def get_intraday_vcs(**kwargs):
if 'report_date' in kwargs.keys():
report_date = kwargs['report_date']
else:
report_date = exp.doubledate_shift_bus_days()
atm_vol_ratio = kwargs['atm_vol_ratio']
vcs_output = vcs.generate_vcs_sheet_4date(date_to=report_date)
vcs_pairs = vcs_output['vcs_pairs']
if 'id' in kwargs.keys():
id = kwargs['id']
ticker1 = vcs_pairs['ticker1'].iloc[id]
ticker2 = vcs_pairs['ticker2'].iloc[id]
else:
ticker1 = kwargs['ticker1']
ticker2 = kwargs['ticker2']
ticker_head = cmi.get_contract_specs(ticker1)['ticker_head']
ticker_class = cmi.ticker_class[ticker_head]
vcs_output = ops.get_vcs_signals(ticker_list=[ticker1, ticker2],
settle_date=report_date,
atm_vol_ratio=atm_vol_ratio)
q = vcs_output['q']
q1 = vcs_output['q1']
filter_out = of.get_vcs_filters(data_frame_input=pd.DataFrame.from_dict({
'tickerHead': [ticker_head],
'tickerClass': [ticker_class],
'Q': [q],
'Q1': [q1]
}),
filter_list=['long2', 'short2'])
if filter_out['selected_frame'].empty:
validQ = False
else:
validQ = True
return {
'ticker1': ticker1,
'ticker2': ticker2,
'Q': q,
'Q1': q1,
'validQ': validQ
}
def generate_vcs_formatted_output(**kwargs):
if 'report_date' in kwargs.keys():
report_date = kwargs['report_date']
else:
report_date = exp.doubledate_shift_bus_days()
output_dir = ts.create_strategy_output_dir(strategy_class='vcs',
report_date=report_date)
vcs_output = vcs.generate_vcs_sheet_4date(date_to=report_date)
vcs_pairs = vcs_output['vcs_pairs']
filter_out = of.get_vcs_filters(data_frame_input=vcs_pairs,
filter_list=['long2', 'short2'])
good_vcs_pairs = filter_out['selected_frame']
vcs_pairs_w_selected_columns = vcs_pairs[[
'ticker1', 'ticker2', 'tickerHead', 'tickerClass', 'trDte1', 'trDte2',
'Q', 'Q1', 'fwdVolQ', 'downside', 'upside', 'atmVolRatio', 'fwdVol',
'realVolRatio', 'atmRealVolRatio', 'theta'
]]
good_vcs_pairs_w_selected_columns = good_vcs_pairs[[
'ticker1', 'ticker2', 'tickerHead', 'tickerClass', 'trDte1', 'trDte2',
'Q', 'Q1', 'fwdVolQ', 'downside', 'upside', 'atmVolRatio', 'fwdVol',
'realVolRatio', 'atmRealVolRatio', 'theta'
]]
writer = pd.ExcelWriter(output_dir + '/' + futil.xls_file_names['vcs'] +
'.xlsx',
engine='xlsxwriter')
vcs_pairs_w_selected_columns.to_excel(writer, sheet_name='all')
good_vcs_pairs_w_selected_columns.to_excel(writer, sheet_name='good')
worksheet_good = writer.sheets['good']
worksheet_all = writer.sheets['all']
worksheet_good.freeze_panes(1, 0)
worksheet_all.freeze_panes(1, 0)
worksheet_good.autofilter(0, 0,
len(good_vcs_pairs_w_selected_columns.index),
len(good_vcs_pairs_w_selected_columns.columns))
worksheet_all.autofilter(0, 0, len(vcs_pairs_w_selected_columns.index),
len(vcs_pairs_w_selected_columns.columns))
writer.save()
def generate_vcs_formatted_output(**kwargs):
if 'report_date' in kwargs.keys():
report_date = kwargs['report_date']
else:
report_date = exp.doubledate_shift_bus_days()
output_dir = ts.create_strategy_output_dir(strategy_class='vcs', report_date=report_date)
vcs_output = vcs.generate_vcs_sheet_4date(date_to=report_date)
vcs_pairs = vcs_output['vcs_pairs']
filter_out = of.get_vcs_filters(data_frame_input=vcs_pairs, filter_list=['long2', 'short2'])
