def _grab_bbg_data(self):
bbg = BBG()
self.contract_list = bbg.fetch_futures_list(
generic_ticker=self.comm_bbg_code + '1 Comdty')
self.first_notice_dates = bbg.fetch_contract_parameter(
securities=self.contract_list,
field='FUT_NOTICE_FIRST').sort_values('FUT_NOTICE_FIRST')
# Grab all contract series
df_prices = bbg.fetch_series(securities=self.contract_list,
fields='PX_LAST',
startdate=self.start_date,
enddate=self.end_date)
self.prices = df_prices.fillna(method='ffill')
startdate=start_date,
enddate=end_date)
print(df)
# Grabs cashflow payments of corporate bonds
df = bbg.fetch_cash_flow('EI1436001 Govt', pd.to_datetime('03-jul-2017'))
print(df)
# Grabs weights of the components of an index
df = bbg.fetch_index_weights(index_name='IBOV Index',
ref_date=pd.to_datetime('03-jul-2017'))
print(df)
print(df.sum())
# Grabs all the contracts from a generic series
futures_list = bbg.fetch_futures_list(generic_ticker='TY1 Comdty')
print(futures_list)
# grabs the first notice date for each contract
df_fn = bbg.fetch_contract_parameter(securities=futures_list,
field='FUT_NOTICE_FIRST')
print(df_fn)
# fetches fields with bulk data
df_bulk = bbg.fetch_bulk_data(index_name='AAPL US Equity',
field='PG_REVENUE',
ref_date=start_date)
print(df_bulk)
# fetches historical dividends
df_div = bbg.fetch_dividends('AAPL US Equity', end_date)
class BuildBondFutureTracker(object):
futures_ticker_dict = {
'US': 'TY',
'GE': 'RX',
'FR': 'OAT',
'IT': 'IK',
'JP': 'JB',
'AU': 'XM',
'UK': 'G ',
'CA': 'CN'
}
fx_dict = {
'GE': 'EURUSD Curncy',
'UK': 'GBPUSD Curncy',
'CA': 'CADUSD Curncy',
'JP': 'JPYUSD Curncy',
'AU': 'AUDUSD Curncy',
'FR': 'EURUSD Curncy',
'IT': 'EURUSD Curncy',
'US': 'USD Curncy'
}
def __init__(self, country, start_date, end_date):
self.bbg = BBG()
self.country = country
self.start_date = self._assert_date_type(start_date)
self.end_date = self._assert_date_type(end_date)
self.generic_tickers = [
self.futures_ticker_dict[country] + str(x) + ' Comdty'
for x in range(1, 4)
]
self.df_generics = self._get_generic_future_series()
self.df_uc = self._get_underlying_contracts()
self.contract_list = self._get_contracts_list()
self.df_fn = self._get_first_notice_dates()
self.df_prices = self._get_all_prices()
df_tracker = self._build_tracker()
self.tr_index = df_tracker[['er_index']]
self.df_roll_info = df_tracker[[
'contract_rolling_out', 'roll_out_date', 'holdings'
]].dropna(how='any')
def _get_generic_future_series(self):
df = self.bbg.fetch_series(securities=self.generic_tickers,
fields='PX_LAST',
startdate=self.start_date,
enddate=self.end_date)
return df
def _get_underlying_contracts(self):
df = self.bbg.fetch_series(securities=self.generic_tickers,
fields='FUT_CUR_GEN_TICKER',
startdate=self.start_date,
enddate=self.end_date)
df = df.reindex(self.df_generics.index).fillna(method='ffill')
return df
def _get_contracts_list(self):
contract_list = self.bbg.fetch_futures_list(
generic_ticker=self.futures_ticker_dict[self.country] + '1 Comdty')
return contract_list
def _get_first_notice_dates(self):
df = self.bbg.fetch_contract_parameter(
securities=self.contract_list,
field='FUT_NOTICE_FIRST').sort_values('FUT_NOTICE_FIRST')
return df
def _get_all_prices(self):
tickers = self.contract_list + [self.fx_dict[self.country]]
df = self.bbg.fetch_series(securities=tickers,
fields='PX_LAST',
startdate=self.start_date,
enddate=self.end_date)
df = df.reindex(self.df_generics.index).fillna(method='ffill')
return df
def _build_tracker(self):
df_tracker = pd.DataFrame(index=self.df_generics.index,
columns=[
'contract_rolling_out', 'er_index',
'roll_out_date', 'holdings'
])
# set the values for the initial date
dt_ini = self.df_uc.index[0]
df_tracker.loc[dt_ini, 'er_index'] = 100
contract_rolling_out = self.df_uc.loc[
dt_ini,
