You will be redirected to the original Strategy in 15 seconds.
The SampleStrategy is a trading strategy implemented as a class that inherits from the IStrategy interface. It consists of three main methods: populate_indicators, populate_buy_trend, and populate_sell_trend. populate_indicators: This method adds various technical analysis (TA) indicators to the given DataFrame.
The indicators used include: ADX (Average Directional Index) RSI (Relative Strength Index) Stochastic Fast MACD (Moving Average Convergence Divergence) MFI (Money Flow Index) Bollinger Bands SAR (Stop and Reverse) TEMA (Triple Exponential Moving Average) HT_SINE (Hilbert Transform - SineWave) populate_buy_trend: This method populates the buy signal for the DataFrame based on the TA indicators and specific conditions.
The conditions for a buy signal include: RSI crossing above a predefined buy threshold (buy_rsi) TEMA (Triple Exponential Moving Average) being below the middle Bollinger Band (bb_middleband) TEMA trending upwards Volume not equal to zero populate_sell_trend: This method populates the sell signal for the DataFrame based on the TA indicators and specific conditions.
The conditions for a sell signal include: RSI crossing above a predefined sell threshold (sell_rsi) TEMA (Triple Exponential Moving Average) being above the middle Bollinger Band (bb_middleband) TEMA trending downwards Volume not equal to zero The populate_buy_trend and populate_sell_trend methods modify the DataFrame by adding a "buy" column and a "sell" column, respectively. These columns will have a value of 1 when the corresponding buy or sell condition is met, indicating a trading signal. Overall, the SampleStrategy class implements a backtesting strategy that generates buy and sell signals based on a combination of technical indicators and specific conditions.
The indicators used include: ADX (Average Directional Index) RSI (Relative Strength Index) Stochastic Fast MACD (Moving Average Convergence Divergence) MFI (Money Flow Index) Bollinger Bands SAR (Stop and Reverse) TEMA (Triple Exponential Moving Average) HT_SINE (Hilbert Transform - SineWave) populate_buy_trend: This method populates the buy signal for the DataFrame based on the TA indicators and specific conditions.
The conditions for a buy signal include: RSI crossing above a predefined buy threshold (buy_rsi) TEMA (Triple Exponential Moving Average) being below the middle Bollinger Band (bb_middleband) TEMA trending upwards Volume not equal to zero populate_sell_trend: This method populates the sell signal for the DataFrame based on the TA indicators and specific conditions.
The conditions for a sell signal include: RSI crossing above a predefined sell threshold (sell_rsi) TEMA (Triple Exponential Moving Average) being above the middle Bollinger Band (bb_middleband) TEMA trending downwards Volume not equal to zero The populate_buy_trend and populate_sell_trend methods modify the DataFrame by adding a "buy" column and a "sell" column, respectively. These columns will have a value of 1 when the corresponding buy or sell condition is met, indicating a trading signal. Overall, the SampleStrategy class implements a backtesting strategy that generates buy and sell signals based on a combination of technical indicators and specific conditions.
stoploss: -0.1 timeframe: 5m hash(sha256): c3871e8d0ee607d5285d7b39e7dcf6a335a2ec5dcefdff05ac28c98955fd3f2d indicators: upper htsine tema asks close mfi bb_lowerband bb_percent macdhist fastk htleadsine leadsine volume fastd best_ask sar bids macdsignal mid bb_width macd best_bid adx lower bb_middleband rsi bb_upperband sine
Similar Strategies: (based on used indicators)
Strategy: AlligatorV4, Similarity Score: 96.55%
Strategy: FRAYSTRAT, Similarity Score: 96.55%
Strategy: Machete, Similarity Score: 96.55%
Strategy: MeoMeo99, Similarity Score: 96.55%
Strategy: MrFutu, Similarity Score: 96.55%
Strategy: STRATEGY_DEFAULT, Similarity Score: 96.55%
Strategy: Sar, Similarity Score: 96.55%
Strategy: SmithHoeckx, Similarity Score: 96.55%
Strategy: TEMA, Similarity Score: 96.55%
Strategy: TrainDeepQStrategy, Similarity Score: 96.55%
Strategy: bonafe, Similarity Score: 96.55%
Strategy: default, Similarity Score: 96.55%
Strategy: matteo1905, Similarity Score: 96.55%
Strategy: sample_strategy_151, Similarity Score: 96.55%
Strategy: sample_strategy_168, Similarity Score: 96.55%
Strategy: sample_strategy_170, Similarity Score: 96.55%
Strategy: sample_strategy_182, Similarity Score: 96.55%
Strategy: sample_strategy_193, Similarity Score: 96.55%
Strategy: sample_strategy_2, Similarity Score: 96.55%
Strategy: sample_strategy_20, Similarity Score: 96.55%
Strategy: sample_strategy_215, Similarity Score: 96.55%
Strategy: sample_strategy_47, Similarity Score: 96.55%
Strategy: sample_strategy_56, Similarity Score: 96.55%
Strategy: sample_strategy_701, Similarity Score: 96.55%
Strategy: winner, Similarity Score: 96.55%
Strategy: winner2, Similarity Score: 96.55%
Strategy: sample_strategy_643, Similarity Score: 93.1%
Strategy: firesoul, Similarity Score: 89.66%
Strategy: sample_strategy_34, Similarity Score: 86.21%
Strategy: sample_strategy_487, Similarity Score: 86.21%
last change: 2023-08-09 01:38:50