good_vcs_pairs = filter_out['selected_frame']
vcs_pairs_w_selected_columns = vcs_pairs[['ticker1', 'ticker2', 'tickerHead', 'tickerClass', 'trDte1', 'trDte2', 'Q',
'Q1', 'fwdVolQ', 'downside', 'upside', 'atmVolRatio', 'fwdVol','realVolRatio',
'atmRealVolRatio','theta']]
good_vcs_pairs_w_selected_columns = good_vcs_pairs[['ticker1', 'ticker2', 'tickerHead', 'tickerClass', 'trDte1', 'trDte2', 'Q',
'Q1', 'fwdVolQ', 'downside', 'upside', 'atmVolRatio', 'fwdVol','realVolRatio',
'atmRealVolRatio','theta']]
writer = pd.ExcelWriter(output_dir + '/' + futil.xls_file_names['vcs'] + '.xlsx', engine='xlsxwriter')
vcs_pairs_w_selected_columns.to_excel(writer, sheet_name='all')
good_vcs_pairs_w_selected_columns.to_excel(writer, sheet_name='good')
worksheet_good = writer.sheets['good']
worksheet_all = writer.sheets['all']
worksheet_good.freeze_panes(1, 0)
worksheet_all.freeze_panes(1, 0)
worksheet_good.autofilter(0, 0, len(good_vcs_pairs_w_selected_columns.index),
len(good_vcs_pairs_w_selected_columns.columns))
worksheet_all.autofilter(0, 0, len(vcs_pairs_w_selected_columns.index),
len(vcs_pairs_w_selected_columns.columns))
def get_intraday_vcs(**kwargs):
if 'report_date' in kwargs.keys():
report_date = kwargs['report_date']
else:
report_date = exp.doubledate_shift_bus_days()
id = kwargs['id']
atm_vol_ratio = kwargs['atm_vol_ratio']
vcs_output = vcs.generate_vcs_sheet_4date(date_to=report_date)
vcs_pairs = vcs_output['vcs_pairs']
ticker1 = vcs_pairs['ticker1'].iloc[id]
ticker2 = vcs_pairs['ticker2'].iloc[id]
ticker_head = cmi.get_contract_specs(ticker1)['ticker_head']
ticker_class = cmi.ticker_class[ticker_head]
vcs_output = ops.get_vcs_signals(ticker_list=[ticker1, ticker2],settle_date=report_date,atm_vol_ratio=atm_vol_ratio)
q = vcs_output['q']
q1 = vcs_output['q1']
filter_out = of.get_vcs_filters(data_frame_input=pd.DataFrame.from_items([('tickerHead', [ticker_head]),
('tickerClass', [ticker_class]),
('Q', [q]), ('Q1', [q1])]), filter_list=['long2', 'short2'])
if filter_out['selected_frame'].empty:
validQ = False
else:
validQ = True
print(ticker1)
print(ticker2)
print('Q: ' + str(q))
print('Q1: ' + str(q1))
print('Valid?: ' + str(validQ))
def main():
app = algo.Algo()
report_date = exp.doubledate_shift_bus_days()
todays_date = cu.get_doubledate()
con = msu.get_my_sql_connection()
vcs_output = vcs.generate_vcs_sheet_4date(date_to=report_date)
vcs_pairs = vcs_output['vcs_pairs']
filter_out = of.get_vcs_filters(data_frame_input=vcs_pairs,
filter_list=['long2', 'short2'])
vcs_pairs = filter_out['selected_frame']
vcs_pairs = vcs_pairs[vcs_pairs['downside'].notnull()
& vcs_pairs['upside'].notnull()]
# &(vcs_pairs.tickerClass!='Energy')
vcs_pairs = vcs_pairs[(vcs_pairs['trDte1'] >= 50)
& (vcs_pairs.tickerClass != 'Metal') &
(vcs_pairs.tickerClass != 'FX') &
(vcs_pairs.tickerClass != 'Energy')]
vcs_pairs = vcs_pairs[((vcs_pairs['Q'] <= 30) &
(vcs_pairs['fwdVolQ'] >= 30)) |
((vcs_pairs['Q'] >= 70) &
(vcs_pairs['fwdVolQ'] <= 70))]
vcs_pairs.reset_index(drop=True, inplace=True)
vcs_pairs['underlying_ticker1'] = [
omu.get_option_underlying(ticker=x) for x in vcs_pairs['ticker1']
]
vcs_pairs['underlying_ticker2'] = [
omu.get_option_underlying(ticker=x) for x in vcs_pairs['ticker2']
