NDF#

class rateslib.instruments.NDF(settlement, pair, *, currency=NoInput.blank, fx_rate=NoInput.blank, notional=NoInput.blank, leg2_notional=NoInput.blank, eval_date=NoInput.blank, modifier=NoInput.blank, eom=NoInput.blank, fx_fixings=NoInput.blank, leg2_fx_fixings=NoInput.blank, reversed=NoInput.blank, leg2_reversed=NoInput.blank, curves=NoInput.blank, spec=NoInput.blank)#

Bases: _BaseInstrument

A non-deliverable FX forward (NDF), composing two CustomLeg of individual Cashflow.

Examples

In [1]: ndf = NDF(dt(2026, 1, 5), FXIndex("usdbrl", "fed", 2), fx_rate=5.5)

In [2]: ndf.cashflows()
Out[2]: 
            Type  Ccy    Payment   Notional    DF   Cashflow   NPV  FX Rate Base Ccy NPV Ccy Collateral FX Fixing FX Fix Date Reference Ccy
leg1 0  Cashflow  USD 2026-01-05 -1000000.0  None  1000000.0  None      1.0      USD    None       None       NaN         NaT           NaN
leg2 0  Cashflow  USD 2026-01-05  5500000.0  None        NaN  None      1.0      USD    None       None      None  2025-12-31           BRL

Pricing

The methods of an NDF require an FXForwards object for fx .

They also require a disc curve, which is an appropriate curve to discount the cashflows of the deliverable settlement currency. The following input formats are allowed:

curves = disc_curve | [disc_curve]  # one curve
curves = [None, disc_curve, None, disc_curve]  # four curves
curves = {  # dict form is explicit
    "disc_curve": disc_curve,
    "leg2_disc_curve": disc_curve,
}

Parameters:

. –

Note

The following are settlement parameters.
settlement (datetime, str, required) – The date of settlement for the currency pair and payment date.
pair (FXIndex, str, required) – The FXIndex containing the FX pair implying the reference currencies and notional of leg1 and leg2 respectively.
currency (str, optional (set as LHS currency in pair)) – The physical settlement currency of each leg. If not a currency in pair then each leg will be non-deliverable (3-digit code).
notional (float, optional) – The notional of leg1 expressed in units of LHS currency of pair. This can be derived from fx_rate and leg2_notional.
leg2_notional (float, optional) – The notional of leg2 expressed in units of RHS currency of pair. This can be derived from fx_rate and notional.
fx_rate (float, optional) –
The transational FX rate of pair. This can be derived from notional and leg2_notional.

Note

The following are scheduling parameters required only if settlement given as string tenor.
eval_date (datetime, optional) – Today’s date from which spot and other dates may be determined.
modifier (Adjuster, str, optional) – The date adjuster for determining tenor dates under the convention for pair.
eom (bool, optional) –
Whether tenors under pair adopt EOM convention or not.

Note

The following are FX fixing parameters defining the settlement of the transaction.
fx_fixings (float, Dual, Dual2, Variable, Series, str, optional) – The value of the FXFixing for settlement of leg1 if that leg is non-deliverable. If a scalar is used directly. If a string identifier will link to the central fixings object and data loader.
reversed (bool, optional (set as False)) – Only used by a 3-currency NDF. Standard direction of the pair is ‘settlement:reference’, unless reversed is True, in which case ‘reference:settlement’ is used.
leg2_fx_fixings (float, Dual, Dual2, Variable, Series, str, optional) – The value of the FXFixing for settlement of leg2 if that leg is non-deliverable. If a scalar is used directly. If a string identifier will link to the central fixings object and data loader.
leg2_reversed (bool, optional (set as False)) –
Only used by a 3-currency NDF. Standard direction of the pair is ‘settlement:reference’, unless reversed is True, in which case ‘reference:settlement’ is used.

Note

The following are meta parameters.
curves (_BaseCurve, str, dict, _Curves, Sequence, optional) – Pricing objects passed directly to the Instrument’s methods’ curves argument. See Pricing.
spec (str, optional) – A collective group of parameters. See default argument specifications.

Notes

NDFs in rateslib replicate an FXForward whose cashflows are paid out netted in a single settlement currency. Two types are allowed:

A two currency NDF where one Leg is directly deliverable in its own currency and the other Leg is non-deliverable.
A three currency NDF when both Legs with cashflow currencies of pair are non-deliverable into a third currency.

