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Perfomance index Backtest The Performance indicator or a more familiar term, KPI (key performance indicator), is an industry term that measures the performance. Generally used by organizations, they determine whether the company is successful or not, and the degree of success. It is used on a business’ different levels, to quantify the progress or regress of a department, of an employee or even of a certain program or activity. For a manager it’s extremely important to determine which KPIs are relevant for his activity, and what is important almost always depends on which department he wants to measure the performance for. So the indicators set for the financial team will be different than the ones for the marketing department and so on. Similar to the KPIs companies use to measure their performance on a monthly, quarterly and yearly basis, the stock market makes use of a performance indicator as well, although on the market, the performance index is calculated on a daily basis. The stock market performance indicates the direction of the stock market as a whole, or of a specific stock and gives traders an overall impression over the future security prices, helping them decide the best move. A change in the indicator gives information about future trends a stock could adopt, information about a sector or even on the whole economy. The financial sector is the most relevant department of the economy and the indicators provide information on its overall health, so when a stock price moves upwards, the indicators are a signal of good news. On the other hand, if the price of a particular stock decreases, that is because bad news about its performance are out and they generate negative signals to the market, causing the price to go downwards. One could state that the movement of the security prices and consequently, the movement of the indicators are an overall evaluation of a country’s economic trend. You can change long to short in the Input Settings WARNING: - For purpose educate only - This script to change bars colors.
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HPotter tarafından
Chande Forecast Oscillator Backtest The Chande Forecast Oscillator developed by Tushar Chande The Forecast Oscillator plots the percentage difference between the closing price and the n-period linear regression forecasted price. The oscillator is above zero when the forecast price is greater than the closing price and less than zero if it is below. You can change long to short in the Input Settings WARNING: - For purpose educate only - This script to change bars colors.
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HPotter tarafından
Fractal Chaos Bands Backtest The FCB indicator looks back in time depending on the number of time periods trader selected to plot the indicator. The upper fractal line is made by plotting stock price highs and the lower fractal line is made by plotting stock price lows. Essentially, the Fractal Chaos Bands show an overall panorama of the price movement, as they filter out the insignificant fluctuations of the stock price. You can change long to short in the Input Settings WARNING: - For purpose educate only - This script to change bars colors.
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HPotter tarafından
Liquidity Sweep Detector – PDH/PDL LevelsPrevious Day High/Low Liquidity Sweep Detector (Intraday Accurate) This indicator tracks the previous day's high and low using intraday data, rather than the daily candle, ensuring precise sweep detection across lower timeframes (15m to 4H). It monitors for liquidity sweeps—moments when price briefly moves above the previous high or below the previous low—and visually marks these events on the chart. Key Features Intraday-accurate PDH/PDL tracking Real-time sweep detection On-chart labels marking sweep events Toggleable table showing sweep status Alert conditions for PDH/PDL sweep triggers Best For Traders who use Smart Money Concepts (SMC), liquidity-based strategies, or look for stop hunts and reversal zones tied to key prior-day levels. Works well across FX, crypto, and indices on 15m, 1H, and 4H charts.
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backtestbay tarafından
RSI MTF Ob+OsHello Traders, This indicator use the same concept as my previous indicator "CCI MTF Ob+Os". It is a simple "Relative Strength Index" ( RSI ) indicator with multi-timeframe (MTF) overbought and oversold level. It can detect overbought and oversold level up to 5 timeframes, which help traders spot potential reversal point more easily. There are options to select 1-5 timeframes to detect overbought and oversold. Aqua Background is "Oversold" , looking for "Long". Orange Background is "Overbought" , looking for "Short". Have fun :)
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BacktestTerminal tarafından
9
CCI MTF Ob+OsHello Traders, This is a simple Commodity Channel Index (CCI) indicator with multi-timeframe (MTF) overbought and oversold level. It can detect overbought and oversold level up to 5 timeframes, which help traders spot potential reversal point more easily. There are options to select 1-5 timeframes to detect overbought and oversold. Green Background is "Oversold" , looking for "Long". Red Background is "Overbought" , looking for "Short". Have fun :)
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BacktestTerminal tarafından
Demand & Supply Zones [eyes20xx]Demand & Supply Zones This indicator helps to identify large moves driven by institutions. What qualifies as a zone? If the price moves (open to close) by more than a certain % in one candle or in a bullish / bearish run of candles, the zone is marked as a Demand or Supply zone . 0.8% is good for Crypto and Forex might be better with 0.4%. Play around with the % to match your requirements. Active zones A zone remains active until it is hit by the price. When it becomes inactive, the zone background becomes transparent. Zone lines Lines are displayed if the zone is active and within a certain % of the close. 3% is a good setting for Crypto. A maximum of two lines are displayed for each zone type.
