We want our decision-making algorithm to recalculate trading signals on every price or order update. Let's create a generate_signals_and_think() method inside the MeanReversionTrader class to do this:
def generate_signals_and_think(self): df_resampled = self.df_prices\ .resample(self.resample_interval)\ .ffill()\ .dropna() resampled_len = len(df_resampled.index) if resampled_len < self.mean_periods: print( 'Insufficient data size to calculate logic. Need', self.mean_periods - resampled_len, 'more.' ) return mean = df_resampled.tail(self.mean_periods).mean()[self.symbol] # Signal flag calculation is_signal_buy = mean > self.ask_price is_signal_sell = mean < self.bid_price print( 'is_signal_buy:', ...