In [3]: fixings.add("WMR_10AM_TY0_USDINR", Series(index=[dt(2026, 2, 16)], data=[92.5]))

In [4]: fixings.add("WMR_10AM_TY0_USDSGD", Series(index=[dt(2026, 2, 16)], data=[1.290]))

The required parameters of a two currency NDF are as follows;

A pair which defines the currency pair and implicitly determines the reference currency. The settlement currency for both Legs is inferred as the LHS, although this can be manually set by using the currency argument.
A notional or leg2_notional. Each notional should be expressed in the reference currency for that Leg. If both are given that defines the transactional fx_rate. If an fx_rate is given that will imply the missing notional.
fx_fixings or leg2_fx_fixings. FX fixings can only be added to the non-deliverable Leg.

This example is a USDINR NDF in 500mm INR payment with an initially agreed FX rate of USDINR 92.0

In [5]: ndf = NDF(
   ...:     settlement=dt(2026, 2, 18),
   ...:     currency="usd",              #  <-  USD settlement currency
   ...:     pair="usdinr",               #  <-  INR reference currency implied
   ...:     leg2_notional=500e6,         #  <-  Leg2 is based on the reference currency (INR)
   ...:     leg2_fx_fixings="WMR_10AM_TY0",
   ...:     fx_rate=92.0,                #  <-  Leg1 notional is implied as -5.43mm
   ...: )
   ...: 

In [6]: ndf.cashflows()
Out[6]: 
            Type  Ccy    Payment      Notional    DF      Cashflow   NPV  FX Rate Base Ccy NPV Ccy Collateral  FX Fixing FX Fix Date Reference Ccy
leg1 0  Cashflow  USD 2026-02-18  5.434783e+06  None -5.434783e+06  None      1.0      USD    None       None        NaN         NaT           NaN
leg2 0  Cashflow  USD 2026-02-18 -5.000000e+08  None  5.405405e+06  None      1.0      USD    None       None       92.5  2026-02-16           INR

The required parameters of a three currency NDXCS are as follows;

A currency which defines the settlement currency on both legs.
A pair which defines the currency pair and implicitly determines the reference currency 1 and reference currency 2.
A notional or leg2_notional. Each notional should be expressed in the reference currency for that Leg. If both are given that defines the transactional fx_rate. If an fx_rate is given that will imply the missing notional.
fx_fixings and leg2_fx_fixings. Both legs are non-deliverable so FX fixings may be provided to both Leg.

This example is a SGDINR NDF in 500mm INR payment with an initially agreed FX rate of SGDINR 70.1

In [7]: ndf = NDF(
   ...:     settlement=dt(2026, 2, 18),
   ...:     currency="usd",               #  <-  USD settlement currency
   ...:     pair=FXIndex("SGDINR", "mum", 2),  #  <-  SGD + INR reference currencies
   ...:     leg2_notional=500e6,          #  <-  INR notional
   ...:     fx_rate=70.1,                 #  <-  Transaction rate of pair
   ...:     fx_fixings="WMR_10AM_TY0",       #  <-  Data series tag for FXFixings on Leg1
   ...:     leg2_fx_fixings="WMR_10AM_TY0",  #  <-  Data series tag for FXFixings on Leg2
   ...: )
   ...: 

In [8]: ndf.cashflows()
Out[8]: 
            Type  Ccy    Payment      Notional    DF      Cashflow   NPV  FX Rate Base Ccy NPV Ccy Collateral  FX Fixing FX Fix Date Reference Ccy
leg1 0  Cashflow  USD 2026-02-18  7.132668e+06  None -5.529200e+06  None      1.0      USD    None       None       1.29  2026-02-16           SGD
leg2 0  Cashflow  USD 2026-02-18 -5.000000e+08  None  5.405405e+06  None      1.0      USD    None       None      92.50  2026-02-16           INR

Attributes Summary

`kwargs`	The `_KWArgs` container for the Instrument.
`leg1`	The `CustomLeg` of the Instrument.
`leg2`	The `CustomLeg` of the Instrument.
`legs`	A list of the Legs of the Instrument.
`rate_scalar`	A scaling quantity associated with the `Solver` risk calculations.
`settlement_params`	The default `_SettlementParams` of the Instrument.

