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FTSE FridaysThis code snippet below is a quick and dirty follow up to some statistical analysis performed on the FTSE 100. It showed that over the long run, (since 1995) going long on a Friday appeared to have a statistical edge (53%). As a bit of fun, I wanted to create a quick pine script backtest to test this and see if it is possible to profit from it. After all, the index might finish up 53% of the time, but that doesn't mean one can profit from it. A full commentary to the script and FTSE analysis post can be found on the Backtest-Rookies website. To comply with house rules, I cannot post a direct link here. Important Note The script must run on the 4H time frame…..Why? It is a quick and dirty implementation and it relies on entering a long position on the 4H bar before the market opens. This way the position will enter at the open of the market. (Since positions are always opening on the bar following an entry signal).
Strategia Pine Script®
di BacktestRookies
System 0530 - Stoch RSI Strategy with ATR filterStrategy Description: System 0530 - Multi-Timeframe Stochastic RSI with ATR Filter Overview: This strategy, "System 0530," is designed to identify trading opportunities by leveraging the Stochastic RSI indicator across two different timeframes: a shorter timeframe for initial signal triggers (assumed to be the chart's current timeframe, e.g., 5-minute) and a longer timeframe (15-minute) for signal confirmation. It incorporates an ATR (Average True Range) filter to help ensure trades are taken during periods of adequate market volatility and includes a cooldown mechanism to prevent rapid, successive signals in the same direction. Trade exits are primarily handled by reversing signals. How It Works: 1. Signal Initiation (e.g., 5-Minute Timeframe): Long Signal Wait: A potential long entry is considered when the 5-minute Stochastic RSI %K line crosses above its %D line, AND the %K value at the time of the cross is at or below a user-defined oversold level (default: 30). Short Signal Wait: A potential short entry is considered when the 5-minute Stochastic RSI %K line crosses below its %D line, AND the %K value at the time of the cross is at or above a user-defined overbought level (default: 70). When these conditions are met, the strategy enters a "waiting state" for confirmation from the 15-minute timeframe. 2. Signal Confirmation (15-Minute Timeframe): Once in a waiting state, the strategy looks for confirmation on the 15-minute Stochastic RSI within a user-defined number of 5-minute bars (wait_window_5min_bars, default: 5 bars). Long Confirmation: The 15-minute Stochastic RSI %K must be greater than or equal to its %D line. The 15-minute Stochastic RSI %K value must be below a user-defined threshold (stoch_15min_long_entry_level, default: 40). Short Confirmation: The 15-minute Stochastic RSI %K must be less than or equal to its %D line. The 15-minute Stochastic RSI %K value must be above a user-defined threshold (stoch_15min_short_entry_level, default: 60). 3. Filters: ATR Volatility Filter: If enabled, trades are only confirmed if the current ATR value (converted to ticks) is above a user-defined minimum threshold (min_atr_value_ticks). This helps to avoid taking signals during periods of very low market volatility. If the ATR condition is not met, the strategy continues to wait for the condition to be met within the confirmation window, provided other conditions still hold. Signal Cooldown Filter: If enabled, after a signal is generated, the strategy will wait for a minimum number of bars (min_bars_between_signals) before allowing another signal in the same direction. This aims to reduce overtrading. 4. Entry and Exit Logic: Entry: A strategy.entry() order is placed when all trigger, confirmation, and filter conditions are met. Exit: This strategy primarily uses reversing signals for exits. For example, if a long position is open, a confirmed short signal will close the long position and open a new short position. There are no explicit take profit or stop loss orders programmed into this version of the script. Key User-Adjustable Parameters: Stochastic RSI Parameters: RSI Length, Stochastic RSI Length, %K Smoothing, %D Smoothing. Signal Trigger & Confirmation: 5-minute %K trigger levels for long and short. 15-minute %K confirmation thresholds for long and short. Wait window (in 5-minute bars) for 15-minute confirmation. Filters: Enable/disable and configure the Signal Cooldown filter (minimum bars between signals). Enable/disable and configure the ATR Volatility filter (ATR period, minimum ATR value in ticks). Strategy Parameters: Leverage Multiplier (Note: This primarily affects theoretical position sizing for backtesting calculations in TradingView and does not simulate actual leveraged trading risks). Recommendations for Users: Thorough Backtesting: Test this strategy extensively on historical data for the instruments and timeframes you intend to trade. Parameter Optimization: Experiment with different parameter settings to find what works best for your trading style and chosen markets. The default values are starting points and may not be optimal for all conditions. Understand the Logic: Ensure you understand how each component (Stochastic RSI on different timeframes, ATR filter, cooldown) interacts to generate signals. Risk Management: Since this version does not include explicit stop-loss orders, ensure you have a clear risk management plan in place if trading this strategy live. You might consider manually adding stop-loss orders through your broker or using TradingView's separate strategy order settings for stop-loss if applicable. Disclaimer: This strategy description is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Trading involves significant risk of loss. Always do your own research and understand the risks before trading.
