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Strategy: bbrsis
Downloaded: 20220112
Stoploss: -0.99
5mSpotv2UnbiasedLink


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Average Overall
BuysAvgprofTotProfWin%DD%Time
223.75-0.05-4.375110.988.85
SharpeSortinoCalmar
-2.75-3.42-5.02
Prof.FactorExpectancyCagr
0.3800
Trades/DayRejected Signals
7.7843.5
Ninja Score: 54
The BBRSIS strategy is a trading strategy implemented in Python using the Freqtrade library. It utilizes several technical indicators to generate buy and sell signals for trading. The strategy calculates various indicators to make trading decisions, including: Simple Moving Averages (SMA) with different time periods (5, 75, and 200) for trend analysis.

Relative Strength Index (RSI) with a time period of 20 for momentum analysis.

Bollinger Bands (BB) with a window of 20 and 3 standard deviations for volatility analysis.

The strategy's main logic for generating buy signals is as follows: The closing price is below the lower Bollinger Band. The 5-period SMA is above the 75-period SMA, and the 75-period SMA is above the 200-period SMA. The RSI is lower than the RSI calculated on a resampled dataframe with a time period equal to three times the ticker interval. The trading volume is greater than 0. The strategy's main logic for generating sell signals is as follows: The closing price is above the middle Bollinger Band. The RSI is higher than the RSI calculated on resampled dataframes with time periods equal to three times, six times, and ten times the ticker interval. The trading volume is greater than 0. The strategy aims to achieve a minimal return on investment (ROI) of 0.30 and uses a stop-loss of -0.99. It operates on a ticker interval of 5 minutes. Please note that this is just a brief description of the strategy's functionality based on the provided code snippet.

stoploss: -0.99
timeframe: 5m
hash(sha256): c5932fb833f3317f498985b36adb6232c66a969fda9e1c61bf33eeb3c1e20a01
indicators:
sma5 sma75 mid lower upper
volume _long _short bb_middleband rsi
close _shortrsi _longrsi _medium bb_upperband
bb_lowerband _mediumrsi sma200

No similar strategies found. (based on used indicators)

last change: 2024-05-02 21:43:43