Methods Summary

`analytic_delta`(*[, curves, solver, fx, vol, ...])	Calculate the analytic rate delta of a Leg of the Instrument.
`cashflows`(*[, curves, solver, fx, vol, ...])	Return aggregated cashflow data for the Instrument.
`cashflows_table`(*[, curves, solver, fx, ...])	Aggregate the values derived from a `cashflows()`, grouped by date, settlement currency and collateral.
`delta`(*[, curves, solver, fx, vol, base, ...])	Calculate delta risk of an Instrument against the calibrating instruments in a `Solver`.
`exo_delta`(*[, curves, solver, fx, vol, ...])	Calculate delta risk of an Instrument against some exogenous user created Variables, via a `Solver`.
`gamma`(*[, curves, solver, fx, vol, base, ...])	Calculate cross-gamma risk of an Instrument against the calibrating instruments of a `Solver`.
`local_analytic_rate_fixings`(*[, curves, ...])	Calculate the sensitivity to rate fixings of the Instrument, expressed in local settlement currency per basis point.
`local_fixings`(identifiers[, scalars, ...])	Calculate the sensitivity to fixings of the Instrument, expressed in local settlement currency.
`npv`(*[, curves, solver, fx, vol, base, ...])	Calculate the NPV of the Instrument converted to any other base accounting currency.
`rate`(*[, curves, solver, fx, vol, base, ...])	Calculate some pricing rate metric for the Instrument.
`reset_fixings`([state])	Resets any fixings values of the Instrument derived using the given data state.
`spread`(*[, curves, solver, fx, vol, base, ...])	Calculate some pricing spread metric for the Instrument.

Attributes Documentation

kwargs#: The _KWArgs container for the Instrument.

leg1#: The CustomLeg of the Instrument.

leg2#: The CustomLeg of the Instrument.

legs#: A list of the Legs of the Instrument.

rate_scalar#: A scaling quantity associated with the Solver risk calculations.

settlement_params#

The default _SettlementParams of the Instrument.

This is used to define a base currency when one is not specified.

Methods Documentation

analytic_delta(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, local=False, settlement=NoInput.blank, forward=NoInput.blank, leg=1)#

Calculate the analytic rate delta of a Leg of the Instrument.

Examples

In [9]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.75})

In [10]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", fixed_rate=1.0, curves=[curve])

In [11]: irs.analytic_delta()
Out[11]: 287.14750127899316

In [12]: irs.analytic_delta(local=True)
Out[12]: {'usd': 287.14750127899316}

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
local (bool, optional (set as False)) – An override flag to return a dict of NPV values indexed by string currency.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.
leg (int, optional (set as 1)) – The Leg over which to calculate the analytic rate delta.

Return type:

float, Dual, Dual2, Variable or dict of such indexed by string currency.

cashflows(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank)#

Return aggregated cashflow data for the Instrument.

Warning

This method is a convenience method to provide a visual representation of all associated calculation data. Calling this method to extract certain values should be avoided. It is more efficient to source relevant parameters or calculations from object attributes or other methods directly.

Examples

In [1]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", fixed_rate=1.0)

In [2]: irs.cashflows()
Out[2]: 
               Type  Ccy    Payment   Notional   Period Convention       DCF  Acc Start    Acc End    DF      Cashflow   NPV  FX Rate Base Ccy NPV Ccy Collateral  Rate  Spread
leg1 0  FixedPeriod  USD 2001-01-04  1000000.0  Regular     Act360  1.013889 2000-01-03 2001-01-02  None -10138.888889  None      1.0      USD    None       None   1.0     NaN
     1  FixedPeriod  USD 2002-01-04  1000000.0  Regular     Act360  1.013889 2001-01-02 2002-01-02  None -10138.888889  None      1.0      USD    None       None   1.0     NaN
     2  FixedPeriod  USD 2003-01-06  1000000.0  Regular     Act360  1.013889 2002-01-02 2003-01-02  None -10138.888889  None      1.0      USD    None       None   1.0     NaN
leg2 0  FloatPeriod  USD 2001-01-04 -1000000.0  Regular     Act360  1.013889 2000-01-03 2001-01-02  None           NaN  None      1.0      USD    None       None   NaN     0.0
     1  FloatPeriod  USD 2002-01-04 -1000000.0  Regular     Act360  1.013889 2001-01-02 2002-01-02  None           NaN  None      1.0      USD    None       None   NaN     0.0
     2  FloatPeriod  USD 2003-01-06 -1000000.0  Regular     Act360  1.013889 2002-01-02 2003-01-02  None           NaN  None      1.0      USD    None       None   NaN     0.0

Providing relevant pricing objects will ensure all data that can be calculated is returned.

