IBORStubFixing#

class rateslib.data.fixings.IBORStubFixing(*, rate_series, accrual_start, accrual_end, value=NoInput.blank, identifier=NoInput.blank, date=NoInput.blank)#

Bases: _BaseFixing

A rate fixing value referencing an interpolated tenor-IBOR type calculation.

Parameters:

rate_series (FloatRateSeries) – The parameters associated with the floating rate index.
accrual_start (datetime) – The start accrual date for the period.
accrual_end (datetime) – The end accrual date for the period..
date (datetime, optional) – The date of relevance for the fixing, which is its publication date. This can be determined by a lag parameter of the rate_series measured from the accrual_start.
value (float, Dual, Dual2, Variable, optional) – The initial value for the fixing to adopt. Most commonly this is not given and it is determined from a timeseries of published FX rates.
identifier (str, optional) – The string name of the timeseries to be loaded by the Fixings object. This is a series identifier, e.g. “Euribor”, which will be extended to derive the full version, e.g. “Euribor_3m” based on available and necessary tenors.

Notes

An interpolated tenor-IBOR type calculation depends upon two tenors being determinable from which a rate can be linearly interpolated.

The rate_series has a tenors attribute which will be used in a first instance. If this is empty, i.e. unspecified, then the default tenors of [‘1W’, ‘1M’, ‘3M’, ‘6M’, ‘12M’] are used in place.

Examples

This fixing automatically identifies it must be interpolated between the available 3M and 6M tenors.

In [1]: fixings.add("EURIBOR_1M", Series(index=[dt(2000, 1, 3), dt(2000, 2, 4)], data=[1.651, 1.665]))

In [2]: fixings.add("EURIBOR_2M", Series(index=[dt(2000, 1, 3), dt(2000, 2, 4)], data=[2.651, 2.665]))

In [3]: fixings.add("EURIBOR_3M", Series(index=[dt(2000, 1, 3), dt(2000, 2, 4)], data=[3.651, 3.665]))

In [4]: fixings.add("EURIBOR_6M", Series(index=[dt(2000, 1, 3), dt(2000, 2, 4)], data=[4.651, 4.665]))

In [5]: ibor_fix = IBORStubFixing(
   ...:     accrual_start=dt(2000, 1, 5),
   ...:     accrual_end=dt(2000, 5, 17),
   ...:     identifier="Euribor",
   ...:     rate_series=FloatRateSeries(
   ...:         lag=2,
   ...:         modifier="MF",
   ...:         calendar="tgt",
   ...:         convention="act360",
   ...:         eom=False,
   ...:         tenors=["1M", "2M", "3M", "6M", "12M"],
   ...:     )
   ...: )
   ...: 

In [6]: ibor_fix.date
Out[6]: datetime.datetime(2000, 1, 3, 0, 0)

In [7]: ibor_fix.value
Out[7]: np.float64(4.1125384615384615)

This fixing can only be determined from a single tenor, which is quite distinct from the 12 day period length in this case. In practice this should be avoided.

In [8]: fixings.add("NIBOR_6M", Series(index=[dt(2000, 1, 3), dt(2000, 2, 4)], data=[4.651, 4.665]))

In [9]: ibor_fix = IBORStubFixing(
   ...:     accrual_start=dt(2000, 1, 5),
   ...:     accrual_end=dt(2000, 1, 17),
   ...:     identifier="Nibor",
   ...:     rate_series=FloatRateSeries(
   ...:         lag=2,
   ...:         modifier="MF",
   ...:         calendar="osl",
   ...:         convention="act360",
   ...:         eom=True,
   ...:         tenors=["6M"],
   ...:     )
   ...: )
   ...: 

In [10]: ibor_fix.date
Out[10]: datetime.datetime(2000, 1, 3, 0, 0)

In [11]: ibor_fix.value
Out[11]: np.float64(4.651)

In [12]: ibor_fix.fixing2
Out[12]: <NoInput.blank: 0>

Attributes Summary

`accrual_end`	The end accrual date for the defined accrual period.
`accrual_start`	The start accrual date for the defined accrual period.
`date`	The date of relevance for the fixing, which is its publication date.
`fixing1`	The shorter tenor `IBORFixing` making up part of the calculation.
`fixing2`	The longer tenor `IBORFixing` making up part of the calculation.
`identifier`	The string name of the timeseries to be loaded by the Fixings object.
`series`	The `FloatRateSeries` for defining the fixing.
`value`	The fixing value.
`weights`	Scalar multiplier to apply to each tenor fixing for the interpolation.

Methods Summary

reset([state])

Sets the value attribute to NoInput, which allows it to be redetermined from a timeseries.

Attributes Documentation

accrual_end#: The end accrual date for the defined accrual period.

accrual_start#: The start accrual date for the defined accrual period.

date#: The date of relevance for the fixing, which is its publication date.

fixing1#: The shorter tenor IBORFixing making up part of the calculation.

fixing2#: The longer tenor IBORFixing making up part of the calculation.

identifier#: The string name of the timeseries to be loaded by the Fixings object.

series#: The FloatRateSeries for defining the fixing.

value#

weights#: Scalar multiplier to apply to each tenor fixing for the interpolation.

Methods Documentation

reset(state=NoInput.blank)#

Sets the value attribute to NoInput, which allows it to be redetermined from a timeseries.

Examples

In [1]: fx_fixing1 = FXFixing(publication=dt(2021, 1, 1), fx_index="eurusd", identifier="A")

In [2]: fx_fixing2 = FXFixing(publication=dt(2021, 1, 1), fx_index="gbpusd", identifier="B")

In [3]: fixings.add("A_eurusd", Series(index=[dt(2021, 1, 1)], data=[1.1]), state=100)

In [4]: fixings.add("B_gbpusd", Series(index=[dt(2021, 1, 1)], data=[1.4]), state=200)

# data is populated from the available Series
In [5]: fx_fixing1.value
Out[5]: np.float64(1.1)

In [6]: fx_fixing2.value
Out[6]: np.float64(1.4)

# fixings are reset according to the data state
In [7]: fx_fixing1.reset(state=100)

In [8]: fx_fixing2.reset(state=100)

# only the private data for fixing1 is removed because of its link to the data state
In [9]: fx_fixing1._value
Out[9]: <NoInput.blank: 0>

In [10]: fx_fixing2._value
Out[10]: np.float64(1.4)

Parameters:: state (int, optional) – If given only fixings whose state matches this value will be reset. If no state is given then the value will be reset.
Return type:: None

IBORStubFixing#

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