Strategia Pine Script®
di Archertoria
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean. The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests. In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal. In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system. I just wanted to play a bit with the Z-score I guess. Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally. How it works: This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is. In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars. The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score. Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods. Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods. Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa. Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
Strategia Pine Script®
di jensenvilhelm
3
Wunder DCA BotThe bot is based on the DCA system. 1. DCA is the investment method in which you buy a certain portion of the asset after the determined price deviation. 2. For entry, we evaluate the maximum and minimum levels for a given period that you can adjust in the script. The bot enters when price rebound from the specified levels. 3. For the exit, the bot will use the take profit percentage that you will specify in settings. It is also possible to choose how the take profit is calculated either from the average entry price or from the entry order (first order). 4. DCA uses the following settings: - Base order Volume: Volume of your first order on entry signal - Subsequent orders volume: The volume of all subsequent orders except the first - DCA orders count: This parameter will determine how many entries your overall strategy will have. For example: If you will put 3, that will mean that including your initial position you will have 2 additional orders. - DCA order price deviation: This is the value in % which determines the deviation of the additional entries from the entry price. Example: If you go long and the price of the asset is 100$ and you put an order price deviation of 1% that will mean that the first additional entry will occur when the price will drop by 1%, and the second entry will be triggered when the overall price will drop by 2% (as the interval between the first and the second additional entry will be 1%). - DCA Order Volume Multiplier: This parameter will determine the amount that you put into each additional position. If this parameter is equal to 1 that means that each additional entry will be equal to the initial amount. The extra volume will be added to your position from the second DCA entry. Example: Your initial position was 10$ and your Volume Multiplier is set to 2. When you reach your 1st DCA target your additional order will have the same volume of 10$. When you reach your 2nd DCA target your additional order will be 20$ (previous position volume * multiplier). Your 3rd DCA target will place the order of 40$. - DCA order price Deviation Multiplier: This value will increase the price deviation between each additional entry. It is calculated as the price deviation multiplied by the deviation multiplier. For example: if you enter long at the price 100$ and have a price deviation of 1% with the price deviation multiplier of 2 that will mean that the first additional entry will occur when the price will drop to 99$ however the second will occur when the price will go to 97$. The third additional position will be entered at 94$ 5. For full automation of the bot, you should set your comments to the input in the bot settings in the "LONG" and "SHORT" fields. You also need to create an alert signal and set a Webhook to send signals. IMPORTANT!!! 1. Position calculation should take into account several factors: your deposit, leverage, the number of DCA orders, the distance to the last DCA order; 2. When choosing leverage, it is important to correctly calculate the possible drawdown. If you set a high leverage value, then liquidation awaits and the bot will not be able to take profits and will exit the position ahead of time; 3. The size of the position must be determined in accordance with all risks and take into account the size of your deposit; 4. This DCA Bot is able to earn consistently with the correct calculated money management.
Strategia Pine Script®
di Wunderbit
62
Volatility Stop Strategy (by Coinrule)Traders often use the volatility stop to protect trades dynamically, adjusting the stop price gradually based on the asset's volatility. Just like the volatility stop is a great way to capture trend reversals on the downside, the opposite applies as well. Therefore, another useful application of the volatility stop is to add it to a trading system to signal potential trend reversals to catch a good buy opportunity. ENTRY - When the price crosses above the Volatility Stop EXIT - When the price crosses below the Volatility Stop For this strategy, the Volatility stop's multiplier is set to 3 to allow more flexibility to the trade. The strategy is designed for medium-term trades. Based on the backtest result from a sample of crypto trading pairs, the most profitable time frame is the 2-hr. The strategy works well with both crypto-to-crypto and crypto-to-fiat pairs. To make results more realistic, a trading fee of 0.1% is added to the script. The fee is aligned to the base fee applied on Binance.