In [3]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.75})

In [4]: irs.cashflows(curves=[curve])
Out[4]: 
               Type  Ccy    Payment   Notional   Period Convention       DCF  Acc Start    Acc End        DF      Cashflow           NPV  FX Rate Base Ccy       NPV Ccy Collateral      Rate  Spread
leg1 0  FixedPeriod  USD 2001-01-04  1000000.0  Regular     Act360  1.013889 2000-01-03 2001-01-02  0.971359 -10138.888889  -9848.496702      1.0      USD  -9848.496702       None  1.000000     NaN
     1  FixedPeriod  USD 2002-01-04  1000000.0  Regular     Act360  1.013889 2001-01-02 2002-01-02  0.943835 -10138.888889  -9569.435745      1.0      USD  -9569.435745       None  1.000000     NaN
     2  FixedPeriod  USD 2003-01-06  1000000.0  Regular     Act360  1.013889 2002-01-02 2003-01-02  0.916946 -10138.888889  -9296.817681      1.0      USD  -9296.817681       None  1.000000     NaN
leg2 0  FloatPeriod  USD 2001-01-04 -1000000.0  Regular     Act360  1.013889 2000-01-03 2001-01-02  0.971359  29161.694029  28326.461668      1.0      USD  28326.461668       None  2.876222     0.0
     1  FloatPeriod  USD 2002-01-04 -1000000.0  Regular     Act360  1.013889 2001-01-02 2002-01-02  0.943835  29161.694029  27523.820438      1.0      USD  27523.820438       None  2.876222     0.0
     2  FloatPeriod  USD 2003-01-06 -1000000.0  Regular     Act360  1.013889 2002-01-02 2003-01-02  0.916946  29161.694029  26739.710399      1.0      USD  26739.710399       None  2.876222     0.0

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

DataFrame

cashflows_table(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank)#

Aggregate the values derived from a cashflows(), grouped by date, settlement currency and collateral.

Examples

In [5]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", fixed_rate=1.0)

In [6]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.75})

In [7]: irs.cashflows_table(curves=[curve])
Out[7]: 
local_ccy               USD
collateral_ccy          NaN
payment                    
2001-01-04      19022.80514
2002-01-04      19022.80514
2003-01-06      19022.80514

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
local (bool, optional (set as False)) – An override flag to return a dict of NPV values indexed by string currency.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

DataFrame

delta(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank)#

Calculate delta risk of an Instrument against the calibrating instruments in a Solver.

Examples

In [8]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2002, 1, 1): 0.85, dt(2010, 1, 1): 0.75})

In [9]: solver = Solver(
   ...:     curves=[curve],
   ...:     instruments=[
   ...:         IRS(dt(2000, 1, 1), "2Y", spec="usd_irs", curves=[curve]),
   ...:         IRS(dt(2000, 1, 1), "5Y", spec="usd_irs", curves=[curve]),
   ...:     ],
   ...:     s=[2.0, 2.25],
   ...:     instrument_labels=["2Y", "5Y"],
   ...:     id="US_RATES"
   ...: )
   ...: 
SUCCESS: `func_tol` reached after 6 iterations (levenberg_marquardt), `f_val`: 8.499591036903249e-16, `time`: 0.0030s

In [10]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", curves=[curve])

In [11]: irs.delta(solver=solver)
Out[11]: 
local_ccy                          usd
display_ccy                        usd
type        solver   label            
instruments US_RATES 2Y     129.580448
                     5Y     162.173287

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, required) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

DataFrame

Notes

Delta measures the sensitivity of the PV to a change in any of the calibrating instruments of the given Solver. Values are returned according to the rate_scalar quantity at an Instrument level and according to the metric used to derive the rate() method of each Instrument.

exo_delta(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank, vars, vars_scalar=NoInput.blank, vars_labels=NoInput.blank)#

Calculate delta risk of an Instrument against some exogenous user created Variables, via a Solver.

