def basis_swap_term_structure(
asset: Asset,
spread_benchmark_type: BenchmarkType = None,
spread_tenor: str = None,
reference_benchmark_type: BenchmarkType = None,
reference_tenor: str = None,
forward_tenor: str = 'Spot',
pricing_date: Optional[GENERIC_DATE] = None,
*,
source: str = None,
real_time: bool = False,
) -> Series:
"""
GS end-of-day Floating-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param spread_benchmark_type: benchmark type of spread leg on which basis spread is added e.g. LIBOR
:param spread_tenor: relative date representation of expiration date of spread leg e.g. 1m
:param reference_benchmark_type: benchmark type of reference leg e.g. LIBOR
:param reference_tenor: relative date representation of expiration date of reference leg e.g. 1m
:param forward_tenor: relative date representation of forward starting point eg: '1y' or 'Spot' for spot
starting swaps
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate curve
"""
if real_time:
raise NotImplementedError('realtime basis_swap_rate not implemented')
currency = CurrencyEnum(asset.get_identifier(AssetIdentifier.BLOOMBERG_ID))
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP']:
raise NotImplementedError(
'Data not available for {} basis swap rates'.format(
currency.value))
for benchmark_type in [spread_benchmark_type, reference_benchmark_type]:
if benchmark_type is not None and \
benchmark_type.value not in CURRENCY_TO_SWAP_RATE_BENCHMARK[currency.value].keys():
raise MqValueError('%s is not supported for %s', benchmark_type,
currency.value)
for floating_rate_tenor in [spread_tenor, reference_tenor]:
if not re.fullmatch('(\\d+)([bdwmy])', floating_rate_tenor):
raise MqValueError('invalid floating rate tenor ' +
floating_rate_tenor)
if forward_tenor == '0b' or forward_tenor is None or forward_tenor == 'Spot':
forward_tenor = '0d'
elif not re.fullmatch('(\\d+)([bdwmy])', forward_tenor):
raise MqValueError('invalid forward tenor ' + forward_tenor)
# default benchmark types
legs_w_defaults = dict()
legs_w_defaults['spread'] = _get_swap_leg_defaults(currency,
spread_benchmark_type,
spread_tenor)
legs_w_defaults['reference'] = _get_swap_leg_defaults(
currency, reference_benchmark_type, reference_tenor)
csaTerms = currency.value + '-1'
clearing_house = 'LCH'
kwargs = dict(
type='BasisSwap',
asset_parameters_payer_rate_option=legs_w_defaults['spread']
['benchmark_type'],
asset_parameters_payer_designated_maturity=legs_w_defaults['spread']
['floating_rate_tenor'],
asset_parameters_receiver_rate_option=legs_w_defaults['reference']
['benchmark_type'],
asset_parameters_receiver_designated_maturity=legs_w_defaults[
'reference']['floating_rate_tenor'],
asset_parameters_clearing_house=clearing_house,
asset_parameters_effective_date=forward_tenor,
asset_parameters_notional_currency=currency.name,
pricing_location=legs_w_defaults['spread']['pricing_location'])
assets = GsAssetApi.get_many_assets(**kwargs)
if len(assets) == 0:
raise MqValueError(
'Specified arguments did not match any asset in the dataset')
else:
rate_mqids = [asset.id for asset in assets]
_logger.debug(
'where spread_benchmark_type=%s, spread_tenor=%s, reference_benchmark_type=%s, '
'reference_tenor=%s, forward_tenor=%s, pricing_location=%s ',
legs_w_defaults['spread']['benchmark_type'],
legs_w_defaults['spread']['floating_rate_tenor'],
legs_w_defaults['reference']['benchmark_type'],
legs_w_defaults['reference']['floating_rate_tenor'], forward_tenor,
legs_w_defaults['spread']['pricing_location'])
start, end = _range_from_pricing_date(assets[0].exchange, pricing_date)
with DataContext(start, end):
where = FieldFilterMap(csaTerms=csaTerms)
q = GsDataApi.build_market_data_query(rate_mqids,
QueryType.BASIS_SWAP_RATE,
where=where,
source=source,
real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
return pd.Series()
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
business_day = _get_custom_bd(asset.exchange)
df = df.assign(expirationDate=df.index +
df['terminationTenor'].map(_to_offset) + business_day -
business_day)
