*Last updated: 2023-03-16.*
# tf_quant_finance.experimental.instruments.FixedCashflowStream
View source
Represents a batch of fixed stream of cashflows.
```python
tf_quant_finance.experimental.instruments.FixedCashflowStream(
start_date, end_date, coupon_spec, first_coupon_date=None,
penultimate_coupon_date=None, dtype=None, name=None
)
```
#### Example:
The following example illustrates the construction of an FixedCashflowStream
and calculating its present value.
```python
import numpy as np
import tensorflow as tf
import tf_quant_finance as tff
dates = tff.datetime
instruments = tff.experimental.instruments
rc = tff.experimental.instruments.rates_common
dtype = np.float64
start_date = dates.convert_to_date_tensor([(2020, 2, 2)])
maturity_date = dates.convert_to_date_tensor([(2023, 2, 2)])
valuation_date = dates.convert_to_date_tensor([(2020, 2, 2)])
period_6m = dates.periods.months(6)
fix_spec = instruments.FixedCouponSpecs(
coupon_frequency=period_6m, currency='usd',
notional=1.e6, coupon_rate=0.03134,
daycount_convention=rc.DayCountConvention.ACTUAL_365,
businessday_rule=dates.BusinessDayConvention.NONE)
cf_stream = instruments.FixedCashflowStream([start_date], [maturity_date],
[fix_spec], dtype=dtype)
curve_dates = valuation_date + dates.periods.years([1, 2, 3, 5, 7, 10, 30])
reference_curve = instruments.RateCurve(
curve_dates,
np.array([
0.02834814, 0.03077457, 0.03113739, 0.03130794, 0.03160892,
0.03213901, 0.03257991
], dtype=dtype),
dtype=dtype)
market = instruments.InterestRateMarket(
reference_curve=reference_curve, discount_curve=reference_curve)
price = cf_stream.price(valuation_date, market)
# Expected result: 89259.267853547
```
#### Args:
* `start_date`: A rank 1 `DateTensor` specifying the starting dates of the
accrual of the first coupon of the cashflow stream. The shape of the
input correspond to the numbercof streams being created.
* `end_date`: A rank 1 `DateTensor` specifying the end dates for accrual of
the last coupon in each cashflow stream. The shape of the input should
be the same as that of `start_date`.
* `coupon_spec`: A scalar or a list of `FixedCouponSpecs` specifying the
details of the coupon payment for the cashflow stream. If specified as
a list then the length of the list should be the same as the number of
streams being created and each coupon within the list must have the
same daycount_convention and businessday_rule. If specified as
a scalar, then the elements of the namedtuple must be of the same shape
as (or compatible to) the shape of `start_date`.
* `first_coupon_date`: An optional rank 1 `DateTensor` specifying the payment
dates of the first coupon of the cashflow stream. Use this input for
cashflows with irregular first coupon.
Default value: None which implies regular first coupon.
* `penultimate_coupon_date`: An optional rank 1 `DateTensor` specifying the
payment date of the penultimate (next to last) coupon of the cashflow
stream. Use this input for cashflows with irregular last coupon.
Default value: None which implies regular last coupon.
* `dtype`: `tf.Dtype`. If supplied the dtype for the real variables or ops
either supplied to the FixedCashflowStream object or created by the
object.
Default value: None which maps to the default dtype inferred by
TensorFlow.
* `name`: Python str. The name to give to the ops created by this class.
Default value: `None` which maps to 'fixed_cashflow_stream'.
#### Attributes:
* `contract_index`
* `daycount_fractions`
* `fixed_rate`
* `notional`
* `payment_dates`
## Methods
price
View source
```python
price(
valuation_date, market, model=None, pricing_context=None, name=None
)
```
Returns the present value of the stream on the valuation date.
#### Args:
* `valuation_date`: A scalar `DateTensor` specifying the date on which
valuation is being desired.
* `market`: A namedtuple of type `InterestRateMarket` which contains the
necessary information for pricing the cashflow stream.
* `model`: Reserved for future use.
* `pricing_context`: Additional context relevant for pricing.
* `name`: Python str. The name to give to the ops created by this function.
Default value: `None` which maps to 'price'.
#### Returns:
A Rank 1 `Tensor` of real type containing the modeled price of each stream
based on the input market data.