def generate_spread_carry_followup_report(**kwargs):
if 'as_of_date' in kwargs.keys():
as_of_date = kwargs['as_of_date']
else:
as_of_date = exp.doubledate_shift_bus_days()
kwargs['as_of_date'] = as_of_date
con = msu.get_my_sql_connection(**kwargs)
ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date,
ext='ta')
if 'writer' in kwargs.keys():
writer = kwargs['writer']
else:
writer = pd.ExcelWriter(ta_output_dir + '/followup.xlsx',
engine='xlsxwriter')
strategy_frame = ts.get_open_strategies(**kwargs)
strategy_class_list = [
sc.convert_from_string_to_dictionary(
string_input=strategy_frame['description_string'][x])
['strategy_class'] for x in range(len(strategy_frame.index))
]
spread_carry_indx = [x == 'spread_carry' for x in strategy_class_list]
spread_carry_frame = strategy_frame[spread_carry_indx]
if spread_carry_frame.empty:
return writer
results = [
sf.get_results_4strategy(
alias=spread_carry_frame['alias'].iloc[x],
strategy_info_output=spread_carry_frame.iloc[x],
con=con) for x in range(len(spread_carry_frame.index))
]
results_frame_list = [
results[x]['results_frame'] for x in range(len(results))
if results[x]['success']
]
spread_carry_followup_frame = pd.concat(results_frame_list)
spread_carry_followup_frame.to_excel(writer, sheet_name='sc')
worksheet_sc = writer.sheets['sc']
worksheet_sc.freeze_panes(1, 0)
worksheet_sc.autofilter(0, 0, len(spread_carry_followup_frame.index),
len(spread_carry_followup_frame.columns))
if 'con' not in kwargs.keys():
con.close()
return writer
def generate_spread_carry_followup_report(**kwargs):
if 'as_of_date' in kwargs.keys():
as_of_date = kwargs['as_of_date']
else:
as_of_date = exp.doubledate_shift_bus_days()
kwargs['as_of_date'] = as_of_date
con = msu.get_my_sql_connection(**kwargs)
ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date, ext='ta')
if 'writer' in kwargs.keys():
writer = kwargs['writer']
else:
writer = pd.ExcelWriter(ta_output_dir + '/followup.xlsx', engine='xlsxwriter')
strategy_frame = ts.get_open_strategies(**kwargs)
strategy_class_list = [sc.convert_from_string_to_dictionary(string_input=strategy_frame['description_string'][x])['strategy_class']
for x in range(len(strategy_frame.index))]
spread_carry_indx = [x == 'spread_carry' for x in strategy_class_list]
spread_carry_frame = strategy_frame[spread_carry_indx]
results = [sf.get_results_4strategy(alias=spread_carry_frame['alias'].iloc[x],
strategy_info_output=spread_carry_frame.iloc[x],
con=con)
for x in range(len(spread_carry_frame.index))]
results_frame_list = [results[x]['results_frame'] for x in range(len(results)) if results[x]['success']]
spread_carry_followup_frame = pd.concat(results_frame_list)
spread_carry_followup_frame.to_excel(writer, sheet_name='sc')
worksheet_sc = writer.sheets['sc']
worksheet_sc.freeze_panes(1, 0)
worksheet_sc.autofilter(0, 0, len(spread_carry_followup_frame.index),
len(spread_carry_followup_frame.columns))
if 'con' not in kwargs.keys():
con.close()
return writer
def generate_futures_butterfly_followup_report(**kwargs):
con = msu.get_my_sql_connection(**kwargs)
if 'as_of_date' in kwargs.keys():
as_of_date = kwargs['as_of_date']
else:
as_of_date = exp.doubledate_shift_bus_days()