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date:DataContext.current.end_date]
return df['basisSwapRate'] if not df.empty else pd.Series()
def basis_swap_term_structure(asset: Asset, spread_benchmark_type: BenchmarkType = None, spread_tenor: str = None,
reference_benchmark_type: BenchmarkType = None, reference_tenor: str = None,
forward_tenor: Optional[GENERIC_DATE] = None,
clearing_house: _ClearingHouse = None,
pricing_date: Optional[GENERIC_DATE] = None,
*, source: str = None, real_time: bool = False, ) -> Series:
"""
GS end-of-day Floating-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param spread_benchmark_type: benchmark type of spread leg on which basis spread is added e.g. LIBOR
:param spread_tenor: relative date representation of expiration date of spread leg e.g. 1m
:param reference_benchmark_type: benchmark type of reference leg e.g. LIBOR
:param reference_tenor: relative date representation of expiration date of reference leg e.g. 1m
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param clearing_house: Example - "LCH", "EUREX", "JSCC", "CME"
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate curve
"""
if real_time:
raise NotImplementedError('realtime basis_swap_rate not implemented')
currency = CurrencyEnum(asset.get_identifier(AssetIdentifier.BLOOMBERG_ID))
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP']:
raise NotImplementedError('Data not available for {} basis swap rates'.format(currency.value))
clearing_house = _check_clearing_house(clearing_house)
for benchmark_type in [spread_benchmark_type, reference_benchmark_type]:
_check_benchmark_type(currency, benchmark_type)
# default benchmark types
legs_w_defaults = dict()
legs_w_defaults['spread'] = _get_swap_leg_defaults(currency, spread_benchmark_type, spread_tenor)
legs_w_defaults['reference'] = _get_swap_leg_defaults(currency, reference_benchmark_type, reference_tenor)
for key, leg in legs_w_defaults.items():
if not re.fullmatch('(\\d+)([bdwmy])', leg['floating_rate_tenor']):
raise MqValueError('invalid floating rate tenor ' + leg['floating_rate_tenor'] + ' index: ' +
leg['benchmark_type'])
forward_tenor = check_forward_tenor(forward_tenor)
calendar = legs_w_defaults['spread']['pricing_location'].value
if pricing_date is not None and pricing_date in list(GsCalendar.get(calendar).holidays):
raise MqValueError('Specified pricing date is a holiday in {} calendar'.format(calendar))
csaTerms = currency.value + '-1'
kwargs = dict(type='BasisSwap', asset_parameters_payer_rate_option=legs_w_defaults['spread']['benchmark_type'],
asset_parameters_payer_designated_maturity=legs_w_defaults['spread']['floating_rate_tenor'],
asset_parameters_receiver_rate_option=legs_w_defaults['reference']['benchmark_type'],
asset_parameters_receiver_designated_maturity=legs_w_defaults['reference']['floating_rate_tenor'],
asset_parameters_clearing_house=clearing_house.value, asset_parameters_effective_date=forward_tenor,
asset_parameters_notional_currency=currency.name,
pricing_location=legs_w_defaults['spread']['pricing_location'].value)
assets = GsAssetApi.get_many_assets(**kwargs)
if len(assets) == 0:
raise MqValueError('Specified arguments did not match any asset in the dataset')
else:
rate_mqids = [asset.id for asset in assets]
asset_string = ''
for mqid in rate_mqids:
asset_string = asset_string + ',' + mqid
_logger.debug('assets returned %s', asset_string)
_logger.debug('where spread_benchmark_type=%s, spread_tenor=%s, reference_benchmark_type=%s, '
'reference_tenor=%s, forward_tenor=%s, pricing_location=%s ',
legs_w_defaults['spread']['benchmark_type'], legs_w_defaults['spread']['floating_rate_tenor'],
legs_w_defaults['reference']['benchmark_type'], legs_w_defaults['reference']['floating_rate_tenor'],
forward_tenor, legs_w_defaults['spread']['pricing_location'].value)
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
where = dict(csaTerms=csaTerms)
q = GsDataApi.build_market_data_query(rate_mqids, QueryType.BASIS_SWAP_RATE, where=where,
