The BinHV27 strategy is a trading strategy implemented in Python using the Freqtrade framework. Here is a short description of what the strategy does:
The strategy is designed to generate buy and sell signals based on various indicators and conditions. It uses the talib library for technical analysis calculations and the qtpylib library for additional indicators.
Key indicators used in this strategy: RSI (Relative Strength Index) EMA (Exponential Moving Average) ADX (Average Directional Index) MINUS_DI (Minus Directional Indicator) PLUS_DI (Plus Directional Indicator) SMA (Simple Moving Average) The populate_indicators function is responsible for calculating and populating these indicators on the input dataframe containing OHLCV (Open, High, Low, Close, Volume) data.
The populate_buy_trend function generates buy signals based on a combination of conditions involving the indicators mentioned above.
The conditions include checks for the relationship between moving averages, RSI values, ADX values, and trend directions. The populate_sell_trend function generates sell signals based on specific conditions, such as price crossing moving averages, RSI values, ADX values, and trend confirmation. The strategy also defines a minimal_roi (minimum return on investment) and a stoploss value, which determine the profit targets and stop-loss levels for trades executed based on the strategy. The ticker_interval and timeframe variables specify the timeframe for the trading data used by the strategy. Overall, the BinHV27 strategy aims to identify potential buying and selling opportunities based on the analyzed indicators and conditions.
Key indicators used in this strategy: RSI (Relative Strength Index) EMA (Exponential Moving Average) ADX (Average Directional Index) MINUS_DI (Minus Directional Indicator) PLUS_DI (Plus Directional Indicator) SMA (Simple Moving Average) The populate_indicators function is responsible for calculating and populating these indicators on the input dataframe containing OHLCV (Open, High, Low, Close, Volume) data.
The populate_buy_trend function generates buy signals based on a combination of conditions involving the indicators mentioned above.
The conditions include checks for the relationship between moving averages, RSI values, ADX values, and trend directions. The populate_sell_trend function generates sell signals based on specific conditions, such as price crossing moving averages, RSI values, ADX values, and trend confirmation. The strategy also defines a minimal_roi (minimum return on investment) and a stoploss value, which determine the profit targets and stop-loss levels for trades executed based on the strategy. The ticker_interval and timeframe variables specify the timeframe for the trading data used by the strategy. Overall, the BinHV27 strategy aims to identify potential buying and selling opportunities based on the analyzed indicators and conditions.
stoploss: -0.05 timeframe: 5T hash(sha256): 2f733d62d6c390bc2a85dd7171bb54279c209cae25bdabcfbe85583894c4d935 indicators: preparechangetrend close lowsma delta trend minusdi slowingdown continueup slowsma highsma bigdown emarsi bigup minusdiema adx plusdi fastsma preparechangetrendconfirm rsi plusdiema
Similar Strategies: (based on used indicators)
Strategy: BHV27v2, Similarity Score: 95.24%
Strategy: BinHV27, Similarity Score: 95.24%
Strategy: BinHV27F, Similarity Score: 95.24%
Strategy: BinHV27V1, Similarity Score: 95.24%
Strategy: BinHV27_1, Similarity Score: 95.24%
Strategy: BinHV27_104, Similarity Score: 95.24%
Strategy: BinHV27_2, Similarity Score: 95.24%
Strategy: BinHV27_214, Similarity Score: 95.24%
Strategy: BinHV27_253, Similarity Score: 95.24%
Strategy: BinHV27_254, Similarity Score: 95.24%
Strategy: BinHV27_3, Similarity Score: 95.24%
Strategy: BinHV27_31, Similarity Score: 95.24%
Strategy: BinHV27_387, Similarity Score: 95.24%
Strategy: BinHV27_4, Similarity Score: 95.24%
Strategy: BinHV27_5, Similarity Score: 95.24%
Strategy: BinHV27_747, Similarity Score: 95.24%
Strategy: BinHV27_823, Similarity Score: 95.24%
Strategy: BinHV27_long, Similarity Score: 95.24%
Strategy: BinHV27_short, Similarity Score: 95.24%
Strategy: BinHV27_short_2, Similarity Score: 95.24%
Strategy: BinHV27_short_3, Similarity Score: 95.24%
Strategy: BinHV27_short_4, Similarity Score: 95.24%
Strategy: CombinedAMD1, Similarity Score: 95.24%
Strategy: CombinedAMD2, Similarity Score: 95.24%
Strategy: Discord_BinHV27_combined, Similarity Score: 95.24%
Strategy: Discord_BinHV27_combined_test, Similarity Score: 95.24%
Strategy: FBHV27, Similarity Score: 95.24%
Strategy: SHV27, Similarity Score: 95.24%
Strategy: SuperHV27, Similarity Score: 95.24%
Strategy: jazz, Similarity Score: 95.24%
Strategy: jazz_2, Similarity Score: 95.24%
Strategy: BinHV27_short_10, Similarity Score: 90.48%
Strategy: BinHV27_short_5, Similarity Score: 90.48%
Strategy: BinHV27_short_6, Similarity Score: 90.48%
Strategy: BinHV27_short_7, Similarity Score: 90.48%
Strategy: BinHV27_short_8, Similarity Score: 90.48%
Strategy: BinHV27_short_9, Similarity Score: 90.48%
Strategy: Frieza, Similarity Score: 90.48%
Strategy: SFrieza, Similarity Score: 90.48%
Strategy: SMAIP3_combine, Similarity Score: 90.48%
last change: 2024-04-29 20:54:07