatility thresholds. • RSI and ADX Filters: Requires RSI > 50 for bullish trends or < 50 for bearish trends, alongside ADX > 15 and rising to confirm trend strength. Volatility-Adjusted Bands: Constructs upper and lower bands around price action, adjusted by the volatility cluster’s dynamic factor. 🔷Signal Generation The generate_signals function generates signals as follows: • Buy Signal: Triggered when SmartTrend crosses above SmartTrend2 and the price is above SmartTrend, with directional confirmation. • Sell Signal: Triggered when SmartTrend crosses below SmartTrend2 and the price is below SmartTrend, with directional confirmation. Directional Logic: Tracks trend direction to filter out conflicting signals, ensuring alignment with the broader market context. Signals are visualized as small circles with bullish (🐮) or bearish (🐻) emojis, with an option to toggle visibility. 🔷Backtesting The get_backtest function evaluates signal outcomes using the SmartTrend3 value (rather than closing prices) to align with the trend-based methodology. It tracks: • Total Trades: Counts completed long and short trades. • Win Rate: Calculates the percentage of trades where SmartTrend3 moves favorably (higher for longs, lower for shorts). Position Management: Closes opposite positions before opening new ones, simulating a single-position trading system. Results are displayed in a table at the top-right of the chart, showing win rate and total trades. Note that backtest results reflect the indicator’s internal logic and should not be interpreted as predictive of real-world performance. 🔷Visualization and Alerts • Trend Lines: SmartTrend3 is plotted with gradient colors reflecting trend direction and volatility cluster, accompanied by a secondary line for visual clarity. • Signal Markers: Optional buy/sell signals are plotted as small circles with customizable colors. • Alerts: Supports alerts for: • Bullish and bearish trend shifts (confirmed on bar close). Transitions to high, medium, or low volatility states. 🔷Input Parameters • ATR Length (default: 14): Period for ATR calculation, used in volatility clustering. • Period (default: 21): Common period for RSI, ADX, and standard deviation calculations. • Base SmartTrend Factor (default: 2.0): Base multiplier for volatility-adjusted bands. • SmartTrend Smoothing Length (default: 10): Length for Gaussian smoothing of the trend line. • Show Buy/Sell Signals? (default: true): Enables/disables signal markers. • Bullish/Bearish Color: Customizable colors for trend lines and signals. 🔷Usage Instructions • Apply to Chart: Add the indicator to any TradingView chart. • Configure Inputs: Adjust parameters to align with your trading style or market conditions (e.g., shorter ATR length for faster markets). • Interpret Output: • Trend Lines: Use SmartTrend3’s direction and color to gauge market bias. • Signals: Monitor bullish (🐮) and bearish (🐻) markers for potential entry/exit points. • Backtest Table: Review win rate and total trades to understand the indicator’s behavior in historical data. • Set Alerts: Configure alerts for trend shifts or volatility changes to support manual or automated trading workflows. • Combine with Analysis: Use the indicator alongside other tools or market context, as it is designed to complement, not replace, comprehensive analysis. 🔷Technical Notes • Data Requirements: Requires at least 100 bars for accurate volatility clustering. Ensure sufficient historical data is loaded. • Market Suitability: The indicator is designed for trend detection and may perform differently in ranging or volatile markets due to its reliance on RSI and ADX filters. • Backtesting Scope: The backtest module uses SmartTrend3 values, which may differ from price-based outcomes. Results are for informational purposes only. • Computational Intensity: The K-Means clustering and Gaussian smoothing may increase processing time on lower timeframes or with large datasets. 🔷For Developers The script is modular, well-commented, encouraging reuse and modification with proper attribution. Key functions include: • gaussianSmooth: Applies Gaussian kernel smoothing to any data series. • pineSmartTrend: Computes adaptive trend lines with volatility and momentum filters. • getDynamicFactor: Adjusts trend sensitivity based on volatility clusters. • get_backtest: Evaluates signal performance using SmartTrend3. Developers can extend these functions for custom indicators or strategies, leveraging the volatility clustering and smoothing methodologies. The K-Means implementation is particularly useful for adaptive volatility analysis. 🔷Limitations • The indicator is not predictive and should be used as part of a broader trading strategy. • Performance varies by market, timeframe, and parameter settings, requiring user experimentation. • Backtest results are based on historical data and internal logic, not real-world trading conditions. • Volatility clustering assumes sufficient historical data; incomplete data may affect accuracy. 🔷Acknowledgments Developed by Bitwardex, inspired by machine learning concepts and adaptive trading methodologies. Community feedback is welcome via TradingView’s platform. 🔷 Risk Disclaimer Trading involves significant risks, and most traders may incur losses. Bitwardex AI Algo is provided for informational and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument . The signals, metrics, and features are tools for analysis and do not guarantee profits or specific outcomes. Past performance is not indicative of future results. Always conduct your own due diligence and consult a financial advisor before making trading decisions.