source=source, real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
series = ExtendedSeries()
else:
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
business_day = _get_custom_bd(calendar)
df = df.assign(expirationDate=df.index + df['terminationTenor'].map(_to_offset) + business_day - business_day)
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date: DataContext.current.end_date]
series = ExtendedSeries() if df.empty else ExtendedSeries(df['basisSwapRate'])
series.dataset_ids = getattr(df, 'dataset_ids', ())
return series
def swap_term_structure(asset: Asset,
benchmark_type: BenchmarkType = None,
floating_rate_tenor: str = None,
forward_tenor: Optional[GENERIC_DATE] = None,
pricing_date: Optional[GENERIC_DATE] = None,
*,
source: str = None,
real_time: bool = False) -> Series:
"""
GS end-of-day Fixed-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param benchmark_type: benchmark type e.g. LIBOR
:param floating_rate_tenor: floating index rate
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate term structure
"""
if real_time:
raise NotImplementedError('realtime swap_rate not implemented')
currency = asset.get_identifier(AssetIdentifier.BLOOMBERG_ID)
currency = CurrencyEnum(currency)
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP', 'CHF', 'SEK']:
raise NotImplementedError(
'Data not available for {} swap rates'.format(currency.value))
clearing_house = 'LCH'
_check_benchmark_type(currency, benchmark_type)
forward_tenor = check_forward_tenor(forward_tenor)
defaults = _get_swap_leg_defaults(currency, benchmark_type,
floating_rate_tenor)
if not re.fullmatch('(\\d+)([bdwmy])', defaults['floating_rate_tenor']):
raise MqValueError('invalid floating rate tenor ' +
defaults['floating_rate_tenor'] + ' for index: ' +
defaults['benchmark_type'])
calendar = defaults['pricing_location'].value
if pricing_date is not None and pricing_date in list(
GsCalendar.get(calendar).holidays):
raise MqValueError(
'Specified pricing date is a holiday in {} calendar'.format(
calendar))
csaTerms = currency.value + '-1'
fixed_rate = 'ATM'
kwargs = dict(
type='Swap',
asset_parameters_floating_rate_option=defaults['benchmark_type'],
asset_parameters_fixed_rate=fixed_rate,
asset_parameters_clearing_house=clearing_house,
asset_parameters_floating_rate_designated_maturity=defaults[
'floating_rate_tenor'],
asset_parameters_effective_date=forward_tenor,
asset_parameters_notional_currency=currency.name,
pricing_location=defaults['pricing_location'].value)
assets = GsAssetApi.get_many_assets(**kwargs)
if len(assets) == 0:
raise MqValueError(
'Specified arguments did not match any asset in the dataset')
else:
rate_mqids = [asset.id for asset in assets]
asset_string = ''
for mqid in rate_mqids:
asset_string = asset_string + ',' + mqid
_logger.debug('assets returned %s', asset_string)
_logger.debug(
'where benchmark_type=%s, floating_rate_tenor=%s, forward_tenor=%s, '
'pricing_location=%s', defaults['benchmark_type'],
defaults['floating_rate_tenor'], forward_tenor,
defaults['pricing_location'].value)
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
where = FieldFilterMap(csaTerms=csaTerms)
q = GsDataApi.build_market_data_query(rate_mqids,
QueryType.SWAP_RATE,
where=where,
source=source,
real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
return pd.Series()
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
business_day = _get_custom_bd(calendar)
df = df.assign(expirationDate=df.index +
df['terminationTenor'].map(_to_offset) + business_day -
business_day)
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date:DataContext.current.end_date]
return df['swapRate'] if not df.empty else pd.Series()
def inflation_swap_term(asset: Asset,
index_type: str = None,
forward_tenor: Optional[GENERIC_DATE] = None,
pricing_date: Optional[GENERIC_DATE] = None,
clearing_house: tm_rates._ClearingHouse = None,
location: PricingLocation = None,
*,
source: str = None,
real_time: bool = False,
request_id: Optional[str] = None) -> Series:
"""
Forward term structure of GS end-of-day inflation swaps.