Strategia Pine Script®
di Coinrule
2
Bagheri IG Ether v2In this version, the winning ratio has been decreased, but the Risk to Reward Ratio (RRR) has been set to be better than the previous version. This is a technical trading strategy for Ethereum ( BINANCE:ETHUSDT ). We built and developed it on MetaEditor and optimized it with MetaTrader optimizer. The main indicators are Donchian Channel, Oscillator of ROC , Bears Power, Balance of Power , and Simple Moving Average ( SMA ). Default values in the input panel are the best combination of these indicators, but you can change any of them and try it for better results. Please notice that this strategy has been optimized on the 1-minute chart of Ethereum . For each position, you can see the Take Profit (TP) and Stop Loss (SL) levels. Also, you can find the values of mentioned TP and SL in points from the input panel of the script. Attention: The price of Ethereum has 2 decimal places. Therefore, 3000 points for TP means 30 USDT for trading 1 BINANCE:ETHUSDT .
Strategia Pine Script®
di Bagheri_IG
Bagheri IG EtherThis is a technical trading strategy for Ethereum ( BINANCE:ETHUSDT ). We built and developed it on MetaEditor and optimized it with MetaTrader optimizer. The main indicators are Donchian Channel, Oscillator of ROC, Bears Power, Balance of Power, and Simple Moving Average (SMA). Default values in the input panel are the best combination of these indicators, but you can change any of them and try it for better results. Please notice that this strategy has been optimized on the 1-minute chart of Ethereum. For each position, you can see the Take Profit (TP) and Stop Loss (SL) levels. Also, you can find the values of mentioned TP and SL in points from the input panel of the script. Attention: The price of Ethereum has 2 decimal places. Therefore, 3000 points for TP means 30 USDT for trading 1 BINANCE:ETHUSDT .
Strategia Pine Script®
di Bagheri_IG
SNAP BACK 2.0 Strategy This strategy is designed to allow you to catch the bounce or "SNAP Back" of an equity that has been in a trend. 1) Once the moving averages are in the order of 200SMA > 50 SMA > 34EMA > 20SMA > 8EMA (or reverse for and uptrend), the strategy is setup. 2) Next you wait for a trigger of the closing price crossing the 8EMA, while there is a desired gap size between the 8EMA and the 20SMA (2-10% of stock value preferred). 3) Exit position based on target profit reached (conservative sell half at 34EMA and engage a trailing stop loss for remainder or set static limit) or price crosses 8EMA or stop loss% *)This code also allows you to determine your desired backtesting date compliments of alanaster This code is the product of many hours of hard work on the part of the greater tradingview community. The credit goes to everyone in the community who has put code out there for the greater good. The idea for the coding came from a video I watched on YouTube presented by TradeStation called Snap Back - thank you guys for the inspiration. UPDATE: I have coded the other side of the strategy to allow you to take advantage of the same set-up in an uptrend for Short plays. You can turn the up or downsides on, off, or both. The main intent is to catch the bounces of a falling stock. However, I have found that you can do the inverse and catch the drops in a rising stock (the latter is not as reliable). This also tends to work better on less volatile stocks. I have included a large volume of user defined conditions and display entry and exit conditions on the chart to see how your choices are impacting the script.
