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FXCross

FXCross#

class sigtech.framework.infra.analytics.fx.cross.FXCross

Class handling FX currency conversions.

Note

The over/under convention represents how much one under unit costs in terms of over units.

  • over is the over or quote currency. In EURUSD, the over currency would be USD.

  • under is the under or base currency. In EURUSD, the under currency would be EUR.

clear_cache()

Clear the object cache.

convert(values, from_ccy, to_ccy, data_point=None)

Convert a daily timeseries from the source currency to the target currency using the TradingManager default data point / close time.

Parameters:

  • values – Input timeseries with a date index (no time or timezone).

  • from_ccy – Source currency.

  • to_ccy – Target currency.

  • data_point – Data point (optional).

Returns:

pandas Series.

convert_at_d(value, d, from_ccy, to_ccy, fx_source='SNAP', field='MidPrice', data_point=None)

Convert the input value on date or datetime d from the source currency to the target currency.

Parameters:

  • value – Input value.

  • d – Reference date or datetime.

  • from_ccy – Source currency.

  • to_ccy – Target currency.

  • fx_source – FX source (default is 'SNAP').

  • field – Field (default is 'MidPrice').

  • data_point – Data point (optional).

Returns:

Converted value.

convert_at_dt(value, dt, from_ccy, to_ccy, fx_source='SNAP', field='MidPrice')

Convert the input value on time dt from the source currency to the target currency.

Parameters:

  • value – Input value.

  • dt – Reference datetime.

  • from_ccy – Source currency.

  • to_ccy – Target currency.

  • fx_source – FX source (default is 'SNAP').

  • field – Field (default is 'MidPrice').

Returns:

Converted value.

dependencies(over: str, under: str, time: ~typing.Optional[~datetime.time], tz: <module 'pytz.tzinfo' from '/github/home/.cache/pypoetry/virtualenvs/sigtech-framework-GMC81NYz-py3.11/lib/python3.11/site-packages/pytz/tzinfo.py'>, start_dt: ~datetime.datetime, end_dt: ~datetime.datetime) → list[sigtech.framework.internal.infra.mu.graph.registry.factory.Dependency]

Dependencies for an fx pair

static fx_pair_in_canonical_order(pair: str, check=True)

Return the FX pair in canonical order, e.g. 'jpyusd' -> 'USDJPY', 'eurusd' -> 'EURUSD'.

Parameters:

  • pair – FX pair in string format.

  • check – Flag to enable extra checks on the FX pair (length and case sensitive check) if set to True (default).

Returns:

str.

get_available_data_points(fx_source='SNAP')

Return the list of available data points.

Parameters:

fx_source – FX source (default is 'SNAP').

Returns:

list.

get_series(over, under, fx_source='SNAP', field=None, data_point=None, start_dt=None, end_dt=None)

Get a daily series of conversion values.

Parameters:

  • over – Over currency.

  • under – Under currency.

  • fx_source – FX source (default is 'SNAP').

  • field – Field (optional).

  • data_point – Data point (optional).

  • start_dt – start datetime, for use with intraday data_point only

  • end_dt – end datetime, for use with intraday data_point only

Returns:

pandas Series.

get_value(d, over, under, fx_source='SNAP', field='MidPrice', data_point=None)

Get an individual FX cross conversion value.

Parameters:

  • d – Reference date or datetime.

  • over – Over currency.

  • under – Under currency.

  • fx_source – FX source (default is 'SNAP').

  • field – Field (default is 'MidPrice').

  • data_point – Data point (optional).

Returns:

Converted value.

classmethod is_flipped(over, under)

Determine whether over/under needs to be flipped to be in line with market quoting conventions.

Parameters:

  • over – Over currency.

  • under – Under currency.

Returns:

bool.