:param asset: asset object loaded from security master
:param index_type: benchmark type e.g. UKRPI
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param pricing_date: YYYY-MM-DD or relative date
:param clearing_house: Example - "LCH", "EUREX", "JSCC", "CME"
:param location: Example - "TKO", "LDN", "NYC"
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:param request_id: service request id, if any
:return: inflation swap forward term curve
"""
currency = CurrencyEnum(asset.get_identifier(AssetIdentifier.BLOOMBERG_ID))
if currency.value not in CURRENCY_TO_INDEX_BENCHMARK.keys():
raise NotImplementedError(
'Data not available for {} inflation swap rates'.format(
currency.value))
if location is None:
location = tm_rates._default_pricing_location(currency)
else:
location = PricingLocation(location)
calendar = location.value
if pricing_date is not None and pricing_date in list(
GsCalendar.get(calendar).holidays):
raise MqValueError(
'Specified pricing date is a holiday in {} calendar'.format(
calendar))
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
df = _get_inflation_swap_data(asset=asset,
swap_tenor=None,
index_type=index_type,
forward_tenor=forward_tenor,
clearing_house=clearing_house,
source=source,
real_time=real_time,
query_type=QueryType.SWAP_RATE,
location=location,
allow_many=True,
request_id=request_id)
if df.empty:
series = ExtendedSeries(dtype=float)
else:
latest = df.index.max()
# TODO: add forward tenor to latest. Technically series index should be latest + forwardTenor + terminationTenor
# TODO: but that would make it hard to compare term structure btwn different forwardTenors
# TODO: may be implemented some day when plot can handle different x-axes
# TODO: As-is, this is consistent with other swap term measures axis handling
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
biz_day = _get_custom_bd(calendar)
df['expirationDate'] = df['terminationTenor'].apply(
_get_term_struct_date, args=(latest, biz_day))
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date:DataContext.current.
end_date]
series = ExtendedSeries(
dtype=float) if df.empty else ExtendedSeries(df['swapRate'])
series.dataset_ids = getattr(df, 'dataset_ids', ())
if series.empty: # Raise descriptive error if no data returned + historical date context
check_forward_looking(None, source, 'inflation_swap_term')
return series
def basis_swap_term_structure(
asset: Asset,
spread_benchmark_type: str = None,
spread_tenor: str = None,
reference_benchmark_type: str = None,
reference_tenor: str = None,
forward_tenor: Optional[GENERIC_DATE] = None,
clearing_house: _ClearingHouse = None,
pricing_date: Optional[GENERIC_DATE] = None,
*,
source: str = None,
real_time: bool = False,
) -> Series:
"""
GS end-of-day Floating-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param spread_benchmark_type: benchmark type of spread leg on which basis spread is added e.g. LIBOR
:param spread_tenor: relative date representation of expiration date of spread leg e.g. 1m
:param reference_benchmark_type: benchmark type of reference leg e.g. LIBOR
:param reference_tenor: relative date representation of expiration date of reference leg e.g. 1m
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param clearing_house: Example - "LCH", "EUREX", "JSCC", "CME"
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate curve
"""
if real_time:
raise NotImplementedError('realtime basis_swap_rate not implemented')
kwargs = _get_basis_swap_kwargs(
asset=asset,
spread_benchmark_type=spread_benchmark_type,
spread_tenor=spread_tenor,
reference_benchmark_type=reference_benchmark_type,
reference_tenor=reference_tenor,
forward_tenor=forward_tenor,
clearing_house=clearing_house)
calendar = kwargs['pricing_location']
if pricing_date is not None and pricing_date in list(
GsCalendar.get(calendar).holidays):
raise MqValueError(
'Specified pricing date is a holiday in {} calendar'.format(
calendar))
rate_mqids = _get_mdapi_rates_assets(**kwargs)
_logger.debug('assets returned %s', ', '.join(rate_mqids))
_logger.debug(
'where spread_benchmark_type=%s, spread_tenor=%s, reference_benchmark_type=%s, '
'reference_tenor=%s, forward_tenor=%s, pricing_location=%s ',
kwargs['asset_parameters_payer_rate_option'],
kwargs['asset_parameters_payer_designated_maturity'],
kwargs['asset_parameters_receiver_rate_option'],
kwargs['asset_parameters_receiver_designated_maturity'],
kwargs['asset_parameters_effective_date'], kwargs['pricing_location'])
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
where = dict(csaTerms=kwargs['asset_parameters_notional_currency'] +
'-1')
q = GsDataApi.build_market_data_query(rate_mqids,
QueryType.BASIS_SWAP_RATE,
where=where,
source=source,
real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
series = ExtendedSeries()
else:
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
business_day = _get_custom_bd(calendar)
df = df.assign(expirationDate=df.index +
df['terminationTenor'].map(_to_offset) + business_day -
business_day)
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date:DataContext.current.
