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Strategy: NFI5MOHO
Downloaded: 20220115
Stoploss: -0.1
5mSpotv2UnbiasedLink


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Average Overall
BuysAvgprofTotProfWin%DD%Time
25.50.351.3177.53.9749.05
SharpeSortinoCalmar
1.321.0215.43
Prof.FactorExpectancyCagr
0.2700
Trades/DayRejected Signals
1.02254
Ninja Score: 66
The strategy, named NFI5MOHO, is implemented as a class that inherits from the IStrategy class. It consists of several methods that perform different tasks. The populate_indicators method takes a DataFrame and a metadata dictionary as input and returns an updated DataFrame.

It populates the indicators using the informative_1h_indicators and normal_tf_indicators methods.

The informative_1h_indicators method calculates indicators based on the 1-hour timeframe data, and the normal_tf_indicators method calculates indicators based on the normal timeframe data.

The indicators are merged into the original DataFrame using the merge_informative_pair function. The populate_buy_trend method takes a DataFrame and metadata dictionary as input and returns an updated DataFrame. It defines a list of conditions based on various indicators and criteria, such as the close price, MFI (Money Flow Index), EMA (Exponential Moving Average), EWO (Elder's Force Index), and volume. If any of the conditions are met, the corresponding rows in the DataFrame are marked as a "buy." The populate_sell_trend method takes a DataFrame and metadata dictionary as input and returns an updated DataFrame. It defines a list of conditions based on the close price and volume. However, the code for these conditions is commented out in the provided code snippet. The last part of the code snippet seems to be an additional function that calculates a technical indicator called SMADIF (Simple Moving Average Difference). It takes a DataFrame as input, creates two EMAs (Exponential Moving Averages) using different time periods, and calculates the difference between them. The result is normalized by dividing it by the close price and multiplying by 100. Overall, the NFI5MOHO strategy involves populating indicators based on different timeframes, determining buy signals based on various conditions, determining sell signals (although not implemented in the provided code snippet), and calculating the SMADIF technical indicator.

startup_candle_count : 300
ema_100_1h: -0.001%
ema_200_1h: -0.187%
ema_100: 0.003%
ema_200: -0.004%
ewo: -1.064%
stoploss: -0.1
timeframe: 5m
hash(sha256): 0d413291622df8061a833d3a6bf65fbfd28731b4c721fdbbcdf53de9acc61447
indicators:
upper ema_200 ema_50 safe_dips close
safe_pump_36 ema_15 tail sma_5 safe_pump_36_strict
chop bb_lowerband safe_pump_24_strict mfi safe_pump_48_strict
sma ema trima t3 kama
bbdelta ewo safe_pump_24 volume low_offset
i_offset_buy closedelta ema_20 high_offset open
safe_pump_36_loose safe_dips_loose safe_dips_strict volume_mean_30 sma_200
safe_pump_48_loose volume_mean_4 mid i_offset_sell safe_pump_48
safe_pump_24_loose rsi_1h ema_100 lower ema_12
sma_30 bb_middleband rsi sma_200_dec bb_upperband
e

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last change: 2024-04-01 19:40:41