See What are exogenous variables? in the cookbook.

Examples

This example calculates the risk of the fixed rate increasing by 1bp and the notional increasing by 1mm. Mathematically this should be equivalent to the npv and the analytic delta (although the calculation is based on AD and is completely independent of the solver).

In [12]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2002, 1, 1): 0.85, dt(2010, 1, 1): 0.75})

In [13]: solver = Solver(
   ....:     curves=[curve],
   ....:     instruments=[
   ....:         IRS(dt(2000, 1, 1), "2Y", spec="usd_irs", curves=[curve]),
   ....:         IRS(dt(2000, 1, 1), "5Y", spec="usd_irs", curves=[curve]),
   ....:     ],
   ....:     s=[2.0, 2.25],
   ....:     instrument_labels=["2Y", "5Y"],
   ....:     id="US_RATES"
   ....: )
   ....: 
SUCCESS: `func_tol` reached after 6 iterations (levenberg_marquardt), `f_val`: 8.499591036903249e-16, `time`: 0.0029s

In [14]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", fixed_rate=Variable(3.0, ["R"]), notional=Variable(1e6, ["N"]), curves=[curve])

In [15]: irs.exo_delta(solver=solver, vars=["R", "N"], vars_scalar=[1e-2, 1e6])
Out[15]: 
local_ccy                          usd
display_ccy                        usd
type      solver   label              
exogenous US_RATES R       -291.752073
                   N     -25123.690181

In [16]: irs.analytic_delta()
Out[16]: <Dual: 291.752073, (N, 916ad0, 916ad1, ...), [0.0, 49.2, 239.9, ...]>

In [17]: irs.npv()
Out[17]: <Dual: -25123.690181, (N, R, 916ad0, ...), [-0.0, -29175.2, 982218.9, ...]>

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, required) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.
vars (list[str], required) – The variable tags which to determine sensitivities for.
vars_scalar (list[float], optional) – Scaling factors for each variable, for example converting rates to basis point etc. Defaults to ones.
vars_labels (list[str], optional) – Alternative names to relabel variables in DataFrames.

Return type:

DataFrame

gamma(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank)#

Calculate cross-gamma risk of an Instrument against the calibrating instruments of a Solver.

Examples

In [18]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2002, 1, 1): 0.85, dt(2010, 1, 1): 0.75})

In [19]: solver = Solver(
   ....:     curves=[curve],
   ....:     instruments=[
   ....:         IRS(dt(2000, 1, 1), "2Y", spec="usd_irs", curves=[curve]),
   ....:         IRS(dt(2000, 1, 1), "5Y", spec="usd_irs", curves=[curve]),
   ....:     ],
   ....:     s=[2.0, 2.25],
   ....:     instrument_labels=["2Y", "5Y"],
   ....:     id="US_RATES"
   ....: )
   ....: 
SUCCESS: `func_tol` reached after 6 iterations (levenberg_marquardt), `f_val`: 8.499591036903249e-16, `time`: 0.0030s

In [20]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", curves=[curve])

In [21]: irs.gamma(solver=solver)
Out[21]: 
type                                             instruments          
solver                                              US_RATES          
label                                                     2Y        5Y
local_ccy display_ccy type        solver   label                      
usd       usd         instruments US_RATES 2Y      -0.029442 -0.038104
                                           5Y      -0.038104 -0.010190

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, required) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

DataFrame

Notes

Gamma measures the second order cross-sensitivity of the PV to a change in any of the calibrating instruments of the given Solver. Values are returned according to the rate_scalar quantity at an Instrument level and according to the metric used to derive the rate() method of each Instrument.

local_analytic_rate_fixings(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank)#

Calculate the sensitivity to rate fixings of the Instrument, expressed in local settlement currency per basis point.