kwargs['as_of_date'] = as_of_date
if 'writer' in kwargs.keys():
writer = kwargs['writer']
else:
ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date, ext='ta')
writer = pd.ExcelWriter(ta_output_dir + '/followup.xlsx', engine='xlsxwriter')
strategy_frame = ts.get_open_strategies(**kwargs)
strategy_class_list = [sc.convert_from_string_to_dictionary(string_input=strategy_frame['description_string'][x])['strategy_class']
for x in range(len(strategy_frame.index))]
futures_butterfly_indx = [x == 'futures_butterfly' for x in strategy_class_list]
futures_butterfly_frame = strategy_frame[futures_butterfly_indx]
results = [sf.get_results_4strategy(alias=futures_butterfly_frame['alias'].iloc[x],
strategy_info_output=futures_butterfly_frame.iloc[x])
for x in range(len(futures_butterfly_frame.index))]
butterfly_followup_frame = pd.DataFrame(results)
butterfly_followup_frame['alias'] = futures_butterfly_frame['alias'].values
pnl_frame = pm.get_daily_pnl_snapshot(as_of_date=as_of_date, con=con)
risk_output = hr.get_historical_risk_4open_strategies(as_of_date=as_of_date, con=con)
merged_frame1 = pd.merge(butterfly_followup_frame,pnl_frame, how='left', on='alias')
merged_frame2 = pd.merge(merged_frame1, risk_output['strategy_risk_frame'], how='left', on='alias')
butterfly_followup_frame = merged_frame2[['alias', 'ticker_head', 'holding_tr_dte', 'short_tr_dte',
'z1_initial', 'z1', 'QF_initial', 'QF',
'total_pnl', 'downside','recommendation']]
butterfly_followup_frame.rename(columns={'alias': 'Alias', 'ticker_head': 'TickerHead',
'holding_tr_dte': 'HoldingTrDte', 'short_tr_dte': 'ShortTrDte',
'z1_initial': 'Z1Initial', 'z1': 'Z1',
'QF_initial': 'QFInitial','total_pnl': 'TotalPnl',
'downside': 'Downside','recommendation':'Recommendation'}, inplace=True)
butterfly_followup_frame.sort('QF', ascending=False,inplace=True)
butterfly_followup_frame['Z1'] = butterfly_followup_frame['Z1'].round(2)
butterfly_followup_frame.to_excel(writer, sheet_name='butterflies')
worksheet_butterflies = writer.sheets['butterflies']
worksheet_butterflies.set_column('B:B', 26)
worksheet_butterflies.freeze_panes(1, 0)
worksheet_butterflies.autofilter(0, 0, len(butterfly_followup_frame.index),
len(butterfly_followup_frame.columns))
if 'con' not in kwargs.keys():
con.close()
return writer
def generate_vcs_followup_report(**kwargs):
if 'as_of_date' in kwargs.keys():
as_of_date = kwargs['as_of_date']
else:
as_of_date = exp.doubledate_shift_bus_days()
kwargs['as_of_date'] = as_of_date
ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date, ext='ta')
con = msu.get_my_sql_connection(**kwargs)
if 'writer' in kwargs.keys():
writer = kwargs['writer']
else:
writer = pd.ExcelWriter(ta_output_dir + '/followup.xlsx', engine='xlsxwriter')
strategy_frame = ts.get_open_strategies(**kwargs)
strategy_class_list = [sc.convert_from_string_to_dictionary(string_input=strategy_frame['description_string'][x])['strategy_class']
for x in range(len(strategy_frame.index))]
vcs_indx = [x == 'vcs' for x in strategy_class_list]
vcs_frame = strategy_frame[vcs_indx]
results = [sf.get_results_4strategy(alias=vcs_frame['alias'].iloc[x],
strategy_info_output=vcs_frame.iloc[x])