Strategia Pine Script®
di MakeMoneyCoESTB2020
RSI of Ultimate Oscillator [SHORT Selling] StrategyThis is SHORT selling strategy with Ultimate Oscillator. Instead of drectly using the UO oscillator , I have used RSI on UO (as I did in my previous strategies ) Ultimator Oscillator settings are 5, 10 and 15 RSI of UO setting is 5 Short Sell ========== I have used moving averages from WilliamAlligator indicator --- settings are 10(Lips), 20(teeth) and 50 (Jaw) when Lips , Teeth and Jaw are aligned to downtrend (that means Lips < Teeth < Jaw ) Look for RSIofUO dropping below 60 ( setting parameter is Sell Line ) Partial Exit ========== When RSIofUO crossing up Oversold line i.e 30 Cover Short / Exit ================= When RSIofUO crosisng above overbought line i.e 70 StopLoss ======== StopLoss defaulted to 3 % , Though it is mentioned in settings , it has not been not used to calcuate and StopLoss Exit... Reason is, when RSIofUO already crossed 60 line (for SHORTING) , then it would take more efforts go up beynd 60. There is saying price takes stairs to climb up but it takes elevator to go down. I have not purely depend on this to exit stop loss, however noticed the trades in this stratgey did not get out with loss higher than when RSIofUO reaching 70 level. Note ====== Williams Alligator is not drawn from the script. It is manually added to chart for illustration purpose. Please add it when you are using this strategy , whch woould give an idea how the strategy is taking Short Trades. This is tested on Hourly chart for SPY Bar color changes to purple when the strategy is in SHORT trade Warning ======== For the eductional purposes only
Strategia Pine Script®
di eemani123
2
RSI Alligator StrategyHello trading family! Just wanted to give a quick write up and share the new code for the RSI Alligator Strategy. I amended it to show every crossover signal, weak and strong, so we can accurately gauge its effectiveness. Having played with this for a couple hours now I have learned a few things -Using Heikin Ashi seems to smooth it out a bit and provides about 20% fewer signals, leading to overall more accuracy. However, it can be misleading as the Heikin Ashi opening price doesn't always line up with the market price, especially in cases of large moves. Overall though it didn't seem too far off except for a few instances. -Also, using the Heikin Ashi gives you a better idea of the trend, which this indicator is primarily used to detect and exploit. -Having tested on TF of 1H-1D, overall profitability is found to be highest between 4H-12H, with 1D giving the "safest" longer term signals, and lower TF's generating many more signals due to volatility. -Instead of waiting for the next signal in order to close, you can often use a crossover/crossunder of the 5 and 13 to close the previous trade, especially if paired with a Heikin Ashi of opposite color (green to close a short, red to close a long) -You will also notice several instances where the Green 5 period show divergences that aren't visible on the regular RSI, another handy little feature So far I have still only tested this on BTCUSD. Feel free to apply it to any coin and let me know what you find. Here is the script. If you have any ideas or suggestions please let me know!
Strategia Pine Script®
di Bitcoinnoisseur
3
CryptoWise4hETHstrategyCrypto Wise 4h ETH Trading Script with Alerts ETH is very volatile, and that's what makes this script great: Being able to catch the next Move Up or Down. No repainting. Better to be used on a 4hr Chart. No indicator is perfect, but when it gets integrated into a great strategy, and used together with other indicators like the Stoch RSI , you can easily make great trades. You can get access to the script for $20 / month. Payments accepted in BTC, ETH, LTC, BCH. 72hr Trial given upon request.
Strategia Pine Script®
di wisecrypto
7
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy. Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade. My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength. My sell strategy is triggered by either one of these conditions: the EMA(6) of the close value is crossing under the trailing stop value (green) or the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength. The trailing stop value (green) is set to a multiple of the ATR(15) value. ATR(15) is the SMA(15) value of the difference between the high and low values. The scripts shows a lot of graphical information: The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade. the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end)) the EMA and SMA values for both buy and sell signals are shown as a line the buy and sell(close) signals are labeled in blue How to use this strategy? Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR). Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters) Then keep using these parameters for future buy/sell signals only for that particular stock. Do the same for other stocks. Important : optimizing these parameters is no guarantee for future winning trades! Here are the parameters: Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20) Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100) Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120) Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20) Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100) Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120) Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20) Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing): BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20 NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78% BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9 NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55% AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8 NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938% TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14 NetProfit: 129%, #Trade
Strategia Pine Script®
di XPl0RR
8
Holy GrailThis is a long-only educational strategy that simulates what happens if you keep adding to a position during pullbacks and only exit when the asset hits a new All-Time High (ATH). It is intended for learning purposes only — not for live trading. 🧠 How it works: The strategy identifies pullbacks using a simple moving average (MA). When price dips below the MA, it begins monitoring for the first green candle (close > open). That green candle signals a potential bottom, so it adds to the position. If price goes lower, it waits for the next green candle and adds again. The exit happens after ATH — it sells on each red candle (close < open) once a new ATH is reached. You can adjust: MA length (defines what’s considered a pullback) Initial buy % (how much to pre-fill before signals start) Buy % per signal (after pullback green candle) Exit % per red candle after ATH 📊 Intended assets & timeframes: This strategy is designed for broad market indices and long-term appreciating assets, such as: SPY, NASDAQ, DAX, FTSE Use it only on 1D or higher timeframes — it’s not meant for scalping or short-term trading. ⚠️ Important Limitations: Long-only: The script does not short. It assumes the asset will eventually recover to a new ATH. Not for all assets: It won't work on assets that may never recover (e.g., single stocks or speculative tokens). Slow capital deployment: Entries happen gradually and may take a long time to close. Not optimized for returns: Buy & hold can outperform this strategy. No slippage, fees, or funding costs included. This is not a performance strategy. It’s a teaching tool to show that: High win rate ≠ high profitability Patience can be deceiving Many signals = long capital lock-in 🎓 Why it exists: The purpose of this strategy is to demonstrate market psychology and risk overconfidence. Traders often chase strategies with high win rates without considering holding time, drawdowns, or opportunity cost. This script helps visualize that phenomenon.
