def get_intraday_outright_covariance(**kwargs):
date_to = kwargs['date_to']
num_days_back_4intraday = 20
liquid_futures_frame = cl.get_liquid_outright_futures_frame(settle_date=date_to)
date_list = [exp.doubledate_shift_bus_days(double_date=date_to,shift_in_days=x) for x in reversed(range(1,num_days_back_4intraday))]
date_list.append(date_to)
intraday_data = opUtil.get_aligned_futures_data_intraday(contract_list=liquid_futures_frame['ticker'].values,date_list=date_list)
intraday_data['time_stamp'] = [x.to_datetime() for x in intraday_data.index]
intraday_data['hour_minute'] = [100*x.hour+x.minute for x in intraday_data['time_stamp']]
intraday_data = intraday_data.resample('30min',how='last')
intraday_data = intraday_data[(intraday_data['hour_minute'] >= 830) &
(intraday_data['hour_minute'] <= 1200)]
intraday_data_shifted = intraday_data.shift(1)
selection_indx = intraday_data['hour_minute']-intraday_data_shifted['hour_minute'] > 0
num_contracts = len(liquid_futures_frame.index)
diff_frame = pd.DataFrame()
for i in range(num_contracts):
mid_p = (intraday_data['c' + str(i+1)]['best_bid_p']+
intraday_data['c' + str(i+1)]['best_ask_p'])/2
mid_p_shifted = (intraday_data_shifted['c' + str(i+1)]['best_bid_p']+
intraday_data_shifted['c' + str(i+1)]['best_ask_p'])/2
diff_frame[liquid_futures_frame['ticker_head'].iloc[i]] = (mid_p-mid_p_shifted)*cmi.contract_multiplier[liquid_futures_frame['ticker_head'].iloc[i]]
diff_frame = diff_frame[selection_indx]
return {'cov_matrix': diff_frame.cov(),
'cov_data_integrity': 100*diff_frame.notnull().sum().sum()/(len(diff_frame.columns)*20*6)}
def get_intraday_outright_covariance(**kwargs):
date_to = kwargs['date_to']
num_days_back_4intraday = 20
liquid_futures_frame = cl.get_liquid_outright_futures_frame(
settle_date=date_to)
date_list = [
exp.doubledate_shift_bus_days(double_date=date_to, shift_in_days=x)
for x in reversed(range(1, num_days_back_4intraday))
]
date_list.append(date_to)
intraday_data = opUtil.get_aligned_futures_data_intraday(
contract_list=liquid_futures_frame['ticker'].values,
date_list=date_list)
if len(intraday_data.index) == 0:
return {'cov_matrix': pd.DataFrame(), 'cov_data_integrity': 0}
intraday_data['time_stamp'] = [
x.to_datetime() for x in intraday_data.index
]
intraday_data['hour_minute'] = [
100 * x.hour + x.minute for x in intraday_data['time_stamp']
]
intraday_data = intraday_data.resample('30min', how='last')
intraday_data = intraday_data[(intraday_data['hour_minute'] >= 830)
& (intraday_data['hour_minute'] <= 1200)]
intraday_data_shifted = intraday_data.shift(1)
selection_indx = intraday_data['hour_minute'] - intraday_data_shifted[
'hour_minute'] > 0
num_contracts = len(liquid_futures_frame.index)
diff_frame = pd.DataFrame()
for i in range(num_contracts):
mid_p = (intraday_data['c' + str(i + 1)]['best_bid_p'] +
intraday_data['c' + str(i + 1)]['best_ask_p']) / 2
mid_p_shifted = (
intraday_data_shifted['c' + str(i + 1)]['best_bid_p'] +
intraday_data_shifted['c' + str(i + 1)]['best_ask_p']) / 2
diff_frame[liquid_futures_frame['ticker_head'].iloc[i]] = (
mid_p - mid_p_shifted) * cmi.contract_multiplier[
liquid_futures_frame['ticker_head'].iloc[i]]
diff_frame = diff_frame[selection_indx]
return {
'cov_matrix':
diff_frame.cov(),
'cov_data_integrity':
100 * diff_frame.notnull().sum().sum() /
(len(diff_frame.columns) * 20 * 6)
}
def get_tickers_4date(**kwargs):
liquid_futures_frame = cl.get_liquid_outright_futures_frame(
settle_date=kwargs['date_to'])
liquid_futures_frame = liquid_futures_frame[
~liquid_futures_frame['ticker_head'].isin(['ED', 'TU'])]
liquid_futures_frame.reset_index(drop=True, inplace=True)
return liquid_futures_frame[['ticker', 'ticker_head']]
def get_tickers_4date(**kwargs):
liquid_futures_frame = cl.get_liquid_outright_futures_frame(settle_date=kwargs['date_to'])
liquid_futures_frame.reset_index(drop=True,inplace=True)
return liquid_futures_frame[['ticker', 'ticker_head']]
