def generate_ibo_sheet_4date(**kwargs):
date_to = kwargs['date_to']
output_dir = ts.create_strategy_output_dir(strategy_class='ibo', report_date=date_to)
#if os.path.isfile(output_dir + '/summary.pkl') and os.path.isfile(output_dir + '/cov.pkl'):
# sheet_4date = pd.read_pickle(output_dir + '/summary.pkl')
# cov_output = pckl.load(open(output_dir + '/cov.pkl', 'rb'))
# return {'sheet_4date': sheet_4date, 'cov_output': cov_output, 'success': True}
sheet_4date = get_tickers_4date(**kwargs)
num_tickers = len(sheet_4date.index)
sheet_4date = pd.concat([ifs.get_intraday_trend_signals(ticker=sheet_4date.iloc[x]['ticker'],date_to=date_to)['pnl_frame']
for x in range(num_tickers)])
sheet_4date.to_pickle(output_dir + '/summary.pkl')
cov_output = ifs.get_intraday_outright_covariance(**kwargs)
with open(output_dir + '/cov.pkl', 'wb') as handle:
pckl.dump(cov_output, handle)
return {'sheet_4date': sheet_4date, 'cov_output': cov_output, 'success': True}
def generate_candlestick_sheet_4date(**kwargs):
date_to = kwargs['date_to']
output_dir = ts.create_strategy_output_dir(strategy_class='candlestick',
report_date=date_to)
if os.path.isfile(output_dir + '/summary.pkl'):
sheet_4date = pd.read_pickle(output_dir + '/summary.pkl')
return {'sheet_4date': sheet_4date, 'success': True}
sheet_4date = get_tickers_4date(**kwargs)
num_tickers = len(sheet_4date.index)
signals_output = [
ifs.get_intraday_trend_signals(ticker=sheet_4date.iloc[x]['ticker'],
date_to=date_to)
for x in range(num_tickers)
]
sheet_4date['contract_noise'] = [
x['contract_noise'] for x in signals_output
]
sheet_4date['daily_noise'] = [x['daily_noise'] for x in signals_output]
sheet_4date['average_volume'] = [
x['average_volume'] for x in signals_output
]
sheet_4date['ewma10_50_spread'] = [
x['ewma10_50_spread'] for x in signals_output
]
sheet_4date['ewma20_100_spread'] = [
x['ewma20_100_spread'] for x in signals_output
]
sheet_4date['intraday_mean5'] = [
x['intraday_mean5'] for x in signals_output
]
sheet_4date['intraday_std5'] = [x['intraday_std5'] for x in signals_output]
sheet_4date['intraday_mean2'] = [
x['intraday_mean2'] for x in signals_output
]
sheet_4date['intraday_std2'] = [x['intraday_std2'] for x in signals_output]
sheet_4date['intraday_mean1'] = [
x['intraday_mean1'] for x in signals_output
]
sheet_4date['intraday_std1'] = [x['intraday_std1'] for x in signals_output]
sheet_4date.to_pickle(output_dir + '/summary.pkl')
cov_output = ifs.get_intraday_outright_covariance(**kwargs)
with open(output_dir + '/cov.pkl', 'wb') as handle:
pckl.dump(cov_output, handle)
return {
'sheet_4date': sheet_4date,
'cov_output': cov_output,
'success': True
}
def get_intraday_breakout_chart(**kwargs):
signal_out = ifs.get_intraday_trend_signals(ticker=kwargs['ticker'],date_to=kwargs['trade_date'])
intraday_data = signal_out['intraday_data']
trade_datetime = cu.convert_doubledate_2datetime(kwargs['trade_date'])
intraday_data = intraday_data[intraday_data['time_stamp']>=trade_datetime]
plt.figure(figsize=(16, 7))
plt.plot(intraday_data['time_stamp'],intraday_data['mid_p'],color='k')
plt.plot(intraday_data['time_stamp'],intraday_data['ewma25'],color='b')
plt.plot(intraday_data['time_stamp'],intraday_data['ewma100'],color='g')
plt.axvline(dt.datetime.combine(trade_datetime,dt.time(8,30,0,0)),color='r')
plt.axvline(dt.datetime.combine(trade_datetime,dt.time(9,0,0,0)),color='r')
#plt.axvline([x for x in intraday_data['time_stamp'] if 100*x.hour+x.minute == 830][0],color='r')
#plt.axvline([x for x in intraday_data.index if 100*x.hour+x.minute == 900][0],color='r')
plt.grid()
plt.show()