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AMRS_LongOnly_PartTimerThis Script is created to back-test the data starting 01/01/2000 based on AMRS strategy. AMRS is long only strategy. It is based on unique calculation around moving averages and 2 year high price. There are few strategies for moving average crossovers but AMRS strategy is unique compared to other moving averages strategies as it has very specific below mentioned calculations evolving around moving average and stock price. AMRS strategy is unique one to generate buying signals when stock price creates new 2 year high and retraces back to 13 day EMA value. AMRS strategy is unique one having specific calculation for entry signal and exit signal as mentioned below. This strategy gives back testing results to help build conviction on entry/exits if trades were taken in past as per the AMRS rules. As per AMRS strategy this script generates green arrow on each time when new 2 year high is made and also generates long signal indicated by white arrow when stock price retraces back to 13 day EMA value and price is within 10% range from 2 year high. This strategy will generate white arrow on the chart for each buy signal when stock price reaches 13 day EMA after first Long signal is generated. These subsequent buy signals can be used for pyramiding. Entry Signal Logic : 1. Stock should be trading near 2 year high. 2. Stock price should be within 10% range from 2 year high 3. Stock price should be less than or equal to 13 day EMA and grater than equal to 21 day EMA This AMRS strategy also generates exit signal for already generated buy signal (open position). Exit signal generated when stock price closes 5% below 21 day EMA or when stock price closes below 20% from most recent 2 year high price. Exit Signal Logic : 1. Stock price closes 5% below 21 day EMA or stock price closes below 20% from most recent 2 year high price. 2. Since exit logic is based on closing price it is plotted on the chart next day. 3. So when exit signal is plotted on the chart, previous days stock price is either closed below 5% of 21 day EMA or corrected 20% from recent 2 year high. Note : To Calculate last entry positions % return, by default all positions are getting closed on mentioned end date. Script parameters : start date as 01/01/2000 - Constructed from Start Year - 2000, Start Month - 1 Start Date - 1 End date (mostly current date) Constructed from Values in End Year, End Month, End Date. Initial Capital - Defaulted to 100000 Order Size - 5% of Equity Pyramiding - 3 orders Commission - 0.2% Slippage - 1 tick (Since this strategy exit is on close basis mostly there wont be any slippages)
Strategia Pine Script®
di ThePartTimeNSE
10
Portfolio Backtester Engine█  OVERVIEW Portfolio Backtester Engine (PBTE). This tool will allow you to backtest strategies across multiple securities at once. Allowing you to easier understand if your strategy is robust. If you are familiar with the PineCoders backtesting engine , then you will find this indicator pleasant to work with as it is an adaptation based on that work. Much of the functionality has been kept the same, or enhanced, with some minor adjustments I made on the account of creating a more subjectively intuitive tool. █  HISTORY The original purpose of the backtesting engine (`BTE`) was to bridge the gap between strategies and studies . Previously, strategies did not contain the ability to send alerts, but were necessary for backtesting. Studies on the other hand were necessary for sending alerts, but could not provide backtesting results . Often, traders would have to manage two separate Pine scripts to take advantage of each feature, this was less than ideal. The `BTE` published by PineCoders offered a solution to this issue by generating backtesting results under the context of a study(). This allowed traders to backtest their strategy and simultaneously generate alerts for automated trading, thus eliminating the need for a separate strategy() script (though, even converting the engine to a strategy was made simple by the PineCoders!). Fast forward a couple years and PineScript evolved beyond these issues and alerts were introduced into strategies. The BTE was not quite as necessary anymore, but is still extremely useful as it contains extra features and data not found under the strategy() context. Below is an excerpt of features contained by the BTE: """ More than `40` built-in strategies, Customizable components, Coupling with your own external indicator, Simple conversion from Study to Strategy modes, Post-Exit analysis to search for alternate trade outcomes, Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting, Plotting of reminders and generation of alerts on in-trade events. """ Before I go any further, I want to be clear that the BTE is STILL a good tool and it is STILL very useful. The Portfolio Backtesting Engine I am introducing is only a tangental advancement and not to be confused as a replacement, this tool would not have been possible without the `BTE`. █  THE PROBLEM Most strategies built in Pine are limited by one thing. Data. Backtesting should be a rigorous process and researchers should examine the performance of their strategy across all market regimes; that includes, bullish and bearish markets, ranging markets, low volatility and high volatility. Depending on your TV subscription The Pine Engine is limited to 5k-20k historical bars available for backtesting, which can often leave the strategy results wanting. As a general rule of thumb, strategies should be tested across a quantity of historical bars which will allow for at least 100 trades. In many cases, the lack of historical bars available for backtesting and frequency of the strategy signals produces less than 100 trades, rendering your strategy results inconclusive. █  THE SOLUTION In order to be confident that we have a robust strategy we must test it across all market regimes and we must have over 100 trades. To do this effectively, researchers can use the Portfolio Backtesting Engine (PBTE). By testing a strategy across a carefully selected portfolio of securities, researchers can now gather 5k-20k historical bars per security! Currently, the PTBE allows up to 5 securities, which amounts to 25k-100k historical bars. █  HOW TO USE 1 — Add the indicator to your chart.  • Confirm inputs. These will be the most important initial values which you can change later by clicking the gear icon ⚙ and opening up the settings of the indicator. 2 — Select a portfolio.  • You will want to spend some time carefully selecting a portfolio of securities.    • Each security should be uncorrelated.    • The entire portfolio should contain a mix of different market regimes.     You should understand that strategies generally take advantage of one particular type of market regime. (trending, ranging, low/high volatility)    For example, the default RSI strategy is typically advantageous during ranging markets, whereas a typical moving average crossover strategy is advantageous in trending markets.    If you were to use the standard RSI strategy during a trending market, you might be selling when you should be buying.    Similarily, if you use an SMA crossover during a ranging market, you will find that the MA's may produce many false signals.    