SwaptionGroup#

class sigtech.framework.instruments.swaption.SwaptionGroup

A class representing a swaption group.

get_option_group_dependencies(t: datetime.time, tz: datetime.tzinfo, valuation_currency: str, start_dt: datetime.datetime, end_dt: datetime.datetime, greek_calculation_dependencies: bool = False) → list[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency]

Dependencies at the option group level

forecast_curves(data_dates, data_point=None)

Forecast curves for the instrument.

Parameters

  • data_dates – Input date or list of dates for which the curves are needed.

  • data_point – Input data point (optional).

Returns

pandas Series.

property available_data_points

Available data points

available_data_providers(entitled_only=True) → Optional[List[str]]

Available data providers for this object. Bool to return entitled providers only

property cache_name: str

Cache name of this object.

property class_name

Class name of this object.

property class_short_name

Short name of the object class.

clear_cached_data()

Clear all the cached data of the object.

clone_object(params=None)

Return a clone of the object with amended parameters.

Parameters

params – Optional dictionary of parameters to override.

Returns

New object.

compute_dependencies(root_dependency: Optional[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency] = None)

Compute these dependencies - triggers MDS requests

static convert_dtypes(clz)

Class decorator to convert classes’ BaseType into variable annotations (PEP-526), and to generate __aliases__ based on BaseType.db_name when required.

data_dict()

Return the object attributes in a dict.

property data_source: str

Field used when retrieving history.

property default_data_point

Default data point

dependencies(input_dependency: Optional[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency] = None, valuation_currency: Optional[str] = None, use_start: bool = True) → list[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency]

Returns a list of Dependency

Parameters

  • input_dependency – A Dependency object representing the root of the dependency tree to be returned.

  • valuation_currency – If supplied, include the dependencies required to output the data in this currency.

  • use_start – If False, return only dependencies required to calculate an earliest start date - self.start_date will be None in this case.

Returns

List of Dependency objects representing the current level in the dependency tree.

property dependency_type

Should return GraphNodeType. Return None to autodetect based on result of dependencies()

discount_curves(data_dates, data_point=None)

Discount curves for the instrument.

Parameters

  • data_dates – Input date or list of dates for which the curves are needed.

  • data_point – Input data point (optional).

Returns

pandas Series.

property env: sigtech.framework.config.config.ConfiguredEnvironment

Return the configured environment.

env_date_change(old_env_dt: datetime.datetime, new_env_dt: datetime.datetime, live_data_update=None)

Routine called after the environment date is changed.

Parameters

  • old_env_dt – Old datetime (tz aware).

  • new_env_dt – New datetime (tz aware).

  • live_data_update – Live streaming data associated with the environment date change.

exchange() → Any

Exchange object where options are traded.

finalize_for_comparison()

Method to call to ensure all data dict values are finalized prior to doing object comparisons.

classmethod from_currency(currency)

Return a group object from a currency ticker.

Parameters

currency – Currency ticker.

Returns

Group object.

classmethod from_dictionary(dct: dict[str, Any], cache: bool = True, identifier: Optional[sigtech.framework.infra.data_adapter.identifier.Identifier] = None, env: Optional[sigtech.framework.config.config.ConfiguredEnvironment] = None, **kwargs)

Factory method to create object using data dictionary

get_atm_vol(expiry: str, swap_tenor: str, start_date: datetime.date, end_date: Optional[datetime.date] = None, data_point=None)

Get rolling daily atm normal volatility for the expiry x swap_tenor swaptions.

Parameters

  • expiry – Swaption expiry string, e.g. '5Y' or '1M'.

  • swap_tenor – Underlying swap tenor, e.g. '5Y'.

  • start_date – Requested series start date

  • end_date – Requested series end date. asof_date used if omitted (optional).

  • data_point – Data point for the vol surface (optional).

Returns

pd.Series of daily vols

classmethod get_group(currency: str)

Create on the fly SWAPTION GROUP for given currency

Parameters

currency – e.g. ‘EUR’ or ‘USD’

Returns

classmethod get_names(sort_by_group: Optional[bool] = False, include_db: Optional[bool] = True, include_local: Optional[bool] = True, include_children: Optional[bool] = False, ignore_unmapped: Optional[bool] = True) → list[str]

Return an ordered list of object names associated with the class.

Parameters

  • sort_by_group – If set, the list is first ordered by sector/group, if applies, e.g. commodity or index futures (default is False).