Strategia Pine Script®
di Intetics
KST Strategy [Skyrexio]Overview KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades. Unique Features ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation. Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions. Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold. Methodology The strategy opens long trade when the following price met the conditions: Close price is above the Alligator's jaw line Close price is above the filtering Moving average KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology) If the Choppiness Index filter is enabled its value shall be less than user defined threshold When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed. Strategy settings In the inputs window user can setup the following strategy settings: ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level) ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level) Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA) Filter MA Length (by default = 200, length for filter MA calculation) Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index) Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution) Choppiness Index Length (by default = 14, length used in Choppiness index calculation) KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology) KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology) KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology) KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology) User can choose the optimal parameters during backtesting on certain price chart. Justification of Methodology Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index. The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago. ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value: KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4 ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1, ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2, ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3, ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4 Also for this indicator the signal line is calculated: Signal = SMA(KST, KST Signal Line Length) When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends. Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages: Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead. Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward. Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward. When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades. The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it. The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA. Key Features: It reacts faster to price changes than most moving averages. It is smoother and less noisy than short-term EMAs. It can be used to identify trend direction, momentum, and potential reversal points. ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction. To calculate it first of all we need to get True Range (TR), this is the greatest value among: High - Low abs(High - Previous Close) abs(Low - Previous Close) ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14. ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market. The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend. Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n) where: ΣATR(n) = sum of the Average True Range over n periods MaxHigh(n) = highest high over n periods MinLow(n) = lowest low over n periods log10 = base-10 logarithm Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning. Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value. When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close. Backtest Results Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions. Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks. Initial capital: 10000 USDT Percent of capital used in every trade: 60% Maximum Single Position Loss: -5.53% Maximum Single Profit: +8.35% Net Profit: +5175.20 USDT (+51.75%) Total Trades: 120 (56.67% win rate) Profit Factor: 1.747 Maximum Accumulated Loss: 1039.89 USDT (-9.1%) Average Profit per Trade: 43.13 USDT (+0.6%) Average Trade Duration: 27 hours These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. How to Use Add the script to favorites for easy access. Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT). Configure settings using the dropdown choice list in the built-in menu. Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}} Disclaimer: Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Strategia Pine Script®
di Skyrexio
Three Candle Bullish Engulfing StrategyThe Three Candle Bullish Engulfing Strategy is a versatile, multi-mode trading system designed for TradingView, combining classic candlestick patterns with momentum confirmation and dynamic risk management. This script supports both swing trading and intraday approaches, as well as an optional RSI-based breakout mode for additional signal filtering. Key Features: Three Candle Pattern Detection: The strategy identifies potential trend reversal points using a three-candle pattern: The first candle is a strong bullish (or bearish) move. The second candle is a doji or small-bodied candle, indicating indecision. The third candle is a bullish (or bearish) engulfing candle that closes above (or below) the previous high (or low), confirming the reversal. Flexible Trading Modes: Swing Long Only: Enter long trades on bullish three-candle setups. Intraday Long & Short: Trade both long and short based on bullish and bearish three-candle patterns, with automatic session-end exits. RSI Breakout Mode: Enter long trades when the 1-hour RSI exceeds a user-defined threshold (default 80) and a bullish candle forms, with breakout confirmation and a fixed-percentage stop loss. Visual Aids: Plots the RSI breakout trigger price and stop loss on the chart for easy monitoring. How It Works: Three Candle Pattern Entries: Long Entry: Triggered when a bullish candle is followed by a doji, then a bullish engulfing candle closes above the previous high. Short Entry (Intraday only): Triggered by the inverse pattern—bearish candle, doji, then bearish engulfing candle closing below the previous low. RSI Breakout Entries: When the RSI on a higher timeframe (default 1 hour) exceeds the set threshold and a bullish candle forms, the script records a trigger price. A long trade is entered if the price breaks above this trigger, with a stop loss set a fixed percentage below. Exits: Positions are closed if the trailing stop is hit, the session ends (for intraday mode), or the stop loss is triggered in RSI breakout mode. In RSI breakout mode, positions are also closed if a new breakout trigger forms while in position.