Even if you build a strategy that is designed to be used only in a trending market, it is still best to select a portfolio of all market regimes    as you will be able to test how your strategy will perform when the market does something unexpected. 3 — Test a built-in strategy or add your own.    • Navigate to gear icon ⚙ (settings) of strategy.    • Choose your options.       • Select a Main Entry Strat and Alternate Entry Strat .          • If you want to add your own strategy, you will need to modify the source code and follow the built-in example.          • You will only need to generate (buy 1 / sell -1/ neutral 0) signals.       • Select a Filter , by default these are all off.       • Select an Entry Stop - This will be your stop loss placed at the trade entry.       • Select Pyamiding - This will allow you to stack positions. By default this is off.       • Select Hard Exits - You can also think of these as Take Profits.    • Let the strategy run and take note of the display tables results.       • Portfolio - Shows each security.          • The strategy runs on each asset in your portfolio.          • The initial capital is equally distributed across each security.           So if you have 5 securities and a starting capital of 100,000$ then each security will run the strategy starting with 20,000$           The total row will aggregate the results on a bar by bar basis showing the total results of your initial capital.       • Net Profit (NP) - Shows profitability.       • Number of Trades (#T) - Shows # of trades taken during backtesting period.          • Typically will want to see this number greater than 100 on the "Total" row.       • Average Trade Length (ATL) - Shows average # of days in a trade.       • Maximum Drawdown (MD ) - Max peak-to-valley equity drawdown during backtesting period.          • This number defines the minimum amount of capital required to trade the system.          • Typically, this shouldn’t be lower than 34% and we will want to allow for at least 50% beyond this number.       • Maximum Loss (ML) - Shows largest loss experienced on a per-trade basis.          • Normally, don’t want to exceed more than 1-2 % of equity.       • Maximum Drawdown Duration (MDD) - The longest duration of a drawdown in equity prior to a new equity peak.          • This number is important to help us psychologically understand how long we can expect to wait for a new peak in account equity.       • Maximum Consecutive Losses (MCL) - The max consecutive losses endured throughout the backtesting period.          • Another important metric for trader psychology, this will help you understand how many losses you should be prepared to handle.       • Profit to Maximum Drawdown (P:MD) - A ratio for the average profit to the maximum drawdown.          • The higher the ratio is, the better. Large profits and small losses contribute to a good PMD.          • This metric allows us to examine the profit with respect to risk.       • Profit Loss Ratio (P:L) - Average profit over the average loss.          • Typically this number should be higher in trend following systems.          • Mean reversion systems show lower values, but compensate with a better win %.       • Percent Winners (% W) - The percentage of winning trades.          • Trend systems will usually have lower win percentages, since statistically the market is only trending roughly 30% of the time.          • Mean reversion systems typically should have a high % W.       • Time Percentage (Time %) - The amount of time that the system has an open position.          • The more time you are in the market, the more you are exposed to market risk, not to mention you could be using that money for something else right?       • Return on Investment (ROI) - Your Net Profit over your initial investment, represented as a percentage.          • You want this number to be positive and high.       • Open Profit (OP) - If the strategy has any open positions, the floating value will be represented here.       • Trading Days (TD) - An important metric showing how many days the strategy was active.          • This is good to know and will be valuable in understanding how long you will need to run this strategy in order to achieve results. █  FEATURES These are additional features that extend the original `BTE` features. - Portfolio backtesting. - Color coded performance results. - Circuit Breakers that will stop trading. - Position reversals on exit. (Simulating the function of always in the market. Similar to strategy.entry functionality) - Whipsaw Filter - Moving Average Filter - Minimum Change Filter - % Gain Equity Exit - Popular strategies, (MACD, MA cross, supertrend) Below are features that were excluded from the original `BTE` - 2 stage in-trade stops with kick-in rules (This was a subjective decision to remove. I found it to be complex and thwarted my use of the `BTE` for some time.) - Simple conversion from Study to Strategy modes. (Not possible with multiple securities) - Coupling with your own external indicator (Not really practical to use with multiple securities, but could be used if signals were generated based on some indicator which was not based on the current chart) - Use of the Data Window to show detailed bar by bar trade information and global statistics. - Post Exit Analysis. - Plotting of reminders and generation of alerts on in-trade events. - Alerts (These may be added in the future by request when I find the time.) █  THANKS The whole PineCoders team for all their shared knowledge and original publication of the BTE and Richard Weismann for his ideas on building robust strategies. ═════════════════════════════════════════════════════════════════════════
Indicatore Pine Script®
di pAulseperformance
36
Easy Loot Golden CrossGolden/Death Cross Moving Average Indicator 30, 100 & 200 period Simple Moving Average (SMA). 30 = Yellow 100 = Green 200 = Black Black crosses mark the 'golden crosses' as well as the 'death crosses'. These black crosses appear when the 30 crosses the 100 & when the 100 crosses the 200. These black crosses don't tell you when to buy/sell, but simply indicate interest in the market. This code is open-source so feel free to add this indicator to your chart and play around with the different moving average timeframes & color schemes. Golden Cross The golden cross occurs when a short-term moving average crosses over a major long-term moving average to the upside and is interpreted by analysts and traders as signaling a definitive upward turn in a market. Basically, the short-term average trends up faster than the long-term average, until they cross. There are three stages to a golden cross: A downtrend that eventually ends as selling is depleted A second stage where the shorter moving average crosses up through the longer moving average Finally, the continuing uptrend, hopefully leading to higher prices Death Cross Conversely, a similar downside moving average crossover constitutes the death cross and is understood to signal a decisive downturn in a market. The death cross occurs when the short term average trends down and crosses the long-term average, basically going in the opposite direction of the golden cross. The death cross preceded the economic downturns in 1929, 1938, 1974, and 2008.