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BacktestBot tarafından
99
Percentage Change FunctionThis is little code snippet can be copied and pasted into your own strategies and indicators to easily calculate some interesting percentage change levels within a given lookback period. The function will return: The price change from the start to the end of the period The price change from the start of the period to the highest point within the period The price change from the start of the period to the lowest point within the period It was originally intended to be used in conjunction with other scripts to assist with decision making. However, it doesn't look too bad as an indicator and so plots have been added. For more information regarding the code, some commentary and free tutorials, you can visit the Bactest-Rookies (.com) website.
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BacktestRookies tarafından
6
Correlate 3 - Correlation IndicatorThe code in contains a simple correlation indicator that can be used as an alternative to Tradingview’s built-in “Correlation Coefficient” indicator. The indicator allows users to correlate up to 3 separate instruments on the same subplot. This allows you, for example, to easily see the correlation of your instrument with stocks, bonds and FX. Alternatively, a user can also see the correlation with sector, industry peers or any other data available in Tradingview. Features Level Guides to easily see the key correlation coefficient levels Multi-instrument:
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BacktestRookies tarafından
2
Laguerre RSI by KivancOzbilgic STRATEGYBacktesting. " Laguerre RSI is based on John EHLERS' Laguerre Filter to avoid the noise of RSI . Change alpha coefficient to increase/decrease lag and smoothness. Buy when Laguerre RSI crosses upwards above 20. Sell when Laguerre RSI crosses down below 80. While indicator runs flat above 80 level, it means that an uptrend is strong. While indicator runs flat below 20 level, it means that a downtrend is strong. " Developer: John EHLERS Author: KivancOzbilgic
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mertriver1 tarafından
8
RSI-VWAPBacktest script based on the previous RSI-VWAP indicator: It's the popular RSI indicator with VWAP as a source instead of close: - RSI_VWAP = rsi(vwap(close), RSI_VWAP_length) What is the Volume Weighted Average Price ( VWAP )? VWAP is calculated by adding up the dollars traded for every transaction (price multiplied by the number of shares traded) and then dividing by the total shares traded. Trades are laddered to improve the average entry price and each entry is increased, improving the entry but increasing the risk of being liquidated. It can be easily converted to study (alerts) Settings for BINANCE:BTCUSDT at 30m
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UnknownUnicorn2151907 tarafından
29
Asset Rotation System [InvestorUnknown]Overview This system creates a comprehensive trend "matrix" by analyzing the performance of six assets against both the US Dollar and each other. The objective is to identify and hold the asset that is currently outperforming all others, thereby focusing on maintaining an investment in the most "optimal" asset at any given time. - - - Key Features - - - 1. Trend Classification: The system evaluates the trend for each of the six assets, both individually against USD and in pairs (assetX/assetY), to determine which asset is currently outperforming others. Utilizes five distinct trend indicators: RSI (50 crossover), CCI, SuperTrend, DMI, and Parabolic SAR. Users can customize the trend analysis by selecting all indicators or choosing a single one via the "Trend Classification Method" input setting. 2. Backtesting: Calculates an equity curve for each asset and for the system itself, which assumes holding only the asset deemed optimal at any time. Customizable start date for backtesting; by default, it begins either 5000 bars ago (the maximum in TradingView) or at the inception of the youngest asset included, whichever is shorter. If the youngest asset's history exceeds 5000 bars, the system uses 5000 bars to prevent errors. The equity curve is dynamically colored based on the asset held at each point, with this coloring also reflected on the chart via barcolor(). Performance metrics like returns, standard deviation of returns, Sharpe, Sortino, and Omega ratios, along with maximum drawdown, are computed for each asset and the system's equity curve. 3 Alerts: Supports alerts for when a new, confirmed optimal asset is identified. However, due to TradingView limitations, the specific asset cannot be included in the alert message. - - - Usage - - - 1. Select Assets/Tickers: Choose which assets or tickers you want to include in the rotation system. Ensure that all selected tickers are denominated in USD to maintain consistency in analysis. 2. Configure Trend Classification: Decide on the trend classification method from the available options (RSI, CCI, SuperTrend, DMI, or Parabolic SAR, All) and adjust the settings to your preferences. This customization allows you to tailor the system to different market conditions or your specific trading strategy. 