for x in range(len(vcs_frame.index))]
vcs_followup_frame = pd.DataFrame(results)
vcs_followup_frame['alias'] = vcs_frame['alias'].values
pnl_frame = pm.get_daily_pnl_snapshot(**kwargs)
merged_frame1 = pd.merge(vcs_followup_frame,pnl_frame, how='left', on='alias')
vcs_followup_frame = merged_frame1[['alias', 'last_adjustment_days_ago','min_tr_dte', 'long_short_ratio',
'net_oev', 'net_theta', 'long_oev', 'short_oev', 'favQMove', 'total_pnl','recommendation']]
vcs_followup_frame['long_short_ratio'] = vcs_followup_frame['long_short_ratio'].round()
vcs_followup_frame['net_oev'] = vcs_followup_frame['net_oev'].round(1)
vcs_followup_frame['long_oev'] = vcs_followup_frame['long_oev'].round(1)
vcs_followup_frame['short_oev'] = vcs_followup_frame['short_oev'].round(1)
vcs_followup_frame['net_theta'] = vcs_followup_frame['net_theta'].round(1)
vcs_followup_frame.sort('total_pnl', ascending=False, inplace=True)
vcs_followup_frame.reset_index(drop=True,inplace=True)
vcs_followup_frame.loc[len(vcs_followup_frame.index)] = ['TOTAL', None, None, None, None, vcs_followup_frame['net_theta'].sum(),
None, None, None, vcs_followup_frame['total_pnl'].sum(), None]
vcs_followup_frame.to_excel(writer, sheet_name='vcs')
worksheet_vcs = writer.sheets['vcs']
worksheet_vcs.set_column('B:B', 18)
worksheet_vcs.freeze_panes(1, 0)
worksheet_vcs.autofilter(0, 0, len(vcs_followup_frame.index),
len(vcs_followup_frame.columns))
if 'con' not in kwargs.keys():
con.close()
writer.save()
def generate_ocs_followup_report(**kwargs):
if 'as_of_date' in kwargs.keys():
as_of_date = kwargs['as_of_date']
else:
as_of_date = exp.doubledate_shift_bus_days()
kwargs['as_of_date'] = as_of_date
broker = kwargs['broker']
ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date,
ext='ta')
con = msu.get_my_sql_connection(**kwargs)
if 'writer' in kwargs.keys():
writer = kwargs['writer']
else:
writer = pd.ExcelWriter(ta_output_dir + '/followup.xlsx',
engine='xlsxwriter')
strategy_frame = ts.get_open_strategies(**kwargs)
strategy_class_list = [
sc.convert_from_string_to_dictionary(
string_input=strategy_frame['description_string'][x])
['strategy_class'] for x in range(len(strategy_frame.index))
]
ocs_indx = [x == 'ocs' for x in strategy_class_list]
ocs_frame = strategy_frame[ocs_indx]
if ocs_frame.empty:
writer.save()
return
results = [
sf.get_results_4strategy(alias=ocs_frame['alias'].iloc[x],
strategy_info_output=ocs_frame.iloc[x],
con=con,
broker=broker,
date_to=as_of_date)
for x in range(len(ocs_frame.index))
]
ocs_followup_frame = pd.DataFrame(results)
ocs_followup_frame['alias'] = ocs_frame['alias'].values
kwargs['name'] = 'final'
pnl_frame = pm.get_daily_pnl_snapshot(**kwargs)
merged_frame1 = pd.merge(ocs_followup_frame,
pnl_frame,
how='left',
on='alias')
ocs_followup_frame = merged_frame1[[
'alias', 'dollar_noise', 'time_held', 'daily_pnl', 'total_pnl', 'notes'
]]
ocs_followup_frame.reset_index(drop=True, inplace=True)
ocs_followup_frame.loc[max(ocs_followup_frame.index) + 1] = [
'TOTAL', np.nan, np.nan, ocs_followup_frame['daily_pnl'].sum(),
ocs_followup_frame['total_pnl'].sum(), ''
]
date_from30 = cu.doubledate_shift(as_of_date, 30)