Strategia Pine Script®
di Somwereinhell
AltCoin Index Correlation🧠 AltCoin Index Correlation — Strategy Overview AltCoin Index Correlation is a dynamic EMA-based trading strategy designed primarily for altcoins, but also adaptable to stocks and indices, thanks to its flexible reference index system. 🧭 Strategy Philosophy The core idea behind this strategy is simple yet powerful: Price action becomes more meaningful when it aligns with broader market context. This script analyzes the correlation between the asset’s trend and a reference index trend, using dual EMA (Exponential Moving Average) crossovers for both. When both the altcoin and the reference index (e.g. Altcoin Dominance, BTC Dominance, Total Market Cap, or even indices like the NASDAQ 100 or S&P 500) are aligned in trend direction, the script considers it a high-confidence setup. It also includes: Optional inverse correlation logic (for contrarian setups) Custom leverage settings (e.g., 1x, 1.8x, etc.) A dynamic scale-out mechanism during weakening trends Date filtering for controlled backtests A live performance dashboard with equity, PnL, win rate, drawdown, APR, and more ⚙️ Default Settings & Backtest Results Timeframe tested: 1H Test date: May 20, 2025 Sample: 100 high-cap altcoins Reference index: CRYPTOCAP:OTHERS.D (Altcoin Dominance) Leverage: 1.8x (180% of capital used) 📊 With default settings: Win rate: ~80% Higher profits, due to increased exposure Best suited for confident trend followers with higher risk tolerance 📉 With fixed capital or 1x leverage: Win rate improves to ~90% Lower returns, but greater capital preservation Ideal for conservative or risk-managed trading styles 🔄 Versatility While tailored for altcoins, this strategy supports traditional markets as well: Easily switch the reference index to OANDA:NAS100USD or S&P 500 for stock correlation trading Adjust EMA lengths and leverage to match the asset class and volatility profile 🧩 Suggested Use Best used on trending markets (not sideways) Ideal for 1H timeframes, but adjustable Suitable for traders who want a rules-based, macro-aware entry/exit system Try it out, customize it to your style, try different settings and share your results with the community! Feedback is welcome — and improvements are always in progress. 🚀 ### Check my profile for other juicy hints and original strategies. ### 🚀
Strategia Pine Script®
di Eddie_Bitcoin
5
Liquidity Grab Strategy (Volume Trap)🧠 Strategy Logic: Liquidity Grab Detection: The script looks for a sharp drop in price (bearish engulfing or breakdown candle). However, volume remains flat (within 5% of the 20-period moving average), suggesting the move is manipulated, not genuine. Fair Value Gap Confirmation (FVG): It confirms that a Fair Value Gap exists — a gap between recent candle bodies that price is likely to retrace into. This gap represents a high-probability entry zone. Trade Setup: A limit BUY order is placed at the base of the FVG. Stop Loss (SL) is placed below the gap. Take Profit (TP) is placed at the most recent swing high. 📈 How to Use It: Add the strategy to your TradingView chart (1–5 min or 15 min works well for intraday setups). Look for green BUY labels and plotted lines: 💚 Green = Entry price 🔴 Red = Stop loss 🔵 Blue = Take profit The script will automatically simulate entries when conditions are met and exit either at TP or SL. Use TradingView’s Strategy Tester to review: Win rate Net profit Risk-adjusted performance
Strategia Pine Script®
di davidmdan
Triangle Breakout Strategy with TP/SL, EMA Filter📌 Triangle Breakout Strategy with TP/SL, EMA Filters, and Backtest – Explained. ✅ 1. Pattern Detection – Triangle Breakout The script scans for triangle patterns by detecting local pivot highs and pivot lows. It uses two recent highs and two recent lows to draw converging trendlines (upper and lower boundaries of the triangle). If the price breaks above the upper trendline, a bullish breakout signal is generated. 🎯 2. TP (Take Profit) & SL (Stop Loss) When a bullish breakout is detected: A buy order is placed using strategy.entry. TP and SL levels are calculated relative to the current close price: TP = 3% above the entry price SL = 1.5% below the entry price These are defined using strategy.exit. 📊 3. EMA Filter An optional filter checks if: Price is above both EMA 20 and EMA 50 Only if this condition is met, the strategy allows a long entry. You can toggle the filter on or off with useEMAFilter. 📈 4. Backtesting with Strategy Tester This script uses strategy() instead of indicator() to enable TradingView’s built-in backtest engine. Every buy entry and exit (based on TP or SL) is recorded. 📌 5. Visuals EMA 20 and EMA 50 lines are plotted on the chart. A label is shown when a breakout is detected: "Breakout Up" Results (profit, win rate, drawdown, etc.) can be viewed in the Strategy Tester panel.