end_date]
series = ExtendedSeries() if df.empty else ExtendedSeries(
df['basisSwapRate'])
series.dataset_ids = getattr(df, 'dataset_ids', ())
return series
def basis_swap_term_structure(
asset: Asset,
spread_benchmark_type: str = None,
spread_tenor: str = None,
reference_benchmark_type: str = None,
reference_tenor: str = None,
tenor_type: _SwapTenorType = None,
tenor: Optional[GENERIC_DATE] = None,
clearing_house: _ClearingHouse = None,
pricing_date: Optional[GENERIC_DATE] = None,
*,
source: str = None,
real_time: bool = False,
) -> Series:
"""
GS end-of-day Floating-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param spread_benchmark_type: benchmark type of spread leg on which basis spread is added e.g. LIBOR
:param spread_tenor: relative date representation of expiration date of spread leg e.g. 1m
:param reference_benchmark_type: benchmark type of reference leg e.g. LIBOR
:param reference_tenor: relative date representation of expiration date of reference leg e.g. 1m
:param tenor_type: specify which tenor should be fixed, SWAP_TENOR or FORWARD_TENOR
:param tenor: absolute / relative date representation of forward starting point or swap maturity
:param clearing_house: Example - "LCH", "EUREX", "JSCC", "CME"
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate curve
"""
if real_time:
raise NotImplementedError('realtime basis_swap_rate not implemented')
tenor_type = _check_tenor_type(tenor_type)
tenor_dict = _check_term_structure_tenor(tenor_type=tenor_type,
tenor=tenor)
kwargs = _get_basis_swap_kwargs(
asset=asset,
spread_benchmark_type=spread_benchmark_type,
spread_tenor=spread_tenor,
reference_benchmark_type=reference_benchmark_type,
reference_tenor=reference_tenor,
clearing_house=clearing_house)
kwargs[tenor_dict['tenor_dataset_field']] = tenor_dict['tenor']
calendar = kwargs['pricing_location']
if pricing_date is not None and pricing_date in list(
GsCalendar.get(calendar).holidays):
raise MqValueError(
'Specified pricing date is a holiday in {} calendar'.format(
calendar))
rate_mqids = _get_mdapi_rates_assets(**kwargs)
if isinstance(rate_mqids, str): # single asset returned
rate_mqids = [rate_mqids]
_logger.debug('assets returned %s', ', '.join(rate_mqids))
_logger.debug(
'where spread_benchmark_type=%s, spread_tenor=%s, reference_benchmark_type=%s, '
'reference_tenor=%s, %s=%s, pricing_location=%s ',
kwargs['asset_parameters_payer_rate_option'],
kwargs['asset_parameters_payer_designated_maturity'],
kwargs['asset_parameters_receiver_rate_option'],
kwargs['asset_parameters_receiver_designated_maturity'],
kwargs[tenor_dict['tenor_dataset_field']], tenor_dict['tenor'],
kwargs['pricing_location'])
where = _get_basis_swap_csa_terms(
kwargs['asset_parameters_notional_currency'],
kwargs['asset_parameters_payer_rate_option'],
kwargs['asset_parameters_receiver_rate_option'])
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
q = GsDataApi.build_market_data_query(rate_mqids,
QueryType.BASIS_SWAP_RATE,
where=where,
source=source,
real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
series = ExtendedSeries()
else:
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
biz_day = _get_custom_bd(calendar)
col_to_plot = tenor_dict['tenor_to_plot']
if isinstance(df, pd.Series): # single asset returned
series = ExtendedSeries(
pd.Series(df['basisSwapRate'],
index=[
_get_term_struct_date(df[col_to_plot], latest,
biz_day)
]))
series = series.loc[DataContext.current.start_date:DataContext.
current.end_date]
else:
if col_to_plot == 'effectiveTenor': # for forward term structure imm date assets
df = df[~df[col_to_plot].isin(['imm1', 'imm2', 'imm3', 'imm4']
)]
df['expirationDate'] = df[col_to_plot].apply(_get_term_struct_date,
args=(latest,
biz_day))
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date:DataContext.current.
