The MoniGoManiHyperStrategy is a trading strategy implemented as a class that inherits from the IStrategy interface. It performs backtesting and generates buy signals based on various technical indicators. The populate_indicators method adds several technical analysis (TA) indicators to a given DataFrame.
These indicators include ADX (Average Directional Index), PLUS_DI (Plus Directional Indicator), MINUS_DI (Minus Directional Indicator), RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), SMA (Simple Moving Average), EMA (Exponential Moving Average), Bollinger Bands, and VWAP (Volume-Weighted Average Price).
The populate_buy_trend method populates the buy signals in the DataFrame based on the TA indicators and the current market trend.
It sets the 'trend' column in the DataFrame to indicate whether the market is trending upwards, downwards, or sideways. It then calculates the buy signal strength for each indicator and adds it to the 'total_buy_signal_strength' column. The buy signal strength is determined based on specific conditions for each indicator and the current trend. For example, if the market is in a downwards trend and the ADX indicator value is above a certain threshold, a weighted buy signal is assigned to the 'adx_strong_up_weighted_buy_signal' column. The same is done for other indicators like RSI, MACD, SMA, EMA, Bollinger Bands, and VWAP. Overall, the strategy combines multiple TA indicators and their respective buy signals to determine the overall buy signal strength, which can be used for further analysis or decision making in trading strategies.
These indicators include ADX (Average Directional Index), PLUS_DI (Plus Directional Indicator), MINUS_DI (Minus Directional Indicator), RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), SMA (Simple Moving Average), EMA (Exponential Moving Average), Bollinger Bands, and VWAP (Volume-Weighted Average Price).
The populate_buy_trend method populates the buy signals in the DataFrame based on the TA indicators and the current market trend.
It sets the 'trend' column in the DataFrame to indicate whether the market is trending upwards, downwards, or sideways. It then calculates the buy signal strength for each indicator and adds it to the 'total_buy_signal_strength' column. The buy signal strength is determined based on specific conditions for each indicator and the current trend. For example, if the market is in a downwards trend and the ADX indicator value is above a certain threshold, a weighted buy signal is assigned to the 'adx_strong_up_weighted_buy_signal' column. The same is done for other indicators like RSI, MACD, SMA, EMA, Bollinger Bands, and VWAP. Overall, the strategy combines multiple TA indicators and their respective buy signals to determine the overall buy signal strength, which can be used for further analysis or decision making in trading strategies.
stoploss: -0.027 timeframe: 1h hash(sha256): cdfc8aa379dca679861040d58291365cd4d909c5947428dbd638c7d824b161b1 indicators: adx_strong_up_weighted_buy_signal wtOversold upper bollinger_bands_weighted_buy_signal total_buy_signal_strength wtCrossUp wtVwap close sma_long_death_cross_weighted_sell_signal bb_lowerband ap crossed_above tci wt1 ema_long_death_cross_weighted_sell_signal crossed_below rsi_weighted_sell_signal trend esa wt2 sma_short_death_cross_weighted_sell_signal sma9 plus_di ema_long_golden_cross_weighted_buy_signal bearish_div ema9 vwap_cross_weighted_buy_signal high macdsignal macd_weighted_sell_signal c
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last change: 2024-04-28 08:57:08