Indicatore Pine Script®
di kyer
6
Combo Strategy 123 Reversal & EMA & MA Crossover This is combo strategies for get a cumulative signal. First strategy This System was created from the Book "How I Tripled My Money In The Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies. The strategy buys at market, if close price is higher than the previous close during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50. The strategy sells at market, if close price is lower than the previous close price during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50. Second strategy The Moving Average Crossover trading strategy is possibly the most popular trading strategy in the world of trading. First of them were written in the middle of XX century, when commodities trading strategies became popular. This strategy is a good example of so-called traditional strategies. Traditional strategies are always long or short. That means they are never out of the market. The concept of having a strategy that is always long or short may be scary, particularly in today’s market where you don’t know what is going to happen as far as risk on any one market. But a lot of traders believe that the concept is still valid, especially for those of traders who do their own research or their own discretionary trading. This version uses crossover of moving average and its exponential moving average. WARNING: - For purpose educate only - This script to change bars colors.
Indicatore Pine Script®
di HPotter
6
Tillson T3 Moving Average MTFMULTIPLE TIME FRAME version of Tillson T3 Moving Average Indicator Developed by Tim Tillson, the T3 Moving Average is considered superior -1.60% to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions. It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend. The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions: If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform. Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions. Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend. And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend . And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions. I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses. Developed by Tim Tillson
Indicatore Pine Script®
di KivancOzbilgic
3
Multiple Moving Averages Alerts ScriptAlerts script that has triggers on multiple moving average crossovers so that profit is maximised, it also has an optional control moving average, enabled by default, that when active will stop trading when the price (first ma) is below the control moving average. Source code is open so that others can use and modify Click Below for Backtesting version: Disclaimers, not an expert, not intended to be financial advise. Biffy
Indicatore Pine Script®
di Biffy
1
Tillson T3 Moving Average by KIVANÇ fr3762Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions. It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend. The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions: If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform. Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions. Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend. And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend . And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions. I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses. Developed by Tim Tillson
Indicatore Pine Script®
di KivancOzbilgic
50
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI) What is Lyapunov Market Instability? Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes. Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth. Theoretical Foundation (Chaos Theory & Lyapunov Exponents) In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories: λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect) λ < 0: System is stable—trajectories converge, perturbations die out λ ≈ 0: Edge of chaos—transition between regimes Phase Space Reconstruction Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions: Time-delay embedding: Create vectors from price at different lags Nearest neighbor search: Find historically similar market states Trajectory evolution: Track how these similar states diverged over time Divergence rate: Calculate average exponential separation Market Application Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work Transition zones: Market regime about to change, reduce position size, wait for confirmation How LMI Works 1. Phase Space Construction Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure. 2. Lyapunov Calculation For each current state, we: - Find similar historical states within epsilon (ε) distance - Track how these initially similar states evolved - Measure exponential divergence rate - Average across multiple trajectories for robustness 3. Signal Generation Chaos signals: When λ crosses above threshold, market enters trending regime Stability signals: When λ crosses below threshold, market enters ranging regime Divergence detection: Price/Lyapunov divergences signal potential reversals 4. Rothko Visualization Color fields: Background zones represent market states with Rothko-inspired palettes Glowing line: Lyapunov exponent with intensity reflecting market state Minimalist design: Focus on essential information without clutter Inputs: 📐 Lyapunov Parameters Embedding Dimension (default: 3) Dimensions for phase space reconstruction 2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns 4-5: Complex dynamics (stocks/indices) - captures intricate market structures Higher dimensions need exponentially more data but reveal deeper patterns Time Delay τ (default: 1) Lag between phase space coordinates 1: High-frequency (1m-15m charts) - captures rapid market shifts 2-3: Medium frequency (1H-4H) - balances noise and signal 4-5: Low frequency (Daily+) - focuses on major regime changes Match to your timeframe's natural cycle Initial Separation ε (default: 0.001) Neighborhood size for finding similar states 0.0001-0.0005: Highly liquid markets (major forex pairs) 0.0005-0.002: Normal markets (large-cap stocks) 0.002-0.01: Volatile markets (crypto, small-caps) Smaller = more sensitive to chaos onset Evolution Steps (default: 10) How far to track trajectory divergence 5-10: Fast signals for scalping - quick regime detection 10-20: Balanced for day trading - reliable signals 20-30: Slow signals for swing trading - major regime shifts only Nearest Neighbors (default: 5) Phase space points for averaging 3-4: Noisy/fast markets - adapts quickly 5-6: Balanced (recommended) - smooth yet responsive 7-10: Smooth/slow markets - very stable signals 📊 Signal Parameters Chaos Threshold (default: 0.05) Lyapunov value above which market is chaotic 0.01-0.03: Sensitive - more chaos signals, earlier detection 0.05: Balanced - optimal for most markets 0.1-0.2: Conservative - only