Pine Script® indicator
by bitwardex
1
Altcoin Reversal or Correction DetectionINDICATOR OVERVIEW: Altcoin Reversal or Correction Detection Altcoin Reversal or Correction Detection is a powerful crypto-specific indicator designed exclusively for altcoins by analyzing their RSI values across multiple timeframes alongside Bitcoin’s RSI. Since BTC's price movements have a strong influence on altcoins, this tool helps traders better understand whether a reversal or correction signal is truly reliable or just noise. Even if an altcoin appears oversold or overbought, it may continue trending with BTC—so this indicator gives you the full picture. The indicator is optimized for CRYPTO MARKETS only. Not suitable for BTC itself—this is a precision tool built only for ALTCOINS only. This indicator is not only for signals but also serves as a tool for observing all the information from different timeframes of BTC and altcoins collectively. How the Calculation Works: Algorithm Overview The Altcoin Reversal or Correction Detection indicator relies on an algorithm that compares the RSI values of the altcoin across multiple timeframes with Bitcoin's RSI values. This allows the indicator to identify key market moments where a reversal or correction might occur. BTC-Altcoin RSI Correlation: The algorithm looks for the correlation between Bitcoin's price movements and the altcoin's price actions, as BTC often influences the direction of altcoins. When both Bitcoin and the altcoin show either overbought or oversold conditions in a significant number of timeframes, the indicator signals the potential for a reversal or correction. Multi-Timeframe Confirmation: Unlike traditional indicators that may focus on a single timeframe, this tool checks multiple timeframes for both BTC and the altcoin. When the same overbought/oversold conditions are met across multiple timeframes, it confirms the likelihood of a trend reversal or correction, providing a more reliable signal. The more timeframes that align with this pattern, the stronger the signal becomes. Overbought/Oversold Conditions & Extreme RSI Values: The algorithm also takes into account the size of the RSI values, especially focusing on extreme overbought and oversold levels. The greater the RSI values are in these extreme regions, the stronger the potential reversal or correction signal. This means that not only do multiple timeframes need to confirm the condition, but the magnitude of the overbought or oversold RSI level plays a crucial role in determining the strength of the signal. Signal Strength Levels: The signals are classified into three levels: Early Signal Strong Signal Very Strong Signal By taking into account the multi-timeframe analysis of both BTC and the altcoin RSI values, along with the magnitude of these RSI values, the indicator offers a highly reliable method for detecting potential reversals and corrections. Who Is This Indicator Suitable For? This indicator can also be used to detect reversal points, but it is especially effective for scalping. It highlights potential correction points, making it perfect for quick entries during smaller market pullbacks or short-term trend shifts, which is more suitable for scalpers looking to capitalize on short-term movements Integration with other tools Use this tool alongside key Support and Resistance zones to further enhance your trade by filtering for even better quality entries and focusing only on high-quality reversal or correction setups. It can be also used with other indicators and suitable with other personalised strategies.
