๐ฏ this is a optimized version based on ATR_RSI_Strategy with no-repaint. Sharpe ratio: 1.4, trade times: 116 , trade symbol: BINANCE:BTCUSDTPERP 15M you can get same backtesting result with the correct settings.
๐ฒ Strategy Logic
๐ฏ the core logic is quite simple, use ATR and RSI and SMA 1. when price is in high volatility ( atr_value > atr_ma); 2. wait for a break signal (rsi_value > rsi_buy or rsi_value < rsi_sell); 3. entry Long or Short,use trailing stop-loss to max security and percent TP to keep profit.
๐ฒ Settings
๐ฏ there are 7 input properties in script, but I only finetune 4 of them (bold field below), you may change other parameter to get better result by yourself.
atr_length: length to get atr value
atr_ma_length: length of smoothing atr value
atr_ma_norm_min: atr_ma normalized min value, filter high volatility ranges
atr_ma_norm_max: atr_ma normalized max value, filter high volatility ranges
rsi_length: length to get rsi value
rsi_entry: 50 +/- rsi_entry to get entry threshold
trailing_percent: trailing stop-loss percent
๐ฒ Usage
๐ฏ the commission set to 0.05%, part of exchange the commission is less than 0.05% in reality, but I will still use 0.05% in my next script.
๐ฏ this script use 50% of equity to size positions follow general script position, you can adjust the value to fix size or 100% of equity to compare result with other strategy, but I still suggest you use 5-10% of equity for each strategy in reality.
๐ฏany questions please comment below. if there are any words violate House Rule, please tell me below and i will revise immediately don't want be hiddened again ๐๐
Additionally, I plan to publish 20 profitable strategies in 2023; letโs witness it together!
Hope this strategy will be usefull for you :)
enjoy! ๐๐๐
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update Order size from 50% to 10% of equity, is usually more realistic for each strategy.
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update script format and remarks for properties.
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add alert. 1. when in living trading, Enter after freq_once_per_bar_close 2. when in living trading, SL and TP should use freq_once_per_bar 3. you can compare with trade_list of backtest result thx for @jeroenderouw92 feedback. ๐