strong trends trigger Stability Threshold (default: -0.05) Lyapunov value below which market is stable -0.01 to -0.03: Sensitive - quick stability detection -0.05: Balanced - reliable ranging signals -0.1 to -0.2: Conservative - only deep stability Signal Smoothing (default: 3) EMA period for noise reduction 1-2: Raw signals for experienced traders 3-5: Balanced - recommended for most 6-10: Very smooth for position traders 🎨 Rothko Visualization Rothko Classic: Deep reds for chaos, midnight blues for stability Orange/Red: Warm sunset tones throughout Blue/Black: Cool, meditative ocean depths Purple/Grey: Subtle, sophisticated palette Visual Options: Market Zones : Background fields showing regime areas Transitions: Arrows marking regime changes Divergences: Labels for price/Lyapunov divergences Dashboard: Real-time state and trading signals Guide: Educational panel explaining the theory Visual Logic & Interpretation Main Elements Lyapunov Line: The heart of the indicator Above chaos threshold: Market is trending, follow momentum Below stability threshold: Market is ranging, fade extremes Between thresholds: Transition zone, reduce risk Background Zones: Rothko-inspired color fields Red zone: Chaotic regime (trending) Gray zone: Transition (uncertain) Blue zone: Stable regime (ranging) Transition Markers: Up triangle: Entering chaos - start trend following Down triangle: Entering stability - start mean reversion Divergence Signals: Bullish: Price makes low but Lyapunov rising (stability breaking down) Bearish: Price makes high but Lyapunov falling (chaos dissipating) Dashboard Information Market State: Current regime (Chaotic/Stable/Transitioning) Trading Bias: Specific strategy recommendation Lyapunov λ: Raw value for precision Signal Strength: Confidence in current regime Last Change: Bars since last regime shift Action: Clear trading directive Trading Strategies In Chaotic Regime (λ > threshold) Follow trends aggressively: Breakouts have high success rate Use momentum strategies: Moving average crossovers work well Wider stops: Expect larger swings Pyramid into winners: Trends tend to persist In Stable Regime (λ < threshold) Fade extremes: Mean reversion dominates Use oscillators: RSI, Stochastic work well Tighter stops: Smaller expected moves Scale out at targets: Trends don't persist In Transition Zone Reduce position size: Uncertainty is high Wait for confirmation: Let regime establish Use options: Volatility strategies may work Monitor closely: Quick changes possible Advanced Techniques - Multi-Timeframe Analysis - Higher timeframe LMI for regime context - Lower timeframe for entry timing - Alignment = highest probability trades - Divergence Trading - Most powerful at regime boundaries - Combine with support/resistance - Use for early reversal detection - Volatility Correlation - Chaos often precedes volatility expansion - Stability often precedes volatility contraction - Use for options strategies Originality & Innovation LMI represents a genuine breakthrough in applying chaos theory to markets: True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement Rothko Aesthetic: Transforms complex math into meditative visual experience Regime Detection: Identifies market state changes before price makes them obvious Practical Application: Clear, actionable signals from theoretical physics This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics. Best Practices Start with defaults: Parameters are optimized for broad market conditions Match to your timeframe: Adjust tau and evolution steps Confirm with price action: LMI shows regime, not direction Use appropriate strategies: Chaos = trend, Stability = reversion Respect transitions: Reduce risk during regime changes Alerts Available Chaos Entry: Market entering chaotic regime - prepare for trends Stability Entry: Market entering stable regime - prepare for ranges Bullish Divergence: Potential bottom forming Bearish Divergence: Potential top forming Chart Information Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes Academic References Takens, F. (1981). "Detecting strange attractors in turbulence" Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series" Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents" Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering. Disclaimer This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results. See markets through the lens of chaos. Trade the regime, not the noise. Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
Indicatore Pine Script®
di DskyzInvestments
Optimized Auto-Detect Strategy (MA, ATR, Trend, RSI) Overview This script is designed for traders seeking a trend-following approach that adapts to different currency pairs (e.g., EURUSD, NZDUSD, XAUUSD). It combines moving average crossovers with ATR-based stops, optional trend filters, and RSI filters to help reduce false signals and capture larger moves. Key Features 1. Auto-Detect Logic - Automatically applies different moving average periods and ATR multipliers based on the symbol (e.g., XAUUSD, EURUSD, NZDUSD). - Makes it easy to switch charts without manually adjusting parameters each time. 2. ATR-Based Stop - Uses the Average True Range (ATR) to set dynamic stop-loss levels, adapting to each market’s volatility. 3. Optional Trend Filter - Filters out trades if price is below the 200 SMA for longs (and above for shorts), aiming to avoid choppy, range-bound markets. 4. Optional RSI Filter - Only enters long if RSI is above a certain threshold (e.g., 50), or short if below another threshold, reducing entries during low momentum. 5. Partial Exit & Trailing/Break-Even - Locks in partial profit at a chosen R:R (e.g., 1:1), then either trails the remaining position or moves the stop to break-even. - This helps capture additional gains if the trend extends beyond the initial target. 6. Customizable Parameters - You can toggle on/off each filter (Trend, RSI) and adjust the ATR multiplier, MA periods, partial exit levels, etc. - Allows easy optimization for different pairs or timeframes. How to Use 1. Add to Chart: Click “Add to chart” in the Pine Editor. 2. Configure Inputs: In the script’s settings, toggle the filters you want (Trend Filter, RSI Filter, etc.) and set your desired ATR multiplier, RSI thresholds, partial exit ratio, etc. 3. Strategy Tester: Check the performance under the “Strategy Tester” tab. Adjust parameters if needed. 4. Realistic Settings: Consider adding spreads/commissions in the “Properties” tab for more accurate backtests, especially if you trade pairs with higher spreads (like XAUUSD). Disclaimer No Guarantee: This script does not guarantee profits. Markets are unpredictable, and results may vary with market conditions. For Educational Purposes: Always do your own research and forward testing. Past performance does not indicate future results.