Pine Script® indicator
by ebecihalil
ThinkTech AI SignalsThink Tech AI Strategy The Think Tech AI Strategy provides a structured approach to trading by integrating liquidity-based entries, ATR volatility thresholds, and dynamic risk management. This strategy generates buy and sell signals while automatically calculating take profit and stop loss levels, boasting a 64% win rate based on historical data. Usage The strategy can be used to identify key breakout and retest opportunities. Liquidity-based zones act as potential accumulation and distribution areas and may serve as future support or resistance levels. Buy and sell zones are identified using liquidity zones and ATR-based filters. Risk management is built-in, automatically calculating take profit and stop loss levels using ATR multipliers. Volume and trend filtering options help confirm directional bias using a 50 EMA and RSI filter. The strategy also allows for session-based trading, limiting trades to key market hours for higher probability setups. Settings The risk/reward ratio can be adjusted to define the desired stop loss and take profit calculations. The ATR length and threshold determine ATR-based breakout conditions for dynamic entries. Liquidity period settings allow for customized analysis of price structure for support and resistance zones. Additional trend and RSI filters can be enabled to refine trade signals based on moving averages and momentum conditions. A session filter is included to restrict trade signals to specific market hours. Style The strategy includes options to display liquidity lines, showing key support and resistance areas. The first 15-minute candle breakout zones can also be visualized to highlight critical market structure points. A win/loss statistics table is included to track trade performance directly on the chart. This strategy is intended for descriptive analysis and should be used alongside other confluence factors. Optimize your trading process with Think Tech AI today!
Pine Script® strategy
by Theonealgo
Mark Hours/Minutes (Formula + Minutes)This Pine Script code is a TradingView indicator that analyzes the hour and minutes of each candle in a 1-minute timeframe and plots a red triangle above the candle if one of the following conditions is met: Sum/Difference Condition: The sum or the absolute difference of the hours and minutes is equal to 29, 35, or 71, with a tolerance of +/- 1. Minutes Condition: The minutes are equal to 00, 29, or 35. This indicator is based on the Goldbach theory and the "algo path" concept popularized by Hopiplaka, which posits that algorithmic trading paths often initiate from minute values of 00, 29, and 35. Use this indicator according to your trading strategy.
Pine Script® indicator
by Lingio78
Stop/Take BoundsThe Stop/Take Bounds indicator is tool for setting dynamic stop-loss and take-profit levels based on percentage distance from the price. Unlike traditional ATR-based methods, this indicator allows traders to set stop levels as a fixed percentage of the price and define the take-profit multiple. - Stop-loss distanceis determined as a percentage of the current price (e.g., 1% means the stop-loss is always 1% away from the price). - Take-profit distance is calculated by multiplying the stop-loss distance by a user-defined multiplier (e.g., a multiplier of 2 places the take-profit level twice as far as the stop-loss). - The indicator plots red lines for stop-loss levels and green lines for take-profit levels, making it easy to visualize risk-to-reward scenarios. How to Use 1. Set Stop-Loss Distance (%) – Define how far the stop-loss should be from the price. 2. Set Take-Profit Multiplier – Choose how many times larger the take-profit should be compared to the stop-loss. 3. Apply to Long and Short Trades – The indicator automatically plots levels for both long and short positions. 4. Use in Manual or Algorithmic Trading – Ideal for discretionary traders as well as for integration into algorithmic strategies. Use Cases - Risk Management – Helps maintain disciplined risk-to-reward ratios. - Strategy Development – Can be used in the creation of algorithmic trading systems. - Trailing Stop Simulation – Can act as a trailing stop mechanism when used dynamically. This indicator is a great addition to any trading strategy!