3. Utilize Backtesting for Calibration: Use the backtesting results, including equity curves and performance metrics, to fine-tune your chosen trend indicators. Be cautious not to overemphasize performance maximization, as this can lead to overfitting. The goal is to achieve a robust system that performs well across various market conditions, rather than just optimizing for past data. - - - Parameters - - - Tickers: Asset 1: Select the symbol for the first asset. Asset 2: Select the symbol for the second asset. Asset 3: Select the symbol for the third asset. Asset 4: Select the symbol for the fourth asset. Asset 5: Select the symbol for the fifth asset. Asset 6: Select the symbol for the sixth asset. General Settings: Trend Classification Method: Choose from RSI, CCI, SuperTrend, DMI, PSAR, or "All" to determine how trends are analyzed. Use Custom Starting Date for Backtest: Toggle to use a custom date for beginning the backtest. Custom Starting Date: Set the custom start date for backtesting. Plot Perf. Metrics Table: Option to display performance metrics in a table on the chart. RSI (Relative Strength Index): RSI Source: Choose the price data source for RSI calculation. RSI Length: Set the period for the RSI calculation. CCI (Commodity Channel Index): CCI Source: Select the price data source for CCI calculation. CCI Length: Determine the period for the CCI. SuperTrend: SuperTrend Factor: Adjust the sensitivity of the SuperTrend indicator. SuperTrend Length: Set the period for the SuperTrend calculation. DMI (Directional Movement Index): DMI Length: Define the period for DMI calculations. Parabolic SAR: PSAR Start: Initial acceleration factor for the Parabolic SAR. PSAR Increment: Increment value for the acceleration factor. PSAR Max Value: Maximum value the acceleration factor can reach. Notes/Recommendations: While this system is operational, it's important to recognize that it relies on "basic" indicators, which may not be ideal for generating trading signals on their own. I strongly suggest that users delve into the code to grasp the underlying logic of the system. Consider customizing it by integrating more sophisticated and higher-quality trend-following indicators to enhance its performance and reliability. Disclaimer: This system's backtest results are historical and do not predict future performance. Use for educational purposes only; not investment advice.
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InvestorUnknown tarafından
25
Smart DCA Strategy (Public)INSPIRATION While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness. The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy. WHY IS IT SMART? The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA. WHAT THIS STRATEGY IS, AND IS NOT This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used. You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed. HOW IT WORKS The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading. HOW TO USE Settings: The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap. The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results. Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets. In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered. You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings. Backtesting: When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading. The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost. Live Trading: After you've finished backtesting you can proceed with configuring your alerts for live trading. But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on BTCUSD Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day Enter that USD amount in the Blind buy size settings box Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period. After you have calculated the Smart buy size, you can go ahead and set up alerts on Smart DCA buy triggers. BOT AUTOMATION In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator. PLANNED FUTURE DEVELOPMENTS Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space! MARKETS Crypto: This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets. Stocks: I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish. Forex: As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex. For more info about this strategy including backtest results, please see the full description on the invite only version of this strategy named "Smart DCA Strategy"
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kevinmck100 tarafından
2
ICT Master Suite [Trading IQ]Hello Traders! We’re excited to introduce the ICT Master Suite by TradingIQ, a new tool designed to bring together several ICT concepts and strategies in one place. The Purpose Behind the ICT Master Suite There are a few challenges traders often face when using ICT-related indicators: Many available indicators focus on one or two ICT methods, which can limit traders who apply a broader range of ICT related techniques on their charts. There aren't many indicators for ICT strategy models, and we couldn't find ICT indicators that allow for testing the strategy models and setting alerts. Many ICT related concepts exist in the public domain as indicators, not strategies! This makes it difficult to verify that the ICT concept has some utility in the market you're trading and if it's worth trading - it's difficult to know if it's working! Some users might not have enough chart space to apply numerous ICT related indicators, which can be restrictive for those wanting to use multiple ICT techniques simultaneously. The ICT Master Suite is designed to offer a comprehensive option for traders who want to apply a variety of ICT methods. By combining several ICT techniques and strategy models into one indicator, it helps users maximize their chart space while accessing multiple tools in a single slot. Additionally, the ICT Master Suite was developed as a strategy . This means users can backtest various ICT strategy models - including deep backtesting. A primary goal of this indicator is to let traders decide for themselves what markets to trade ICT concepts in and give them the capability to figure out if the strategy models are worth trading! What Makes the ICT Master Suite Different There are many ICT-related indicators available on TradingView, each