Strategia Pine Script®
di jontucklogic7467
UVR Crypto TrendINDICATOR OVERVIEW: UVR CRYPTO TREND The UVR Crypto Trend indicator is a custom-built tool designed specifically for cryptocurrency markets, utilizing advanced volatility, momentum, and trend-following techniques. It aims to identify trend reversals and provide buy and sell signals by analyzing multiple factors, such as price volatility(UVR), RSI (Relative Strength Index), CMF (Chaikin Money Flow), and EMA (Exponential Moving Average). The indicator is optimized for CRYPTO MARKETS only. KEY FEATURES AND HOW IT WORKS Volatility Analysis with UVR The UVR (Ultimate Volatility Rate) is a proprietary calculation that measures market volatility by comparing significant price extremes and smoothing the data over time. Purpose: UVR aims to reduce noise in low-volatility environments and highlight significant movements during higher-volatility periods. While it strives to improve filtering in low-volatility conditions, it does not guarantee perfect performance, making it a balanced and adaptable tool for dynamic markets like cryptocurrency. HOW UVR (ULTIMATE VOLATILITY RATE) IS CALCULATED UVR is calculated using a method that ensures precise measurement of market volatility by comparing price extremes across consecutive candles: Volatility Components: Two values are calculated to represent potential price fluctuations: The absolute difference between the current candle's high and the previous candle's low: Volatility Component 1=∣High−Low ∣ The absolute difference between the previous candle's high and the current candle's low: Volatility Component 2=∣High −Low∣ Volatility Ratio: The larger of the two components is selected as the Volatility Ratio, ensuring UVR captures the most significant movement: Volatility Ratio=max(Volatility Component 1,Volatility Component 2) Smoothing with SMMA: To stabilize the volatility calculation, the Volatility Ratio is smoothed using a Smoothed Moving Average (SMMA) over a user-defined period (e.g., 14 candles): UVR=(UVR(Previous)×(Period−1)+Volatility Ratio)/Period ​ This calculation ensures UVR adapts dynamically to market conditions, focusing on significant price movements while filtering out noise. RSI FOR MOMENTUM DETECTION RSI (Relative Strength Index) identifies overbought and oversold conditions. Trend Confirmation at the 50 Level RSI values crossing above 50 signal the potential start of an upward trend. RSI values crossing below 50 indicate the potential start of a downward trend. Key Reversals at Extreme Levels RSI detects trend reversals at overbought (>70) and oversold (<30) levels. For example: Overbought Trend Reversal: RSI >70 followed by bearish price action signals a potential downtrend. Oversold Trend Reversal: RSI <30 with bullish confirmation signals a potential uptrend. Rare Extreme RSI Readings Extreme levels, such as RSI <12 (oversold) or RSI >88 (overbought), are used to identify rare yet powerful reversals. ---HOW IT DIFFERS FROM OTHER INDICATORS--- Using UVR High and Low Values The Ultimate Volatility Rate (UVR) focuses on analyzing the high and low price ranges of the market to measure volatility. Unlike traditional trend indicators that rely primarily on momentum or moving average crossovers, UVR leverages price extremes to better identify trend reversals. This approach ensures fewer false signals during low-volatility phases and more accurate trend detection during high-volatility conditions. UVR as the Core Component The indicator is fundamentally built around UVR as the primary filter, while supporting tools like RSI (momentum detection), CMF (volume confirmation), and EMA (trend validation) complement its functionality. By integrating these additional components, the indicator provides a multidimensional analysis rather than relying solely on a single approach. Dynamic Adaptation to Volatility UVR dynamically adjusts to market conditions, striving to improve filtering in low-volatility phases. While not flawless, this approach minimizes false signals and adapts more effectively to varying levels of market activity. Trend Clouds for Visual Guidance UVR-based dynamic clouds visually mark high and low price areas, highlighting potential consolidation or retracement zones. These clouds serve as guides for setting stop-loss or take-profit levels, offering clear risk management strategies. BUY AND SELL SIGNAL LOGIC BUY CONDITIONS Momentum-Based Buy-Entry RSI >50, CMF >0, and the close price is above EMA50. The price difference between open and close exceeds a threshold based on UVR. Oversold Reversal RSI <30 and CMF >0 with a strong bullish candle (close > open and UVR-based sensitivity filter). Breakout Confirmation The price breaks above a previously identified resistance, with conditions for RSI and CMF supporting the breakout. Reversal from Oversold RSI Extreme RSI <12 on the previous candle with a strong rebound on the current candle with UVR confirmation filter. SELL CONDITIONS Momentum-Based Sell-Entry RSI <50, CMF <0, and the close price is below EMA50. The price difference between open and close exceeds the UVR threshold. Overbought Reversal RSI >70 with bearish price action (open > close and UVR-based sensitivity filter). Breakdown Confirmation The price breaks below a previously identified support, with RSI and CMF supporting the breakdown. Reversal from Overbought RSI Extreme RSI >88 on the