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Strategy: CombinedBinHAndClucV7
Downloaded: 20220113
Stoploss: -0.99
5mSpotv2UnbiasedLink


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Average Overall
BuysAvgprofTotProfWin%DD%Time
52.250.110.9765.754.554.6
SharpeSortinoCalmar
1.061.229.54
Prof.FactorExpectancyCagr
0.3400
Trades/DayRejected Signals
1.952.75
Ninja Score: 59
The CombinedBinHAndClucV7 strategy is a trading strategy implemented as a class in Python. Here is a brief description of what the strategy does: The populate_indicators method is responsible for populating the indicators used in the strategy. It takes a DataFrame containing market data and a metadata dictionary as input and returns the modified DataFrame with the indicators added.

The populate_buy_trend method is used to determine the buy signals based on certain conditions.

It takes the DataFrame with populated indicators and metadata as input and returns the DataFrame with a 'buy' column indicating the buy signals.

The populate_sell_trend method is responsible for determining the sell signals based on specific conditions. It takes the DataFrame with populated indicators and metadata as input and returns the DataFrame with a 'sell' column indicating the sell signals. The strategy uses a combination of different indicators, such as exponential moving averages (ema), Bollinger Bands (bb), relative strength index (rsi), and money flow index (mfi), among others, to generate buy and sell signals. The conditions for buy and sell signals are defined using logical operations and comparison operators. Overall, the CombinedBinHAndClucV7 strategy aims to identify favorable buying opportunities based on the specified conditions and generate corresponding sell signals when certain conditions are met.

startup_candle_count : 200
ema_50_1h: -0.001%
stoploss: -0.99
timeframe: 5m
hash(sha256): d16ea1c3384ef58832ac6202779f9608eb9f23385d23169e2c5bc2b10f71244a
indicators:
sma_200_1h upper ema_200 ema_50 close
sma_5 tail bb_lowerband mfi ema_200_1h
bbdelta volume smaHigh ATR ssl_up
closedelta sslDown open hlv volume_mean_slow
ema_50_1h smaLow sma_200 high sslUp
mid ssl_down_1h ssl_down rsi_1h lower
bb_middleband rsi bb_upperband ema_slow low
ssl_up_1h

Similar Strategies: (based on used indicators)

Strategy: 01_CombinedBinHAndClucV7_OPT, Similarity Score: 97.3%
Strategy: 01_CombinedBinHAndClucV7_OPT_02, Similarity Score: 97.3%
Strategy: 04_CombinedBinHAndClucV8, Similarity Score: 97.3%
Strategy: CombinedBinHAndClucV7_702, Similarity Score: 97.3%
Strategy: CombinedBinHAndClucV8Hyper, Similarity Score: 97.3%
Strategy: CombinedBinHAndClucV8XH, Similarity Score: 97.3%
Strategy: CombinedBinHAndClucV8XHO, Similarity Score: 97.3%
Strategy: Discord_1_TEST, Similarity Score: 97.3%
Strategy: Discord_1_test, Similarity Score: 97.3%
Strategy: CombinedBinHClucAndSMAOffset, Similarity Score: 94.59%
Strategy: CombinedBinHClucAndSMAOffset_2, Similarity Score: 94.59%
Strategy: 02_CombinedBinHClucAndMADV5, Similarity Score: 89.19%
Strategy: CombinedBinHClucAndMADV5, Similarity Score: 89.19%
Strategy: CombinedBinHClucAndMADV5_2, Similarity Score: 89.19%
Strategy: Discord_Bzed, Similarity Score: 89.19%
Strategy: 08_NostalgiaForInfinityV2_OPT, Similarity Score: 86.49%
Strategy: 08_NostalgiaForInfinityV2_OPT_02, Similarity Score: 86.49%
Strategy: CombinedBinHAndClucV6, Similarity Score: 86.49%
Strategy: CombinedBinHAndClucV6_2, Similarity Score: 86.49%
Strategy: NostalgiaForInfinityV1, Similarity Score: 86.49%
Strategy: NostalgiaForInfinityV2, Similarity Score: 86.49%
Strategy: HybridMonster, Similarity Score: 83.78%

last change: 2024-04-02 04:54:08