self.futures_ticker_dict[self.country] + '2 Comdty'] + ' Comdty'
df_tracker.loc[dt_ini, 'contract_rolling_out'] = contract_rolling_out
holdings = df_tracker.loc[dt_ini, 'er_index'] / (
self.df_generics.loc[
dt_ini, self.futures_ticker_dict[self.country] + '2 Comdty'] *
self.df_prices[self.fx_dict[self.country]].loc[dt_ini])
df_tracker.loc[dt_ini, 'holdings'] = holdings
roll_out_date = self.df_fn.loc[df_tracker.loc[dt_ini,
'contract_rolling_out'],
'FUT_NOTICE_FIRST'] - BDay(1)
df_tracker.loc[dt_ini, 'roll_out_date'] = roll_out_date
for d, dm1 in zip(df_tracker.index[1:], df_tracker.index[:-1]):
df_tracker.loc[d, 'contract_rolling_out'] = contract_rolling_out
price_dm1 = self.df_prices.loc[dm1, contract_rolling_out]
price_d = self.df_prices.loc[d, contract_rolling_out]
pnl = holdings * (price_d - price_dm1) * self.df_prices[
self.fx_dict[self.country]].loc[d]
if math.isnan(pnl):
pnl = 0
df_tracker.loc[d,
'er_index'] = df_tracker.loc[dm1, 'er_index'] + pnl
if d >= roll_out_date.date():
contract_rolling_out = (
self.df_uc.loc[d, self.futures_ticker_dict[self.country] +
'2 Comdty'] + ' Comdty')
df_tracker.loc[d,
'contract_rolling_out'] = contract_rolling_out
holdings = df_tracker.loc[d, 'er_index'] / (
self.df_generics.loc[
d, self.futures_ticker_dict[self.country] + '2 Comdty']
* self.df_prices[self.fx_dict[self.country]].loc[d])
df_tracker.loc[d, 'holdings'] = holdings
roll_out_date = self.df_fn.loc[df_tracker.loc[
d, 'contract_rolling_out'], 'FUT_NOTICE_FIRST'] - BDay(1)
df_tracker.loc[d, 'roll_out_date'] = roll_out_date
return df_tracker
@staticmethod
def _assert_date_type(date):
if type(date) is pd.Timestamp:
date = date
else:
date = pd.to_datetime(date)
return date
# value of the qoutes
df_generics = bbg.fetch_series(
securities=['JB1 Comdty', 'JB2 Comdty', 'JB3 Comdty'],
fields='PX_LAST',
startdate=start_date,
enddate=end_date)
# underlying contracts
df_uc = bbg.fetch_series(securities=['JB1 Comdty', 'JB2 Comdty', 'JB3 Comdty'],
fields='FUT_CUR_GEN_TICKER',
startdate=start_date,
enddate=end_date)
df_uc = df_uc.reindex(df_generics.index).fillna(method='ffill')
# all contracts
contract_list = bbg.fetch_futures_list(generic_ticker='JB1 Comdty')
# first notice date for the contract
df_fn = bbg.fetch_contract_parameter(
securities=contract_list,
field='FUT_NOTICE_FIRST').sort_values('FUT_NOTICE_FIRST')
# Grab all contract series
contract_list = contract_list + ['JPYUSD Curncy']
df_prices = bbg.fetch_series(securities=contract_list,
fields='PX_LAST',
startdate=start_date,
enddate=end_date)
df_prices = df_prices.reindex(df_generics.index).fillna(method='ffill')
# sets up the dataframe that will hold our results
class BondFutureTracker(object):
futures_ticker_dict = {
'US': 'TY',
'DE': 'RX',
'FR': 'OAT',
'IT': 'IK',
'JP': 'JB',
'AU': 'XM',
'GB': 'G ',
'CA': 'CN'
}
fx_dict = {
'DE': 'EURUSD Curncy',
'GB': 'GBPUSD Curncy',
'CA': 'CADUSD Curncy',
'JP': 'JPYUSD Curncy',
'AU': 'AUDUSD Curncy',
'FR': 'EURUSD Curncy',
'IT': 'EURUSD Curncy',
'US': 'USD Curncy'
}
def __init__(self, country, start_date, end_date):
assert country in list(
self.futures_ticker_dict.keys()), 'Country not yet supported'
self.bbg = BBG()
self.country = country
self.start_date = self._assert_date_type(start_date)
self.end_date = self._assert_date_type(end_date)
self.generic_tickers = [
self.futures_ticker_dict[country] + str(x) + ' Comdty'
for x in range(1, 4)
]
self.df_generics = self._get_generic_future_series()
self.df_uc = self._get_underlying_contracts()
self.contract_list = self._get_contracts_list()
self.df_fn = self._get_first_notice_dates()
self.df_prices = self._get_all_prices()
self.df_tracker = self._build_tracker()
self.tr_index = self.df_tracker[['er_index']]
self.fh_ticker = 'fibf ' + self.country.lower() + ' 10y'