previous candle with a bearish confirmation on the current candle with UVR confirmation filter. BUY AND SELL SIGNALS VISUALIZATION The UVR Crypto Trend Indicator visually represents buy and sell conditions using dynamic plots, making it easier for traders to interpret and act on the signals. Below is an explanation of the visual representation: Buy Signals and Visualization Signal Trigger: A buy signal is generated when one of the defined Buy Conditions is met (e.g., RSI >50, CMF >0, price above EMA50). Visual Representation: A blue upward arrow appears at the candle where the buy condition is triggered. A blue cloud forms above the price candles, representing the strength of the bullish trend. The cloud dynamically adapts to market volatility, using the UVR calculation to mark support zones or consolidation levels. Purpose of the Blue Cloud: It acts as a visual guide for price movements and stay horizontal when the trend is not moving up Sell Signals and Visualization Signal Trigger: A sell signal is generated when one of the defined Sell Conditions is met (e.g., RSI <50, CMF <0, price below EMA50). Visual Representation: A red downward arrow appears at the candle where the sell condition is triggered. A red cloud forms below the price candles, representing the strength of the bearish trend. Like the blue cloud, it uses the UVR calculation to dynamically mark resistance zones or potential retracement levels. Purpose of the Red Cloud: It acts as a visual guide for price movements and stay horizontal when the trend is not moving down. CONCLUSION The UVR Crypto Trend indicator provides a powerful tool for trend reversal detection by combining volatility analysis, momentum confirmation, and trend-following techniques. Its unique use of the Ultimate Volatility Rate (UVR) as a core element, supported by proven indicators like RSI, CMF, and EMA, ensures reliable and actionable signals tailored for the crypto market's dynamic nature. By leveraging UVR’s high and low price range analysis, it achieves a level of precision that traditional indicators lack, making it a high-performing system for cryptocurrency traders.
Indicatore Pine Script®
di ebecihalil
Traders Trend DashboardThe Traders Trend Dashboard (TTD) is a comprehensive trend analysis tool designed to assist traders in making informed trading decisions across various markets and timeframes. Unlike conventional trend-following scripts, TTD goes beyond simple trend detection by incorporating a unique combination of moving averages and a visual dashboard, providing traders with a clear and actionable overview of market trends. Here's how TTD stands out from the crowd: Originality and Uniqueness: TTD doesn't rely on just one moving average crossover to detect trends. Instead, it employs a dynamic approach by comparing two moving averages of distinct periods across multiple timeframes. This innovative methodology enhances trend detection accuracy and reduces false signals commonly associated with single moving average systems. Market Applicability: TTD is versatile and adaptable to various financial markets, including forex, stocks, cryptocurrencies, and commodities. Its flexibility ensures that traders can utilize it across different asset classes and capitalize on market opportunities. Optimal Timeframe Utilization: Unlike many trend indicators that work best on specific timeframes, TTD caters to traders with diverse trading preferences. It offers support for intraday trading (1m, 3m, 5m), short-term trading (15m, 30m, 1h), and swing trading (4h, D, W, M), making it suitable for a wide range of trading styles. Underlying Conditions and Interpretation: TTD is particularly effective during trending markets, where its multi-timeframe approach helps identify consistent trends across various time horizons. In ranging markets, TTD can indicate potential reversals or areas of uncertainty when moving averages converge or cross frequently. How to Use TTD: 1. Timeframe Selection: Choose the relevant timeframes based on your trading style and preferences. Enable or disable timeframes in the settings to focus on the most relevant ones for your strategy. 2. Dashboard Interpretation: The TTD dashboard displays green (🟢) and red (🔴) symbols to indicate the relationship between two moving averages. A green symbol suggests that the shorter moving average is above the longer one, indicating a potential bullish trend. A red symbol suggests the opposite, indicating a potential bearish trend. 3. Confirmation and Strategy: Consider TTD signals as confirmation for your trading strategy. For instance, in an uptrend, look for long opportunities when the dashboard displays consistent green symbols. Conversely, in a downtrend, focus on short opportunities when red symbols dominate. 4. Risk Management: As with any indicator, use TTD in conjunction with proper risk management techniques. Avoid trading solely based on indicator signals; instead, integrate them into a comprehensive trading plan. Conclusion: The Traders Trend Dashboard (TTD) offers traders a powerful edge in trend analysis, combining innovation, versatility, and clarity. By understanding its unique methodology and integrating its signals with your trading strategy, you can make more informed trading decisions across various markets and timeframes. Elevate your trading with TTD and unlock a new level of trend analysis precision.