history_frame = ts.select_strategies(close_date_from=date_from30,
close_date_to=as_of_date,
con=con)
strategy_class_list = [
sc.convert_from_string_to_dictionary(
string_input=history_frame['description_string'][x])
['strategy_class'] for x in range(len(history_frame.index))
]
ocs_indx = [x == 'ocs' for x in strategy_class_list]
ocs_history_frame = history_frame[ocs_indx]
pnl_past_month = ocs_history_frame['pnl'].sum()
as_of_datetime = cu.convert_doubledate_2datetime(as_of_date)
date_from7 = as_of_datetime + dt.timedelta(days=-7)
ocs_short_history_frame = ocs_history_frame[
ocs_history_frame['close_date'] >= date_from7]
pnl_past_week = ocs_short_history_frame['pnl'].sum()
ocs_followup_frame.loc[max(ocs_followup_frame.index) + 1] = [
'WEEKLY PERFORMANCE', np.nan, np.nan, np.nan, pnl_past_week, ''
]
ocs_followup_frame.loc[max(ocs_followup_frame.index) + 1] = [
'MONTHLY PERFORMANCE', np.nan, np.nan, np.nan, pnl_past_month, ''
]
ocs_followup_frame['total_pnl'] = ocs_followup_frame['total_pnl'].astype(
int)
ocs_followup_frame.to_excel(writer, sheet_name='ocs')
worksheet_ocs = writer.sheets['ocs']
worksheet_ocs.freeze_panes(1, 0)
worksheet_ocs.set_column('B:B', 26)
worksheet_ocs.autofilter(0, 0, len(ocs_followup_frame.index),
len(ocs_followup_frame.columns))
if 'con' not in kwargs.keys():
con.close()
writer.save()
def generate_vcs_followup_report(**kwargs):
if 'as_of_date' in kwargs.keys():
as_of_date = kwargs['as_of_date']
else:
as_of_date = exp.doubledate_shift_bus_days()
kwargs['as_of_date'] = as_of_date
ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date,
ext='ta')
con = msu.get_my_sql_connection(**kwargs)
if 'writer' in kwargs.keys():
writer = kwargs['writer']
else:
writer = pd.ExcelWriter(ta_output_dir + '/followup.xlsx',
engine='xlsxwriter')
strategy_frame = ts.get_open_strategies(**kwargs)
strategy_class_list = [
sc.convert_from_string_to_dictionary(
string_input=strategy_frame['description_string'][x])
['strategy_class'] for x in range(len(strategy_frame.index))
]
vcs_indx = [x == 'vcs' for x in strategy_class_list]
vcs_frame = strategy_frame[vcs_indx]
if len(vcs_frame.index) == 0:
return writer
results = [
sf.get_results_4strategy(alias=vcs_frame['alias'].iloc[x],
strategy_info_output=vcs_frame.iloc[x])
for x in range(len(vcs_frame.index))
]
vcs_followup_frame = pd.DataFrame(results)
vcs_followup_frame['alias'] = vcs_frame['alias'].values
kwargs['name'] = 'final'
pnl_frame = pm.get_daily_pnl_snapshot(**kwargs)
merged_frame1 = pd.merge(vcs_followup_frame,
pnl_frame,
how='left',
on='alias')
vcs_followup_frame = merged_frame1[[
'alias', 'last_adjustment_days_ago', 'min_tr_dte', 'long_short_ratio',
'net_oev', 'net_theta', 'long_oev', 'short_oev', 'favQMove',
'total_pnl', 'recommendation'
]]
vcs_followup_frame['long_short_ratio'] = vcs_followup_frame[
'long_short_ratio'].round()
vcs_followup_frame['net_oev'] = vcs_followup_frame['net_oev'].round(1)
vcs_followup_frame['long_oev'] = vcs_followup_frame['long_oev'].round(1)
vcs_followup_frame['short_oev'] = vcs_followup_frame['short_oev'].round(1)
vcs_followup_frame['net_theta'] = vcs_followup_frame['net_theta'].round(1)