Examples

In [22]: curve1 = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.75}, id="Eur1mCurve")

In [23]: curve3 = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.70}, id="Eur3mCurve")

In [24]: irs = IRS(dt(2000, 1, 1), "20m", spec="eur_irs3", curves=[{"1m": curve1, "3m": curve3}, curve1])

In [25]: irs.local_analytic_rate_fixings()
Out[25]: 
identifier  Eur1mCurve Eur3mCurve
local_ccy          eur        eur
display_ccy        eur        eur
frequency           1M         3M
obs_dates                        
1999-12-30     8.81934   7.215824
2000-02-28         NaN  25.251470
2000-05-30         NaN  25.069179
2000-08-30         NaN  24.619619
2000-11-29         NaN  24.177105
2001-02-27         NaN  24.535960
2001-05-30         NaN  24.884455

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

DataFrame

Notes

This analytic method will index the sensitivities with series identifier according to the Curve id which has forecast the fixing.

local_fixings(identifiers, scalars=NoInput.blank, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank)#

Calculate the sensitivity to fixings of the Instrument, expressed in local settlement currency.

Parameters:

identifiers (Sequence of tuple[str, Series], required) – These are the series string identifiers and the data values that will be used in each Series to determine the sensitivity against.
scalars (Sequence of floats, optional (each set as 1.0)) – A sequence of scalars to multiply the sensitivities by for each on of the identifiers.
curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

DataFrame

npv(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, local=False, settlement=NoInput.blank, forward=NoInput.blank)#

Calculate the NPV of the Instrument converted to any other base accounting currency.

Examples

In [1]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.75})

In [2]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", fixed_rate=1.0, curves=[curve])

In [3]: irs.npv()
Out[3]: 53875.24237805192

In [4]: irs.npv(local=True)
Out[4]: {'usd': 53875.24237805192}

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
local (bool, optional (set as False)) – An override flag to return a dict of NPV values indexed by string currency.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

float, Dual, Dual2, Variable or dict of such indexed by string currency.

Notes

If base is not given then this function will return the value obtained from determining the PV in local settlement currency.

If base is provided this then an FXForwards object may be required to perform conversions. An FXRates object is also allowed for this conversion although best practice does not recommend it due to possible settlement date conflicts.

rate(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank, metric=NoInput.blank)#

Calculate some pricing rate metric for the Instrument.

Examples

The default metric for an IRS is its fixed ‘rate’.

In [1]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.75})

In [2]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", curves=[curve], fixed_rate=2.0)

In [3]: irs.rate()       # <- `fixed_rate` on fixed leg to equate value with float leg
Out[3]: 2.87622187684324

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
local (bool, optional (set as False)) – An override flag to return a dict of NPV values indexed by string currency.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.
metric (str, optional) – The specific calculation to perform and the value to return. See Pricing on each Instrument for details of allowed inputs.

Return type:

float, Dual, Dual2, Variable

reset_fixings(state=NoInput.blank)#

Resets any fixings values of the Instrument derived using the given data state.

Parameters:: state (int, optional) – The state id of the data series that set the fixing. Only fixings determined by this data will be reset. If not given resets all fixings.
Return type:: None

spread(*, curves=NoInput.blank, solver=NoInput.blank, fx=NoInput.blank, vol=NoInput.blank, base=NoInput.blank, settlement=NoInput.blank, forward=NoInput.blank)#

Calculate some pricing spread metric for the Instrument.

This calculation may be an alias for rate() with a specific metric and is designated at an Instrument level.

Examples

The ‘spread’ on an IRS is the float leg spread to equate value with the fixed leg.

In [4]: curve = Curve({dt(2000, 1, 1): 1.0, dt(2010, 1, 1): 0.75})

In [5]: irs = IRS(dt(2000, 1, 1), "3Y", spec="usd_irs", curves=[curve], fixed_rate=2.0)

In [6]: irs.spread()       # <- `spread` on float leg to equate value with fixed leg
Out[6]: -87.62218768432399

Parameters:

curves (_Curves, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
solver (Solver, optional) – A Solver object containing Curve, Smile, Surface, or Cube mappings for pricing.
fx (FXForwards, optional) – The FXForwards object used for forecasting FX rates, if necessary.
vol (_Vol, optional) – Pricing objects. See Pricing on each Instrument for details of allowed inputs.
base (str, optional (set to settlement currency)) – The currency to convert the local settlement NPV to.
local (bool, optional (set as False)) – An override flag to return a dict of NPV values indexed by string currency.
settlement (datetime, optional) – The assumed settlement date of the PV determination. Used only to evaluate ex-dividend status.
forward (datetime, optional) – The future date to project the PV to using the disc_curve.

Return type:

float, Dual, Dual2, Variable

NDF#

This Page