end_date]
series = ExtendedSeries() if df.empty else ExtendedSeries(
df['basisSwapRate'])
series.dataset_ids = getattr(df, 'dataset_ids', ())
return series
def swap_term_structure(asset: Asset,
benchmark_type: str = None,
floating_rate_tenor: str = None,
tenor_type: _SwapTenorType = None,
tenor: Optional[GENERIC_DATE] = None,
clearing_house: _ClearingHouse = None,
pricing_date: Optional[GENERIC_DATE] = None,
*,
source: str = None,
real_time: bool = False) -> Series:
"""
GS end-of-day Fixed-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param benchmark_type: benchmark type e.g. LIBOR
:param floating_rate_tenor: floating index rate
:param tenor_type: specify which tenor should be fixed, SWAP_TENOR or FORWARD_TENOR
:param tenor: absolute / relative date representation of forward starting point or swap maturity
:param clearing_house: Example - "LCH", "EUREX", "JSCC", "CME"
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate term structure
"""
if real_time:
raise NotImplementedError('realtime swap_rate not implemented')
currency = asset.get_identifier(AssetIdentifier.BLOOMBERG_ID)
currency = CurrencyEnum(currency)
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP', 'CHF', 'SEK']:
raise NotImplementedError(
'Data not available for {} swap rates'.format(currency.value))
clearing_house = _check_clearing_house(clearing_house)
benchmark_type = _check_benchmark_type(currency, benchmark_type)
tenor_type = _check_tenor_type(tenor_type)
tenor_dict = _check_term_structure_tenor(tenor_type=tenor_type,
tenor=tenor)
defaults = _get_swap_leg_defaults(currency, benchmark_type,
floating_rate_tenor)
if not re.fullmatch('(\\d+)([bdwmy])', defaults['floating_rate_tenor']):
raise MqValueError('invalid floating rate tenor ' +
defaults['floating_rate_tenor'] + ' for index: ' +
defaults['benchmark_type'])
calendar = defaults['pricing_location'].value
if pricing_date is not None and pricing_date in list(
GsCalendar.get(calendar).holidays):
raise MqValueError(
'Specified pricing date is a holiday in {} calendar'.format(
calendar))
fixed_rate = 'ATM'
kwargs = dict(
type='Swap',
asset_parameters_floating_rate_option=defaults['benchmark_type'],
asset_parameters_fixed_rate=fixed_rate,
asset_parameters_clearing_house=clearing_house.value,
asset_parameters_floating_rate_designated_maturity=defaults[
'floating_rate_tenor'],
asset_parameters_notional_currency=currency.name,
pricing_location=defaults['pricing_location'].value)
kwargs[tenor_dict['tenor_dataset_field']] = tenor_dict['tenor']
rate_mqids = _get_mdapi_rates_assets(**kwargs)
if isinstance(rate_mqids, str):
rate_mqids = [rate_mqids]
_logger.debug('assets returned %s', ', '.join(rate_mqids))
_logger.debug(
'where benchmark_type=%s, floating_rate_tenor=%s, %s=%s, '
'pricing_location=%s', defaults['benchmark_type'],
defaults['floating_rate_tenor'], tenor_type.value, tenor_dict['tenor'],
defaults['pricing_location'].value)
where = _get_swap_csa_terms(currency.value, defaults['benchmark_type'])
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
q = GsDataApi.build_market_data_query(rate_mqids,
QueryType.SWAP_RATE,
where=where,
source=source,
real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
series = ExtendedSeries()
else:
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
biz_day = _get_custom_bd(calendar)
col_to_plot = tenor_dict['tenor_to_plot']
if isinstance(df, pd.Series):
series = ExtendedSeries(
pd.Series(df['swapRate'],
index=[
_get_term_struct_date(df[col_to_plot], latest,
biz_day)
]))
series = series.loc[DataContext.current.start_date:DataContext.
current.end_date]
else:
if col_to_plot == 'effectiveTenor':
df = df[~df[col_to_plot].isin(['imm1', 'imm2', 'imm3', 'imm4']
)]
df['expirationDate'] = df[col_to_plot].apply(_get_term_struct_date,
args=(latest,
biz_day))
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date:DataContext.current.
end_date]
series = ExtendedSeries() if df.empty else ExtendedSeries(
df['swapRate'])
series.dataset_ids = getattr(df, 'dataset_ids', ())
return series
