def slinger(ax, datafile, ticker, put_parameters, call_parameters): time = datafile[ticker]['datetime'][...] data_open = datafile[ticker]['open'][...] data_high = datafile[ticker]['high'][...] data_low = datafile[ticker]['low'][...] data_volume = datafile[ticker]['volume'][...] datafile.close() tradeable = Analytics.market_hours(t=time) print(np.sum(tradeable)) candle = Analytics.candle_avg(open=data_open, high=data_high, low=data_low) candle_low_bollinger, candle_high_bollinger = Analytics.candle_bollinger_bands( open=data_open, high=data_high, low=data_low, average=candle, period=30) period = 30 sma = Analytics.moving_average(data=candle, period=period) sma_short = Analytics.exp_moving_average(data=candle, alpha=.1, period=period // 3) sma_low_bollinger, sma_high_bollinger = Analytics.bollinger_bands( data=sma_short, average=sma) sma_d = Analytics.derivative(sma, period=period // 6) # sma_d = Analytics.moving_average(sma_d, period=period // 6) sma_dd = Analytics.second_derivative(sma, period=period) results_list = SMA_chaser.put_chaser_strat( time=time, sma=sma, bollinger_up=sma_high_bollinger, bollinger_down=sma_low_bollinger, sma_d=sma_d, candle=candle, candle_high=candle_high_bollinger, candle_low=candle_low_bollinger, parameters=put_parameters) put_buy_locs = results_list[0] put_buy_price = results_list[1] # print(put_buy_price) put_buy_option_price = results_list[2] print(put_buy_option_price) put_sell_locs = results_list[3] put_sell_price = results_list[4] # print(put_sell_price) put_sell_option_price = results_list[5] print(put_sell_option_price) put_profits = (put_sell_option_price - put_buy_option_price) put_percent = (put_sell_option_price - put_buy_option_price) / put_buy_option_price print(put_percent) put_percent_avg = np.sum(put_percent) / put_percent.shape[0] print(put_percent_avg) # return_list.append(put_percent) # return_list.append(put_percent_avg) focus_top = time.shape[0] - 60 * 48 focus_bot = time.shape[0] + 1 focus_top = 0 focus_bot = time.shape[0] + 1 candle_rescaled = candle - np.sum(candle) / sma.shape[0] candle_rescaled = candle_rescaled / np.abs(candle_rescaled).max() sma_rescaled = sma - np.sum(sma) / sma.shape[0] sma_rescaled = sma_rescaled / np.abs(sma_rescaled).max() Bollinger_oscillator = 2 * ( sma_short - sma) / np.absolute(sma_high_bollinger - sma_low_bollinger) ''' ax[0].plot(time[focus_top:focus_bot], candle_rescaled, label='candle') ax[0].plot(time[focus_top:focus_bot], sma_rescaled, label='sma') ax[0].plot(time[focus_top:focus_bot], sma_d[focus_top:focus_bot] / np.abs(sma_d).max(), label='sma_d') ax[0].plot(time[focus_top:focus_bot], sma_dd[focus_top:focus_bot] / np.abs(sma_dd).max(), label='sma_dd') ax[0].legend() ''' ################################################################################# # plt.figure(figsize=(20, 10)) # plt.suptitle('profitable trades') # ax[0].plot(time[tradeable], data_volume[tradeable], '.') ax_twin = ax[0].twinx() ax_twin.plot(time[tradeable], sma_d[tradeable]) ax[0].plot(time[tradeable], candle[tradeable], '.', label=str(put_percent_avg)) ax[0].plot(time[tradeable], sma[tradeable]) ax[0].plot(time[tradeable], sma_low_bollinger[tradeable]) ax[0].plot(time[tradeable], sma_high_bollinger[tradeable]) ax[0].plot(time[tradeable], candle_low_bollinger[tradeable]) ax[0].plot(time[tradeable], candle_high_bollinger[tradeable]) profit_put_buy_locs = put_buy_locs[put_profits >= 0] put_cut = profit_put_buy_locs[profit_put_buy_locs > focus_top] ax[0].plot(time[put_cut], candle[put_cut], '>', color='r') profit_put_sell_locs = put_sell_locs[put_profits >= 0] put_cut = profit_put_sell_locs[profit_put_sell_locs > focus_top] ax[0].plot(time[put_cut], candle[put_cut], '<', color='g') ax[0].legend() ################################################################################# # plt.figure(figsize=(20, 10)) # plt.suptitle('loss trades') # ax[1].plot(time, data_volume, '.') ax[1].plot(time[tradeable], candle[tradeable], '.', label=str(put_percent_avg)) ax[1].plot(time[tradeable], sma[tradeable]) ax[1].plot(time[tradeable], sma_low_bollinger[tradeable]) ax[1].plot(time[tradeable], sma_high_bollinger[tradeable]) ax[1].plot(time[tradeable], candle_low_bollinger[tradeable]) ax[1].plot(time[tradeable], candle_high_bollinger[tradeable]) loss_put_buy_locs = put_buy_locs[put_profits < 0] put_cut = loss_put_buy_locs[loss_put_buy_locs > focus_top] ax[1].plot(time[put_cut], candle[put_cut], '>', color='r') loss_put_sell_locs = put_sell_locs[put_profits < 0] put_cut = loss_put_sell_locs[loss_put_sell_locs > focus_top] ax[1].plot(time[put_cut], candle[put_cut], '<', color='g') ax[1].legend() results_list = SMA_chaser.call_chaser_strat( time=time, sma=sma, bollinger_up=sma_high_bollinger, bollinger_down=sma_low_bollinger, sma_d=sma_d, candle=candle, candle_high=candle_high_bollinger, candle_low=candle_low_bollinger, parameters=call_parameters) call_buy_option_price = results_list[2] print(put_buy_option_price) call_sell_option_price = results_list[5] print(put_sell_option_price) call_percent = (call_sell_option_price - call_buy_option_price) / call_buy_option_price print(call_percent) call_percent_avg = np.sum(call_percent) / call_percent.shape[0] print(call_percent_avg) percent_profits = np.concatenate((put_percent, call_percent)) print(percent_profits) average_profit = np.sum(percent_profits) / percent_profits.shape[0] print(average_profit) return call_percent_avg
group_choice = np.random.choice(list(datafile.keys())) time = datafile[group_choice]['datetime'][...] data_open = datafile[group_choice]['open'][...] data_high = datafile[group_choice]['high'][...] data_low = datafile[group_choice]['low'][...] data = Analytics.candle_avg(open=data_open, high=data_high, low=data_low) candle_low_bollinger, candle_high_bollinger = Analytics.candle_bollinger_bands( open=data_open, high=data_high, low=data_low, average=data, period=30) sma = Analytics.moving_average(data=data, period=20) sma_low_bollinger, sma_high_bollinger = Analytics.bollinger_bands(data=data, average=sma) ema = Analytics.exp_moving_average(data=data, alpha=.1, period=30) ema_low_bollinger, ema_high_bollinger = Analytics.bollinger_bands(data=data, average=ema) focus_top = 3000 focus_bot = 35000 plt.figure(figsize=(20, 10)) plt.suptitle(group_choice + ' ' + 'open sma') plt.plot(data[focus_top:focus_bot]) plt.plot(sma[focus_top:focus_bot]) plt.plot(sma_low_bollinger[focus_top:focus_bot]) plt.plot(sma_high_bollinger[focus_top:focus_bot]) plt.plot(candle_low_bollinger[focus_top:focus_bot]) plt.plot(candle_high_bollinger[focus_top:focus_bot]) plt.figure(figsize=(20, 10))