offering valuable insights. What the ICT Master Suite aims to do is bring together a wider selection of these techniques into one tool. This includes both key ICT methods and strategy models, allowing traders to test and activate strategies all within one indicator. Features The ICT Master Suite offers: Multiple ICT strategy models, including the 2022 Strategy Model and Unicorn Model, which can be built, tested, and used for live trading. Calculation and display of key price areas like Breaker Blocks, Rejection Blocks, Order Blocks, Fair Value Gaps, Equal Levels, and more. The ability to set alerts based on these ICT strategies and key price areas. A comprehensive, yet practical, all-inclusive ICT indicator for traders. Customizable Timeframe - Calculate ICT concepts on off-chart timeframes Unicorn Strategy Model 2022 Strategy Model Liquidity Raid Strategy Model OTE (Optimal Trade Entry) Strategy Model Silver Bullet Strategy Model Order blocks Breaker blocks Rejection blocks FVG Strong highs and lows Displacements Liquidity sweeps Power of 3 ICT Macros HTF previous bar high and low Break of Structure indications Market Structure Shift indications Equal highs and lows Swings highs and swing lows Fibonacci TPs and SLs Swing level TPs and SLs Previous day high and low TPs and SLs And much more! An ongoing project! How To Use Many traders will already be familiar with the ICT related concepts listed above, and will find using the ICT Master Suite quite intuitive! Despite this, let's go over the features of the tool in-depth and how to use the tool! The image above shows the ICT Master Suite with almost all techniques activated. ICT 2022 Strategy Model The ICT Master suite provides the ability to test, set alerts for, and live trade the ICT 2022 Strategy Model. The image above shows an example of a long position being entered following a complete setup for the 2022 ICT model. A liquidity sweep occurs prior to an upside breakout. During the upside breakout the model looks for the FVG that is nearest 50% of the setup range. A limit order is placed at this FVG for entry. The target entry percentage for the range is customizable in the settings. For instance, you can select to enter at an FVG nearest 33% of the range, 20%, 66%, etc. The profit target for the model generally uses the highest high of the range (100%) for longs and the lowest low of the range (100%) for shorts. Stop losses are generally set at 0% of the range. The image above shows the short model in action! Whether you decide to follow the 2022 model diligently or not, you can still set alerts when the entry condition is met. ICT Unicorn Model The image above shows an example of a long position being entered following a complete setup for the ICT Unicorn model. A lower swing low followed by a higher swing high precedes the overlap of an FVG and breaker block formed during the sequence. During the upside breakout the model looks for an FVG and breaker block that formed during the sequence and overlap each other. A limit order is placed at the nearest overlap point to current price. The profit target for this example trade is set at the swing high and the stop loss at the swing low. However, both the profit target and stop loss for this model are configurable in the settings. For Longs, the selectable profit targets are: Swing High Fib -0.5 Fib -1 Fib -2 For Longs, the selectable stop losses are: Swing Low Bottom of FVG or breaker block The image above shows the short version of the Unicorn Model in action! For Shorts, the selectable profit targets are: Swing Low Fib -0.5 Fib -1 Fib -2 For Shorts, the selectable stop losses are: Swing High Top of FVG or breaker block The image above shows the profit target and stop loss options in the settings for the Unicorn Model. Optimal Trade Entry (OTE) Model The image above shows an example of a long position being entered following a complete setup for the OTE model. Price retraces either 0.62, 0.705, or 0.79 of an upside move and a trade is entered. The profit target for this example trade is set at the -0.5 fib level. This is also adjustable in the settings. For Longs, the selectable profit targets are: Swing High Fib -0.5 Fib -1 Fib -2 The image above shows the short version of the OTE Model in action! For Shorts, the selectable profit targets are: Swing Low Fib -0.5 Fib -1 Fib -2 Liquidity Raid Model The image above shows an example of a long position being entered following a complete setup for the Liquidity Raid Modell. The user must define the session in the settings (for this example it is 13:30-16:00 NY time). During the session, the indicator will calculate the session high and session low. Following a “raid” of either the session high or session low (after the session has completed) the script will look for an entry at a recently formed breaker block. If the session high is raided the script will look for short entries at a bearish breaker block. If the session low is raided the script will look for long entries at a bullish breaker block. For Longs, the profit target options are: Swing high User inputted Lib level For Longs, the stop loss options are: Swing low User inputted Lib level Breaker block bottom The image above shows the short version of the Liquidity Raid Model in action! For Shorts, the profit target options are: Swing Low User inputted Lib level For Shorts, the stop loss options are: Swing High User inputted Lib level Breaker block top Silver Bullet Model The image above shows an example of a long position being entered following a complete setup for the Silver Bullet Modell. During the session, the indicator will determine the higher timeframe bias. If the higher timeframe bias is bullish the strategy will look to enter long at an FVG