The MoniGoManiHyperStrategyNew is a trading strategy that utilizes various technical analysis (TA) indicators to make buying decisions in backtesting. It calculates and adds several indicators to the input DataFrame, including ADX, PLUS_DI, MINUS_DI, RSI, MACD, SMA (Simple Moving Average), EMA (Exponential Moving Average), Bollinger Bands, and VWAP (Volume Weighted Average Price). In the populate_indicators method, the strategy calculates the values of these indicators based on the given DataFrame and adds them as new columns.
Additionally, it sets a 'trend' column in the DataFrame based on certain conditions.
In the populate_buy_trend method, the strategy populates the 'buy' column in the DataFrame based on the calculated indicators and the identified trend.
The 'buy' signal is weighted according to the respective trend and indicator values. The strategy updates the 'total_buy_signal_strength' column by adding the weighted buy signals from different indicators. Overall, the strategy aims to generate buy signals based on the combination of these TA indicators and the identified trend in order to backtest and evaluate its performance.
Additionally, it sets a 'trend' column in the DataFrame based on certain conditions.
In the populate_buy_trend method, the strategy populates the 'buy' column in the DataFrame based on the calculated indicators and the identified trend.
The 'buy' signal is weighted according to the respective trend and indicator values. The strategy updates the 'total_buy_signal_strength' column by adding the weighted buy signals from different indicators. Overall, the strategy aims to generate buy signals based on the combination of these TA indicators and the identified trend in order to backtest and evaluate its performance.
Traceback (most recent call last): File "/freqtrade/freqtrade/main.py", line 42, in main return_code = args['func'](args) ^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/commands/optimize_commands.py", line 58, in start_backtesting backtesting.start() File "/freqtrade/freqtrade/optimize/backtesting.py", line 1401, in start min_date, max_date = self.backtest_one_strategy(strat, data, timerange) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1318, in backtest_one_strategy preprocessed = self.strategy.advise_all_indicators(data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in advise_all_indicators return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, inreturn {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1410, in advise_indicators return self.populate_indicators(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/maninew.py", line 486, in populate_indicators dataframe['vwap'] = qtpylib.vwap(dataframe) ^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/vendor/qtpylib/indicators.py", line 333, in vwap raise ValueError("using `qtpylib.vwap` facilitates lookahead bias. Please use " ValueError: using `qtpylib.vwap` facilitates lookahead bias. Please use `qtpylib.rolling_vwap` instead, which calculates vwap in a rolling manner.
stoploss: -0.216 timeframe: 1h hash(sha256): 495385e3a2f7cfba88fc939fb3dca03dcc6fce92f7e1f5ce0a690bfbe51be37b indicators: adx_strong_up_weighted_buy_signal upper bollinger_bands_weighted_buy_signal total_buy_signal_strength close sma_long_death_cross_weighted_sell_signal bb_lowerband ema_long_death_cross_weighted_sell_signal date trend warning rsi_weighted_sell_signal trend open_trades trade trend_indicator debug sma_short_death_cross_weighted_sell_signal date sell___unclogger_enabled error sma9 plus_di ema_long_golden_cross_weighted_buy_signal ema9 lookback_candle vwap_cross_weighted_buy_signal macdsignal macd_wei
Similar Strategies: (based on used indicators)
Strategy: MX, Similarity Score: 90%
last change: 2024-04-29 19:11:49