Strategia Pine Script®
di Reanimate_
Arbitrage Spot-Futures Don++Strategy: Spot-Futures Arbitrage Don++ This strategy has been designed to detect and exploit arbitrage opportunities between the Spot and Futures markets of the same trading pair (e.g. BTC/USDT). The aim is to take advantage of price differences (spreads) between the two markets, while minimizing risk through dynamic position management. [Operating principle The strategy is based on calculating the spread between Spot and Futures prices. When this spread exceeds a certain threshold (positive or negative), reverse positions are opened simultaneously on both markets: - i] Long Spot + Short Futures when the spread is positive. - i] Short Spot + Long Futures when the spread is negative. Positions are closed when the spread returns to a value close to zero or after a user-defined maximum duration. [Strategy strengths 1. Adaptive thresholds : - Entry/exit thresholds can be dynamic (based on moving averages and standard deviations) or fixed, offering greater flexibility to adapt to market conditions. 2. Robust data management : - The script checks the validity of data before executing calculations, thus avoiding errors linked to missing or invalid data. 3. Risk limitation : - A position size based on a percentage of available capital (default 10%) limits exposure. - A time filter limits the maximum duration of positions to avoid losses due to persistent spreads. 4. Clear visualization : - Charts include horizontal lines for entry/exit thresholds, as well as visual indicators for spread and Spot/Futures prices. 5. Alerts and logs : - Alerts are triggered on entries and exits to inform the user in real time. [Points for improvement or completion Although this strategy is functional and robust, it still has a few limitations that could be addressed in future versions: 1. [Limited historical data : - TradingView does not retrieve real-time data for multiple symbols simultaneously. This can limit the accuracy of calculations, especially under conditions of high volatility. 2. [Lack of liquidity management : - The script does not take into account the volumes available on the order books. In conditions of low liquidity, it may be difficult to execute orders at the desired prices. 3. [Non-dynamic transaction costs : - Transaction costs (exchange fees, slippage) are set manually. A dynamic integration of these costs via an external API would be more realistic. 4. User-dependency for symbols : - Users must manually specify Spot and Futures symbols. Automatic symbol validation would be useful to avoid configuration errors. 5. Lack of advanced backtesting : - Backtesting is based solely on historical data available on TradingView. An implementation with third-party data (via an API) would enable the strategy to be tested under more realistic conditions. 6. [Parameter optimization : - Certain parameters (such as analysis period or spread thresholds) could be optimized for each specific trading pair. [How can I contribute? If you'd like to help improve this strategy, here are a few ideas: 1. Add additional filters: - For example, a filter based on volume or volatility to avoid false signals. 2. Integrate dynamic costs: - Use an external API to retrieve actual costs and adjust thresholds accordingly. 3. Improve position management: - Implement hedging or scalping mechanisms to maximize profits. 4. Test on other pairs: - Evaluate the strategy's performance on other assets (ETH, SOL, etc.) and adjust parameters accordingly. 5. Publish backtesting results : - Share detailed analyses of the strategy's performance under different market conditions. [Conclusion This Spot-Futures arbitrage strategy is a powerful tool for exploiting price differentials between markets. Although it is already functional, it can still be improved to meet more complex trading scenarios. Feel free to test, modify and share your ideas to make this strategy even more effective! [Thank you for contributing to this open-source community! If you have any questions or suggestions, please feel free to comment or contact me directly.
Strategia Pine Script®
di DonKabu