Indicatore Pine Script®
di AlexFuch
111
Oliver Velez IndicatorOliver Velez is a well-known trader and educator who has developed multiple trading strategies. One of them is the 20-200sma strategy, which is a basic moving average crossover strategy. The strategy involves using two simple moving averages (SMAs) - a short-term SMA with a period of 20 and a long-term SMA with a period of 200 - on a 2-minute timeframe chart. When the short-term SMA crosses above the long-term SMA, it signals a potential bullish trend and traders may look for opportunities to enter a long position. Conversely, when the short-term SMA crosses below the long-term SMA, it signals a potential bearish trend and traders may look for opportunities to enter a short position. Traders using this strategy may also look for additional confirmations, such as price action signals or other technical indicators, before entering or exiting a trade. It is important to note that no trading strategy can guarantee profits, and traders should always use risk management techniques to limit potential losses. This script is an implementation of the 2 SMA's (can also choose other types of MA's), with Elephant Bar Indicator (EBI) and the Tail Bars Indicator in TradingView. The Elephant Bar Indicator is a technical indicator used in trading to identify potential trend reversals in the market. It is named after the large size of the bullish or bearish candlestick that it represents. The Tail Bars Indicator is a pattern recognition technique that identifies candlestick patterns with long tails or wicks. The script starts by defining the input parameters for both indicators. For the Elephant Bar Indicator, the user inputs the lookback period and the size multiplier. For the Tail Bars Indicator, the user inputs the tail ratio and opposite wick ratio. Next, the script calculates the moving averages of the closing price over the defined short and long periods using the Moving Average function. The script then calculates the average candle size and volume over the lookback period. The script then identifies the Elephant Bars and Tail Bars using the input parameters and additional conditions. For Elephant Bars, the script identifies bullish and bearish bars that meet certain criteria, such as a size greater than the average candle size and volume greater than the average volume. For Tail Bars, the script identifies bullish and bearish bars that have long tails or wicks and meet certain criteria such as opposite wick size less than or equal to the tail size multiplied by the input opposite wick ratio. Finally, the script plots the Elephant Bar and Tail Bar signals on the chart using different colors and shapes. The script also plots the moving averages and Keltner Channels to help traders identify potential trend reversals. It is still under development, so please, if someone has ideas to add, more than welcome
Indicatore Pine Script®
di Rginah1974
8
Arch1tect's New ToyDescription: Arch1tect's New Toy tries to predict market trends by simply utilising 2 moving averages crossovers. How it works: Buy signals are triggered when the faster MA crosses over the slower MA from the downside to the upside. Sell signals are triggered when the faster MA crosses under the slower MA from the upside to the downside. How to use: Take buys when buy signal is triggered AND close existing sell position Take sells when sell signal is triggered AND close existing buy position Note: Settings are optimised for XAUUSD on the M1 chart. Extra: Alerts are included. You can toggle between EMA , WMA and SMA to your liking. Strategy Tester version:
Indicatore Pine Script®
di Tutorial05
5
Arch1tect's New Toy (Strategy Tester Version)Description: The version of Arch1tect's New Toy indicator with Strategy Tester added. This indicator tries to predict market trends by simply utilising 2 moving averages crossovers. How it works: Buy signals are triggered when the faster MA crosses over the slower MA from the downside to the upside. Sell signals are triggered when the faster MA crosses under the slower MA from the upside to the downside. How to use: Take buys when buy signal is triggered AND close existing sell position Take sells when sell signal is triggered AND close existing buy position Note: Settings are optimised for XAUUSD on the M1 chart. Extra: Alerts are included. You can toggle between EMA, WMA and SMA to your liking. Indicator version:
Strategia Pine Script®
di Tutorial05
2
[blackcat] L1 Stick-Line Merged MACDLevel: 1 Background The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line. Function L1 Stick-Line Merged MACD merges dif and dea lines with macd sticks by the same color candles. The generation of candles help to confirm the trend contiuation. E.g. yellow candles indicate up trend continuation while blue candles indicate down trend continuation Key Signal dif --> classic MACD diff fast line in yellow dea --> classic MACD dea slow line in fuchsia macd --> classic difference histogram upslmerge --> up trend continuation yellow candle merge condition dnslmerge --> down trend continuation blue candle merge condition Pros and Cons Pros: 1. merged line and stick with candles help confirm trend reversal 2. long entry signal is indicated. Cons: 1. need sophisticated knowledge of MACD to use this well 2. this still requires a lot of MACD experience to obtain reliable trading signals Remarks Merge lines and sticks of MACD into candles. Better view of the trend Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Indicatore Pine Script®
di blackcat1402
4
[blackcat] L1 Another Improved MACD IndicatorLevel: 1 Background The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line. Function L1 Another Improved MACD Indicator improves MACD histogram by customized an algorithm and add three levels of long entry alerts derived from ema (). Key Signal diff --> classic MACD diff fast line in white dea --> classic MACD dea slow line in yellow macd --> classic difference histogram,but I did not use it directly in the plot. macd1 --> ema3 of macd Pros and Cons Pros: 1. more clear sub level trend change with new histograms Cons: 1. need sophisticated knowledge of MACD to use this well 2. this still requires a lot of MACD experience to obtain reliable trading signals Remarks Another improved MACD on histogram Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Indicatore Pine Script®
di blackcat1402
1
[blackcat] L1 Improved MACD IndicatorLevel: 1 Background The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line. Function L1 Improved MACD Indicator mainly improves MACD histogram by customized an algorithm and add three levels of long entry alerts derived from ema(). Key Signal buy1 --> the 1st level of buy alert in green buy2 --> the 2nd level of buy alert in lime buy3 --> the 3rd level of buy alert in yellow diff --> classic MACD diff fast line in white dea --> classic MACD dea slow line in yellow macd --> classic difference histogram,but I did not use it directly in the plot. Pros and Cons Pros: 1. more clear sub level trend change with new histograms 2. three levels of buy alerts Cons: 1. need sophisticated knowledge of MACD to use this well 2. this still requires a lot of MACD experience to obtain reliable trading signals Remarks I am a fan of MACD. Even the most classic MACD can have in-depth usage. I think MACD is the king of indicators. Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Indicatore Pine Script®