  • include_db – If set, include objects available from the database (default is True).

  • include_local – If set, include objects available in the local environment (default is True).

  • include_children – If set, include objects available from child classes (default is False).

  • ignore_unmapped – If set, ignore errors due to unmapped database objects (default is True).

Returns

List of object names.

get_option_dependencies(start_date: datetime.date, maturity: Union[datetime.date, str], data_points: Optional[list[sigtech.framework.infra.data_adapter.common.DataPoint]] = None, **kwargs) → list[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency]

Additional Dependencies at the Swaption level - there aren’t any

get_swaption(option_type: str, strike: Optional[Union[float, str]], start_date: datetime.date, expiry: Union[datetime.date, str], swap_tenor: str, forward_premium: Optional[Union[float, bool]] = None, end_date: Optional[datetime.date] = None, history_start: Optional[datetime.date] = None)

Gets the swaption for a given type of option, strike and expity/tenor

Parameters

  • option_type – 'Payer' or 'Receiver'

  • strike – Strike of swaption. See Swaption for format details.

  • start_date – Start date of the history (also used for expiry offset if tenor given)

  • expiry – Maturity date of the option or expiry tenor (e.g. '3M')

  • swap_tenor – Tenor of the underlying swap (e.g. '5Y')

  • forward_premium – Optional - in case of forward (rather than spot) premium - either forward premium value, or True to imply it from the swaption value (i.e. start_date 0 npv)

  • end_date – Date when the option position is closed (optional, used purely for calculation optimisation).

  • history_start – Optional - date on which history should start, in case it’s needed before the start_date (e.g. for strategy sizing, or valuing if start_date is a non-business day).

Returns

get_vol_surface()

Object referenced by the vol surface name of the group.

get_vol_surface_series(data_dates, data_point=None)

Vol surface timeseries.

Parameters

  • data_dates – List of dates.

  • data_point – Data point (optional).

Returns

Vol surface timeseries.

property holidays: str

List of holiday calendars for this instrument.

property identifier: sigtech.framework.infra.data_adapter.identifier.Identifier

Return the object identifier.

info() → dict

Return a dictionary with useful object information.

property input_parameters

Values of initial input parameters entered when creating the instance.

property internal_id

Ticker - i.e. part of name determining content of the class. For types with saved reference data - ticker will be self._ticker. For software types - ticker should be calculated.

property is_unmapped

Check if the object is not mapped.

property live_supported: bool

Flag for live supported objects.

property name

Primary name by which the FrameworkObject is identified. If reference information (or e.g. corresponding time series) are stored in the DB, then this name will be used.

print_dependencies(root_dependency: Optional[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency] = None, resolve_future_dependencies: bool = True, fields: Optional[list] = None)

Pretty print dependency tree :param root_dependency: starting dependency of the tree. :param resolve_future_dependencies: resolve future dependencies before printing. If ‘false’ nothing get printed. :param fields: additional fields to extract from dependencies object. Default fields are product_type, currency, frequency and data_source. To get the list of available fields for an object you can use the data_dict() method.

property product_type

Return the product_type property of this object.

property publication_delay: str

Publication delay of data for this group.

query_instrument_names() → list[str]

Generic doc store query to retrieve names of objects meeting filter criteria. :return: List of object names meeting filter criteria.

query_instruments() → list[sigtech.framework.internal.infra.objects.core.framework_object.FrameworkObject]

Generic doc store query to retrieve objects meeting filter criteria. :return: List of objects meeting filter criteria

property sector

Sector used on BBG, or the class ID for SIG instruments.

session_data()

Returns the raw Copp-Clarke trading sessions data for this group

static sort_key_static(name)

Convert a name to the sort key as of Portfolio Presentation Guidelines for performance reasons.

Parameters

name – Input name.

Returns

Tuple (sort key, length of sort key, input name).

textual_representation()

Return a printable representation of this object.

validate()

Validation routine adding checks that will be run on object creation.

property valuation_time

Valuation time for the instrument group Included so we can supply this to TradingManager.data_point_from_time

property valuation_tzinfo

Valuation time zone for the instrument group Included so we can supply this to TradingManager.data_point_from_time

currency: str
exchange_code: Optional[str]
cash_settled: Optional[bool]
data_source_all: Optional[list[str]]
instrument_id: Optional[int]