Pine Script® indicator
by Y_Goldman
Quarterly Theory ICT 01 [TradingFinder] XAMD + Q1-Q4 Sessions🔵 Introduction The Quarterly Theory ICT indicator is an advanced analytical system based on the concepts of ICT (Inner Circle Trader) and fractal time. It divides time into quarterly periods and accurately determines entry and exit points for trades by using the True Open as the starting point of each cycle. This system is applicable across various time frames including annual, monthly, weekly, daily, and even 90-minute sessions. Time is divided into four quarters: in the first quarter (Q1), which is dedicated to the Accumulation phase, the market is in a consolidation state, laying the groundwork for a new trend; in the second quarter (Q2), allocated to the Manipulation phase (also known as Judas Swing), sudden price changes and false moves occur, marking the true starting point of a trend change; the third quarter (Q3) is dedicated to the Distribution phase, during which prices are broadly distributed and price volatility peaks; and the fourth quarter (Q4), corresponding to the Continuation/Reversal phase, either continues or reverses the previous trend. By leveraging smart algorithms and technical analysis, this system identifies optimal price patterns and trading positions through the precise detection of stop-run and liquidity zones. With the division of time into Q1 through Q4 and by incorporating key terms such as Quarterly Theory ICT, True Open, Accumulation, Manipulation (Judas Swing), Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, this system enables traders to identify market trends and make informed trading decisions using real data and precise analysis. ♦ Important Note : This indicator and the "Quarterly Theory ICT" concept have been developed based on material published in primary sources, notably the articles on Daye( traderdaye ) and Joshuuu . All copyright rights are reserved. 🔵 How to Use The Quarterly Theory ICT strategy is built on dividing time into four distinct periods across various time frames such as annual, monthly, weekly, daily, and even 90-minute sessions. In this approach, time is segmented into four quarters, during which the phases of Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal appear in a systematic and recurring manner. The first segment (Q1) functions as the Accumulation phase, where the market consolidates and lays the foundation for future movement; the second segment (Q2) represents the Manipulation phase, during which prices experience sudden initial changes, and with the aid of the True Open concept, the real starting point of the market’s movement is determined; in the third segment (Q3), the Distribution phase takes place, where prices are widely dispersed and price volatility reaches its peak; and finally, the fourth segment (Q4) is recognized as the Continuation/Reversal phase, in which the previous trend either continues or reverses. This strategy, by harnessing the concepts of fractal time and smart algorithms, enables precise analysis of price patterns across multiple time frames and, through the identification of key points such as stop-run and liquidity zones, assists traders in optimizing their trading positions. Utilizing real market data and dividing time into Q1 through Q4 allows for a comprehensive and multi-level technical analysis in which optimal entry and exit points are identified by comparing prices to the True Open. Thus, by focusing on keywords like Quarterly Theory ICT, True Open, Accumulation, Manipulation, Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, the Quarterly Theory ICT strategy acts as a coherent framework for predicting market trends and developing trading strategies. 🔵b]Settings Cycle Display Mode: Determines whether the cycle is displayed on the chart or on the indicator panel. Show Cycle: Enables or disables the display of the ranges corresponding to each quarter within the micro cycles (e.g., Q1/1, Q1/2, Q1/3, Q1/4, etc.). Show Cycle Label: Toggles the display of textual labels for identifying the micro cycle phases (for example, Q1/1 or Q2/2). Table Display Mode: Enables or disables the ability to display cycle information in a tabular format. Show Table: Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed. Show More Info: Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle. 🔵 Conclusion Quarterly Theory ICT provides a fractal and recurring approach to analyzing price behavior by dividing time into four quarters (Q1, Q2, Q3, and Q4) and defining the True Open at the beginning of the second phase. The Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal phases repeat in each cycle, allowing traders to identify price patterns with greater precision across annual, monthly, weekly, daily, and even micro-level time frames. Focusing on the True Open as the primary reference point enables faster recognition of potential trend changes and facilitates optimal management of trading positions. In summary, this strategy, based on ICT principles and fractal time concepts, offers a powerful framework for predicting future market movements, identifying optimal entry and exit points, and managing risk in various trading conditions.