self.df_roll_info = self.df_tracker[[
'contract_rolling_out', 'roll_out_date', 'holdings'
]].dropna(how='any')
self.df_metadata = self._get_metadata()
self.df_tracker = self._get_tracker_melted()
def _get_tracker_melted(self):
df = self.df_tracker[['er_index']].rename({'er_index': self.fh_ticker},
axis=1)
df['time_stamp'] = df.index.to_series()
df = df.melt(id_vars='time_stamp',
var_name='fh_ticker',
value_name='value')
df = df.dropna()
return df
def _get_generic_future_series(self):
df = self.bbg.fetch_series(securities=self.generic_tickers,
fields='PX_LAST',
startdate=self.start_date,
enddate=self.end_date)
return df
def _get_underlying_contracts(self):
df = self.bbg.fetch_series(securities=self.generic_tickers,
fields='FUT_CUR_GEN_TICKER',
startdate=self.start_date,
enddate=self.end_date)
df = df.reindex(self.df_generics.index).fillna(method='ffill')
return df
def _get_contracts_list(self):
contract_list = self.bbg.fetch_futures_list(
generic_ticker=self.futures_ticker_dict[self.country] + '1 Comdty')
return contract_list
def _get_first_notice_dates(self):
df = self.bbg.fetch_contract_parameter(
securities=self.contract_list,
field='FUT_NOTICE_FIRST').sort_values('FUT_NOTICE_FIRST')
return df
def _get_all_prices(self):
tickers = self.contract_list + [self.fx_dict[self.country]]
df = self.bbg.fetch_series(securities=tickers,
fields='PX_LAST',
startdate=self.start_date,
enddate=self.end_date)
df = df.reindex(self.df_generics.index).fillna(method='ffill')
return df
def _build_tracker(self):
df_tracker = pd.DataFrame(index=self.df_generics.index,
columns=[
'contract_rolling_out', 'er_index',
'roll_out_date', 'holdings'
])
# set the values for the initial date
dt_ini = self.df_uc.dropna(how='all').index[0]
df_tracker.loc[dt_ini, 'er_index'] = 100
contract_rolling_out = self.df_uc.loc[
dt_ini,
self.futures_ticker_dict[self.country] + '2 Comdty'] + ' Comdty'
df_tracker.loc[dt_ini, 'contract_rolling_out'] = contract_rolling_out
holdings = df_tracker.loc[dt_ini, 'er_index'] / (
self.df_generics.loc[
dt_ini, self.futures_ticker_dict[self.country] + '2 Comdty'] *
self.df_prices[self.fx_dict[self.country]].loc[dt_ini])
df_tracker.loc[dt_ini, 'holdings'] = holdings
roll_out_date = self.df_fn.loc[df_tracker.loc[dt_ini,
'contract_rolling_out'],
'FUT_NOTICE_FIRST'] - BDay(1)
df_tracker.loc[dt_ini, 'roll_out_date'] = roll_out_date
for d, dm1 in zip(df_tracker.index[1:], df_tracker.index[:-1]):
df_tracker.loc[d, 'contract_rolling_out'] = contract_rolling_out
price_dm1 = self.df_prices.loc[dm1, contract_rolling_out]
price_d = self.df_prices.loc[d, contract_rolling_out]
pnl = holdings * (price_d - price_dm1) * self.df_prices[
self.fx_dict[self.country]].loc[d]
if math.isnan(pnl):
pnl = 0
df_tracker.loc[d,
'er_index'] = df_tracker.loc[dm1, 'er_index'] + pnl
if d >= roll_out_date:
contract_rolling_out = (
self.df_uc.loc[d, self.futures_ticker_dict[self.country] +
'2 Comdty'] + ' Comdty')
df_tracker.loc[d,
'contract_rolling_out'] = contract_rolling_out
holdings = df_tracker.loc[d, 'er_index'] / (
self.df_generics.loc[
d, self.futures_ticker_dict[self.country] + '2 Comdty']
* self.df_prices[self.fx_dict[self.country]].loc[d])
df_tracker.loc[d, 'holdings'] = holdings
roll_out_date = self.df_fn.loc[df_tracker.loc[
d, 'contract_rolling_out'], 'FUT_NOTICE_FIRST'] - BDay(1)
df_tracker.loc[d, 'roll_out_date'] = roll_out_date
return df_tracker
@staticmethod
def _assert_date_type(date):
if type(date) is pd.Timestamp:
date = date
else:
date = pd.to_datetime(date)
return date
def _get_metadata(self):
df = pd.DataFrame(index=[0],
data={
'fh_ticker':
self.fh_ticker,
'asset_class':
'fixed income',
'type':
'bond future',
'exchange_symbol':
self.futures_ticker_dict[self.country],
'currency':
'USD',
'country':
self.country,
'maturity':
10
})
return df