]
vcs_pairs['underlying_tickerhead'] = [
cmi.get_contract_specs(x)['ticker_head']
for x in vcs_pairs['underlying_ticker1']
]
futures_data_dictionary = {
x: gfp.get_futures_price_preloaded(ticker_head=x)
for x in vcs_pairs['underlying_tickerhead'].unique()
}
proxy_output_list1 = [
up.get_underlying_proxy_ticker(
ticker=x,
settle_date=report_date,
futures_data_dictionary=futures_data_dictionary)
for x in vcs_pairs['underlying_ticker1']
]
vcs_pairs['proxy_ticker1'] = [x['ticker'] for x in proxy_output_list1]
vcs_pairs['add_2_proxy1'] = [x['add_2_proxy'] for x in proxy_output_list1]
proxy_output_list2 = [
up.get_underlying_proxy_ticker(
ticker=x,
settle_date=report_date,
futures_data_dictionary=futures_data_dictionary)
for x in vcs_pairs['underlying_ticker2']
]
vcs_pairs['proxy_ticker2'] = [x['ticker'] for x in proxy_output_list2]
vcs_pairs['add_2_proxy2'] = [x['add_2_proxy'] for x in proxy_output_list2]
vcs_pairs['expiration_date1'] = [
int(
exp.get_expiration_from_db(instrument='options', ticker=x,
con=con).strftime('%Y%m%d'))
for x in vcs_pairs['ticker1']
]
vcs_pairs['expiration_date2'] = [
int(
exp.get_expiration_from_db(instrument='options', ticker=x,
con=con).strftime('%Y%m%d'))
for x in vcs_pairs['ticker2']
]
vcs_pairs['interest_date1'] = [
grfs.get_simple_rate(as_of_date=report_date, date_to=x)['rate_output']
for x in vcs_pairs['expiration_date1']
]
vcs_pairs['interest_date2'] = [
grfs.get_simple_rate(as_of_date=report_date, date_to=x)['rate_output']
for x in vcs_pairs['expiration_date2']
]
vcs_pairs['exercise_type'] = [
cmi.get_option_exercise_type(ticker_head=x)
for x in vcs_pairs['tickerHead']
]
admin_dir = dna.get_directory_name(ext='admin')
risk_file_out = su.read_text_file(file_name=admin_dir +
'/RiskParameter.txt')
vcs_risk_parameter = 5 * 2 * float(risk_file_out[0])
vcs_pairs['long_quantity'] = vcs_risk_parameter / abs(
vcs_pairs['downside'])
vcs_pairs['short_quantity'] = vcs_risk_parameter / vcs_pairs['upside']
vcs_pairs['long_quantity'] = vcs_pairs['long_quantity'].round()
vcs_pairs['short_quantity'] = vcs_pairs['short_quantity'].round()
vcs_pairs['alias'] = [
generate_vcs_alias(vcs_row=vcs_pairs.iloc[x])
for x in range(len(vcs_pairs.index))
]
vcs_pairs['call_mid_price1'] = np.nan
vcs_pairs['put_mid_price1'] = np.nan
vcs_pairs['call_mid_price2'] = np.nan
vcs_pairs['put_mid_price2'] = np.nan
vcs_pairs['call_iv1'] = np.nan
vcs_pairs['put_iv1'] = np.nan
vcs_pairs['call_iv2'] = np.nan
vcs_pairs['put_iv2'] = np.nan
vcs_pairs['underlying_mid_price1'] = np.nan
vcs_pairs['underlying_mid_price2'] = np.nan
vcs_pairs['proxy_mid_price1'] = np.nan
vcs_pairs['proxy_mid_price2'] = np.nan
vcs_pairs['current_strike1'] = np.nan
vcs_pairs['current_strike2'] = np.nan
ta_folder = dn.get_dated_directory_extension(folder_date=todays_date,
ext='ta')
app.vcs_pairs = vcs_pairs
app.con = con
app.futures_data_dictionary = futures_data_dictionary
app.report_date = report_date
app.todays_date = todays_date
app.log = lg.get_logger(file_identifier='vcs', log_level='INFO')
app.trade_file = ta_folder + '/trade_dir.csv'
app.vcs_risk_parameter = vcs_risk_parameter
app.connect(client_id=3)
app.run()