Pine Script® indicator
by TFlab
12
AO/AC Trading Zones Strategy [Skyrexio] Overview AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades. Unique Features No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs) Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions. Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one. Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one. Methodology The strategy opens long trade when the following price met the conditions: 1. Price closed above EMA (by default, period = 100). Crossover is not obligatory. 2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph) 3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital. 4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened. 5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5. 6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row. Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent. Strategy settings In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart. Justification of Methodology Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA. The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows: 1.Calculate the Smoothing Multiplier: Multiplier = 2 / (n + 1), Where n is the number of periods. 2. EMA Calculation EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier) In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend. Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages: Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead. Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward. Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward. When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades. Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either: Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal. Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal. Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy. How do these tools work together in this strategy? Let’s consider an example of an uptrend. When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish. The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals. In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades. By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics. Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends. The formula for AO is as follows: AO = SMA5(Median Price) − SMA34(Median Price) where: Median Price = (High + Low) / 2 SMA5 = 5-period Simple Moving Average of the Median Price SMA 34 = 34-period Simple Moving Average of the Median Price The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula: AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator When the AC is above the zero line and rising, it suggests accelerating upward momentum. When the AC is below the zero line and falling, it indicates accelerating downward momentum. When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum. Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types: Greed zone: when the AO and AC both are rising Red zone: when the AO and AC both are decreasing Gray zone: when one of AO or AC is rising, the other is falling Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital. Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital. Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators. Backtest Results Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions. Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks. Initial capital: 10000 USDT Percent of capital used in every trade: 10% Maximum Single Position Loss: -9.49% Maximum Single Profit: +24.33% Net Profit: +4374.70 USDT (+43.75%) Total Trades: 278 (39.57% win rate) Profit Factor: 2.203 Maximum Accumulated Loss: 668.16 USDT (-5.43%) Average Profit per Trade: 15.74 USDT (+1.37%) Average Trade Duration: 60 hours How to Use Add the script to favorites for easy access. Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT). Configure settings using the dropdown choice list in the built-in menu. Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}} Disclaimer: Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Pine Script® strategy
by Skyrexio
Arpeet MACDOverview This strategy is based on the zero-lag version of the MACD (Moving Average Convergence Divergence) indicator, which captures short-term trends by quickly responding to price changes, enabling high-frequency trading. The strategy uses two moving averages with different periods (fast and slow lines) to construct the MACD indicator and introduces a zero-lag algorithm to eliminate the delay between the indicator and the price, improving the timeliness of signals. Additionally, the crossover of the signal line and the MACD line is used as buy and sell signals, and alerts are set up to help traders seize trading opportunities in a timely manner. Strategy Principle Calculate the EMA (Exponential Moving Average) or SMA (Simple Moving Average) of the fast line (default 12 periods) and slow line (default 26 periods). Use the zero-lag algorithm to double-smooth the fast and slow lines, eliminating the delay between the indicator and the price. The MACD line is formed by the difference between the zero-lag fast line and the zero-lag slow line. The signal line is formed by the EMA (default 9 periods) or SMA of the MACD line. The MACD histogram is formed by the difference between the MACD line and the signal line, with blue representing positive values and red representing negative values. When the MACD line crosses the signal line from below and the crossover point is below the zero axis, a buy signal (blue dot) is generated. When the MACD line crosses the signal line from above and the crossover point is above the zero axis, a sell signal (red dot) is generated. The strategy automatically places orders based on the buy and sell signals and triggers corresponding alerts. Advantage Analysis The zero-lag algorithm effectively eliminates the delay between the indicator and the price, improving the timeliness and accuracy of signals. The design of dual moving averages can better capture market trends and adapt to different market environments. The MACD histogram intuitively reflects the comparison of bullish and bearish forces, assisting in trading decisions. The automatic order placement and alert functions make it convenient for traders to seize trading opportunities in a timely manner, improving trading efficiency. Risk Analysis In volatile markets, frequent crossover signals may lead to overtrading and losses. Improper parameter settings may cause signal distortion and affect strategy performance. The strategy relies on historical data for calculations and has poor adaptability to sudden events and black swan events. Optimization Direction Introduce trend confirmation indicators, such as ADX, to filter out false signals in volatile markets. Optimize parameters to find the best combination of fast and slow line periods and signal line periods, improving strategy stability. Combine other technical indicators or fundamental factors to construct a multi-factor model, improving risk-adjusted returns of the strategy. Introduce stop-loss and take-profit mechanisms to control single-trade risk. Summary The MACD Dual Crossover Zero Lag Trading Strategy achieves high-frequency trading by quickly responding to price changes and capturing short-term trends. The zero-lag algorithm and dual moving average design improve the timeliness and accuracy of signals. The strategy has certain advantages, such as intuitive signals and convenient operation, but also faces risks such as overtrading and parameter sensitivity. In the future, the strategy can be optimized by introducing trend confirmation indicators, parameter optimization, multi-factor models, etc., to improve the robustness and profitability of the strategy.