di blackcat1402
2
Predictive EMAFrom the MQL5 Indicator database, here is what the author said about the script, "Goal of this indicator: Given three EMA's of varying lengths, use their values for a estimator of "where we are now" or will be in the near future. This is a very simplistic method, better ones are probably found in the signal processing and target tracking literature. A Kalman filter has been known since the 1950's 1960's and there is better still. Nevertheless this is easily programmable in the typical environments of a retail trading application like Metatrader4. Method: An an exponential moving average (EMA) or a simple moving average (SMA), for that matter, have a bandwidth parameter 'L', the effective length of the window. This is in units of time or, really, inverse of frequency. Higher L means a lower frequency effect. With a parameter L, the weighted time index of the EMA and SMA is (L-1)/2. Example: take an SMA of the previous 5 values: -5 -4 -3 -2 -1 now. The average "amount of time" back in the past of the data which go in to the SMA is hence -3, or (L-1)/2. Same applies for an EMA. The standard parameterization makes this correspondence between EMA and SMA. Therefore the idea here is to take two different EMA's, a longer, and a shorter of lengths L1 and L2 (L2 <L1). Now take the pairs: which defines a line. Extrapolate to , solve for y and that is the predictive EMA estimate. Application: Traditional moving averages, as simple-minded linear filters, have significant group delay. In engineering that isn't so important as nobody cares if your sound from your iPod is delayed a few milliseconds after it is first processed. But in markets, you can't trade on the smoothed price, only the actual noisy, market price now. Hence you ought to estimate better. This statistic (what math/science people call what technical analysts call an 'indicator') may be useful as the "fast" moving average in a moving average crossover trading system. It could also be useful for the slow moving average as well. For instance, on a 5 minute chart: try for the fast: (will be very wiggly, note) LongPeriod 25.0 ShortPeriod 8.0 ExtraTimeForward 1.0 and for the slow: LongPeriod 500.0 ShortPeriod 50.0 to 200.0 ExtraTimeForward 0.0 But often a regular MA for the slow can work as well or better, it appears from visual inspection. Enjoy. In chaos there is order, and in that order there is chaos and order inside again. Then, surrounding everything, pointy haired bosses. " I may have done it incorrectly, feel free to revise
Indicatore Pine Script®
di wpatte15
4
Liquidity Market Seeking SwiftEdgeThis indicator is designed to identify potential liquidity levels on the chart by detecting swing highs and lows, which are often areas where stop-loss orders or significant orders accumulate. It visualizes these levels with horizontal lines and labels on the right side of the chart, color-coded based on volume to help traders understand where the market might seek liquidity. How It Works Swing Highs and Lows: The indicator uses the ta.pivothigh and ta.pivotlow functions to identify significant swing points over a user-defined lookback period (Swing Length). These points are considered potential liquidity levels where stop-loss orders might be placed. Volume Analysis: The indicator compares the volume at each swing point to the average volume over a specified period (Volume Average Length). Levels with above-average volume are colored red, indicating higher liquidity, while levels with below-average volume are colored green. Liquidity Visualization: Horizontal dashed lines are drawn at each identified level, extending across the chart. Labels on the right side display the estimated liquidity amount (simulated based on volume and a multiplier, Volume Multiplier for Liquidity). Sell Signal: A "SELL NOW" label appears when the price approaches a liquidity level after an uptrend (detected using a simple moving average crossover). This suggests a potential reversal as the market may target liquidity at that level. Strategy Concept: Market Seeking Liquidity The indicator is based on the concept that markets often move toward areas of high liquidity, such as clusters of stop-loss orders or significant order accumulations. These liquidity pools are typically found around swing highs and lows, where traders place their stop-losses or large orders. By identifying these levels and highlighting those with higher volume (red lines), the indicator aims to show where the market might move to "grab" this liquidity. For example, after an uptrend, the market may reverse at a swing high to take out stop-losses above that level, providing liquidity for larger players to enter or exit positions. Settings Swing Length: The number of bars to look back for detecting swing highs and lows. Default is 20. Liquidity Threshold: The price threshold for merging nearby levels to avoid duplicates. Default is 0.001. Volume Average Length: The period for calculating the average volume to compare against. Default is 20. Volume Multiplier for Liquidity: A multiplier to scale the volume into a simulated liquidity amount (displayed as "K"). Default is 1000. Usage Notes Use this indicator on any timeframe, though it may be more effective on higher timeframes (e.g., 1H, 4H) where swing points are more significant. Red lines indicate levels with higher volume, suggesting stronger liquidity pools that the market might target. Green lines indicate levels with lower volume, which may be less significant. The "SELL NOW" signal is a basic example of how to use liquidity levels for trading decisions. It appears when the price approaches a liquidity level after an uptrend, but it should be used in conjunction with other analysis. Adjust the Volume Multiplier for Liquidity to scale the displayed liquidity amounts based on your instrument (e.g., forex pairs may need a higher multiplier than indices).
Indicatore Pine Script®
di SwiftEdge
1
MA Win RateMoving Average Cross Win Rate This simple yet useful script calculates the percentage of times a moving average crossover successfully predicts price movement. Win Conditions: 1] A Golden Cross (fast MA crossing above slow MA) where the price moves up afterward. 2] A Death Cross (fast MA crossing below slow MA) where the price moves down afterward. In this script, I have used a Simple Moving Average (SMA) for illustration. You can modify the code to apply any type of moving average and test its accuracy.
Indicatore Pine Script®
di Pro_Quantitative_Trader