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))