that forms during the session. If the higher timeframe bias is bearish the indicator will look to enter short at an FVG that forms during the session. For Longs, the profit target options are: Nearest Swing High Above Entry Previous Day High For Longs, the stop loss options are: Nearest Swing Low Previous Day Low The image above shows the short version of the Silver Bullet Model in action! For Shorts, the profit target options are: Nearest Swing Low Below Entry Previous Day Low For Shorts, the stop loss options are: Nearest Swing High Previous Day High Order blocks The image above shows indicator identifying and labeling order blocks. The color of the order blocks, and how many should be shown, are configurable in the settings! Breaker Blocks The image above shows indicator identifying and labeling order blocks. The color of the breaker blocks, and how many should be shown, are configurable in the settings! Rejection Blocks The image above shows indicator identifying and labeling rejection blocks. The color of the rejection blocks, and how many should be shown, are configurable in the settings! Fair Value Gaps The image above shows indicator identifying and labeling fair value gaps. The color of the fair value gaps, and how many should be shown, are configurable in the settings! Additionally, you can select to only show fair values gaps that form after a liquidity sweep. Doing so reduces "noisy" FVGs and focuses on identifying FVGs that form after a significant trading event. The image above shows the feature enabled. A fair value gap that occurred after a liquidity sweep is shown. Market Structure The image above shows the ICT Master Suite calculating market structure shots and break of structures! The color of MSS and BoS, and whether they should be displayed, are configurable in the settings. Displacements The images above show indicator identifying and labeling displacements. The color of the displacements, and how many should be shown, are configurable in the settings! Equal Price Points The image above shows the indicator identifying and labeling equal highs and equal lows. The color of the equal levels, and how many should be shown, are configurable in the settings! Previous Custom TF High/Low The image above shows the ICT Master Suite calculating the high and low price for a user-defined timeframe. In this case the previous day’s high and low are calculated. To illustrate the customizable timeframe function, the image above shows the indicator calculating the previous 4 hour high and low. Liquidity Sweeps The image above shows the indicator identifying a liquidity sweep prior to an upside breakout. The image above shows the indicator identifying a liquidity sweep prior to a downside breakout. The color and aggressiveness of liquidity sweep identification are adjustable in the settings! Power Of Three The image above shows the indicator calculating Po3 for two user-defined higher timeframes! Macros The image above shows the ICT Master Suite identifying the ICT macros! ICT Macros are only displayable on the 5 minute timeframe or less. Strategy Performance Table In addition to a full-fledged TradingView backtest for any of the ICT strategy models the indicator offers, a quick-and-easy strategy table exists for the indicator! The image above shows the strategy performance table in action. Keep in mind that, because the ICT Master Suite is a strategy script, you can perform fully automatic backtests, deep backtests, easily add commission and portfolio balance and look at pertinent metrics for the ICT strategies you are testing! Lite Mode Traders who want the cleanest chart possible can toggle on “Lite Mode”! In Lite Mode, any neon or “glow” like effects are removed and key levels are marked as strict border boxes. You can also select to remove box borders if that’s what you prefer! Settings Used For Backtest For the displayed backtest, a starting balance of $1000 USD was used. A commission of 0.02%, slippage of 2 ticks, a verify price for limit orders of 2 ticks, and 5% of capital investment per order. A commission of 0.02% was used due to the backtested asset being a perpetual future contract for a crypto currency. The highest commission (lowest-tier VIP) for maker orders on many exchanges is 0.02%. All entered positions take place as maker orders and so do profit target exits. Stop orders exist as stop-market orders. A slippage of 2 ticks was used to simulate more realistic stop-market orders. A verify limit order settings of 2 ticks was also used. Even though BTCUSDT.P on Binance is liquid, we just want the backtest to be on the safe side. Additionally, the backtest traded 100+ trades over the period. The higher the sample size the better; however, this example test can serve as a starting point for traders interested in ICT concepts. Community Assistance And Feedback Given the complexity and idiosyncratic applications of ICT concepts amongst its proponents, the ICT Master Suite’s built-in strategies and level identification methods might not align with everyone's interpretation. That said, the best we can do is precisely define ICT strategy rules and concepts to a repeatable process, test, and apply them! Whether or not an ICT strategy is trading precisely how you would trade it, seeing the model in action, taking trades, and with performance statistics is immensely helpful in assessing predictive utility. If you think we missed something, you notice a bug, have an idea for strategy model improvement, please let us know! The ICT Master Suite is an ongoing project that will, ideally, be shaped by the community. A big thank you to the @PineCoders for their Time Library! Thank you!
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Trading-IQ tarafından
29