Pine Script® strategy
by KaamBhaari
Classic Nacked Z-Score ArbitrageThe “Classic Naked Z-Score Arbitrage” strategy employs a statistical arbitrage model based on the Z-score of the price spread between two assets. This strategy follows the premise of pair trading, where two correlated assets, typically from the same market sector, are traded against each other to profit from relative price movements (Gatev, Goetzmann, & Rouwenhorst, 2006). The approach involves calculating the Z-score of the price spread between two assets to determine market inefficiencies and capitalize on short-term mispricing. Methodology Price Spread Calculation: The strategy calculates the spread between the two selected assets (Asset A and Asset B), typically from different sectors or asset classes, on a daily timeframe. Statistical Basis – Z-Score: The Z-score is used as a measure of how far the current price spread deviates from its historical mean, using the standard deviation for normalization. Trading Logic: • Long Position: A long position is initiated when the Z-score exceeds the predefined threshold (e.g., 2.0), indicating that Asset A is undervalued relative to Asset B. This signals an arbitrage opportunity where the trader buys Asset B and sells Asset A. • Short Position: A short position is entered when the Z-score falls below the negative threshold, indicating that Asset A is overvalued relative to Asset B. The strategy involves selling Asset B and buying Asset A. Theoretical Foundation This strategy is rooted in mean reversion theory, which posits that asset prices tend to return to their long-term average after temporary deviations. This form of arbitrage is widely used in statistical arbitrage and pair trading techniques, where investors seek to exploit short-term price inefficiencies between two assets that historically maintain a stable price relationship (Avery & Sibley, 2020). Further, the Z-score is an effective tool for identifying significant deviations from the mean, which can be seen as a signal for the potential reversion of the price spread (Braucher, 2015). By capturing these inefficiencies, traders aim to profit from convergence or divergence between correlated assets. Practical Application The strategy aligns with the Financial Algorithmic Trading and Market Liquidity analysis, emphasizing the importance of statistical models and efficient execution (Harris, 2024). By utilizing a simple yet effective risk-reward mechanism based on the Z-score, the strategy contributes to the growing body of research on market liquidity, asset correlation, and algorithmic trading. The integration of transaction costs and slippage ensures that the strategy accounts for practical trading limitations, helping to refine execution in real market conditions. These factors are vital in modern quantitative finance, where liquidity and execution risk can erode profits (Harris, 2024). References • Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 1317-1343. • Avery, C., & Sibley, D. (2020). Statistical Arbitrage: The Evolution and Practices of Quantitative Trading. Journal of Quantitative Finance, 18(5), 501-523. • Braucher, J. (2015). Understanding the Z-Score in Trading. Journal of Financial Markets, 12(4), 225-239. • Harris, L. (2024). Financial Algorithmic Trading and Market Liquidity: A Comprehensive Analysis. Journal of Financial Engineering, 7(1), 18-34.
Pine Script® strategy
by EdgeTools