vcs_followup_frame.sort_values('total_pnl', ascending=False, inplace=True)
vcs_followup_frame.reset_index(drop=True, inplace=True)
vcs_followup_frame.loc[len(vcs_followup_frame.index)] = [
'TOTAL', None, None, None, None, vcs_followup_frame['net_theta'].sum(),
None, None, None, vcs_followup_frame['total_pnl'].sum(), None
]
vcs_followup_frame.to_excel(writer, sheet_name='vcs')
worksheet_vcs = writer.sheets['vcs']
worksheet_vcs.set_column('B:B', 18)
worksheet_vcs.freeze_panes(1, 0)
worksheet_vcs.autofilter(0, 0, len(vcs_followup_frame.index),
len(vcs_followup_frame.columns))
if 'con' not in kwargs.keys():
con.close()
return writer
def generate_futures_butterfly_followup_report(**kwargs):
con = msu.get_my_sql_connection(**kwargs)
if 'as_of_date' in kwargs.keys():
as_of_date = kwargs['as_of_date']
else:
as_of_date = exp.doubledate_shift_bus_days()
kwargs['as_of_date'] = as_of_date
if 'writer' in kwargs.keys():
writer = kwargs['writer']
else:
ta_output_dir = dn.get_dated_directory_extension(
folder_date=as_of_date, ext='ta')
writer = pd.ExcelWriter(ta_output_dir + '/followup.xlsx',
engine='xlsxwriter')
strategy_frame = ts.get_open_strategies(**kwargs)
strategy_class_list = [
sc.convert_from_string_to_dictionary(
string_input=strategy_frame['description_string'][x])
['strategy_class'] for x in range(len(strategy_frame.index))
]
futures_butterfly_indx = [
x == 'futures_butterfly' for x in strategy_class_list
]
futures_butterfly_frame = strategy_frame[futures_butterfly_indx]
results = [
sf.get_results_4strategy(
alias=futures_butterfly_frame['alias'].iloc[x],
strategy_info_output=futures_butterfly_frame.iloc[x])
for x in range(len(futures_butterfly_frame.index))
]
butterfly_followup_frame = pd.DataFrame(results)
butterfly_followup_frame['alias'] = futures_butterfly_frame['alias'].values
pnl_frame = pm.get_daily_pnl_snapshot(as_of_date=as_of_date,
con=con,
name='final')
risk_output = hr.get_historical_risk_4open_strategies(
as_of_date=as_of_date, con=con)
merged_frame1 = pd.merge(butterfly_followup_frame,
pnl_frame,
how='left',
on='alias')
merged_frame2 = pd.merge(merged_frame1,
risk_output['strategy_risk_frame'],
how='left',
on='alias')
butterfly_followup_frame = merged_frame2[[
'alias', 'ticker_head', 'holding_tr_dte', 'short_tr_dte', 'z1_initial',
'z1', 'QF_initial', 'QF', 'total_pnl', 'downside', 'recommendation'
]]
butterfly_followup_frame.rename(columns={
'alias': 'Alias',
'ticker_head': 'TickerHead',
'holding_tr_dte': 'HoldingTrDte',
'short_tr_dte': 'ShortTrDte',
'z1_initial': 'Z1Initial',
'z1': 'Z1',
'QF_initial': 'QFInitial',
'total_pnl': 'TotalPnl',
'downside': 'Downside',
'recommendation': 'Recommendation'
},
inplace=True)
butterfly_followup_frame.sort_values('QF', ascending=False, inplace=True)
butterfly_followup_frame['Z1'] = butterfly_followup_frame['Z1'].round(2)
butterfly_followup_frame.to_excel(writer, sheet_name='butterflies')
worksheet_butterflies = writer.sheets['butterflies']
worksheet_butterflies.set_column('B:B', 26)
worksheet_butterflies.freeze_panes(1, 0)
worksheet_butterflies.autofilter(0, 0, len(butterfly_followup_frame.index),
len(butterfly_followup_frame.columns))
if 'con' not in kwargs.keys():
con.close()
return writer
