*Last updated: 2023-03-16.*
# tf_quant_finance.rates.analytics.swap.equity_swap_price
View source
Computes prices of a batch of equity swaps.
```python
tf_quant_finance.rates.analytics.swap.equity_swap_price(
rate_leg_coupon_rates, equity_leg_forward_prices, equity_leg_spots,
rate_leg_notional, equity_leg_notional, rate_leg_daycount_fractions,
rate_leg_discount_factors, equity_leg_discount_factors, equity_dividends=None,
is_equity_receiver=None, dtype=None, name=None
)
```
The swap consists of an equity and interest rate legs.
#### Example
```python
rate_leg_coupon_rates = [[0.1, 0.2, 0.05], [0.1, 0.05, 0.2]]
# Two cashflows of 4 and 3 payments, respectively
forward_prices = [[110, 120, 140, 150], [210, 220, 240, 0]]
spots = [100, 200]
notional = 1000
pay_leg_daycount_fractions = 0.5
rate_leg_daycount_fractions = [[0.5, 0.5, 0.5], [0.4, 0.5, 0.6]]
rate_leg_discount_factors = [[0.95, 0.9, 0.85], [0.98, 0.92, 0.88]]
equity_leg_discount_factors = [[0.95, 0.9, 0.85, 0.8],
[0.98, 0.92, 0.88, 0.0]]
equity_swap_price(
rate_leg_coupon_rates=rate_leg_coupon_rates,
equity_leg_forward_prices=forward_prices,
equity_leg_spots=spots,
rate_leg_notional=notional,
equity_leg_notional=notional,
rate_leg_daycount_fractions=rate_leg_daycount_fractions,
rate_leg_discount_factors=rate_leg_discount_factors,
equity_leg_discount_factors=equity_leg_discount_factors,
is_equity_receiver=[True, False],
dtype=tf.float64)
# Expected: [216.87770563, -5.00952381]
forward_rates(df_start_dates, df_end_dates, daycount_fractions,
dtype=tf.float64)
```
#### Args:
* `rate_leg_coupon_rates`: A real `Tensor` of shape
`batch_shape + [num_rate_cashflows]`, where `num_rate_cashflows` is the
number of cashflows for each batch element. Coupon rates for the
interest rate leg.
* `equity_leg_forward_prices`: A `Tensor` of the same `dtype` as
`rate_leg_coupon_rates` and of shape
`batch_shape + [num_equity_cashflows]`, where `num_equity_cashflows` is
the number of cashflows for each batch element. Equity leg forward
prices.
* `equity_leg_spots`: A `Tensor` of the same `dtype` as
`equity_leg_forward_prices` and of shape compatible with `batch_shape`.
Spot prices for each batch element of the equity leg.
* `rate_leg_notional`: A `Tensor` of the same `dtype` as `rate_leg_coupon_rates`
and of compatible shape. Notional amount for each cashflow.
* `equity_leg_notional`: A `Tensor` of the same `dtype` as
`equity_leg_forward_prices` and of compatible shape. Notional amount for
each cashflow.
* `rate_leg_daycount_fractions`: A `Tensor` of the same `dtype` as
`rate_leg_coupon_rates` and of compatible shape. Year fractions for the
coupon accrual.
* `rate_leg_discount_factors`: A `Tensor` of the same `dtype` as
`rate_leg_coupon_rates` and of compatible shape. Discount factors for each
cashflow of the rate leg.
* `equity_leg_discount_factors`: A `Tensor` of the same `dtype` as
`equity_leg_forward_prices` and of compatible shape. Discount factors for
each cashflow of the equity leg.
* `equity_dividends`: A `Tensor` of the same `dtype` as
`equity_leg_forward_prices` and of compatible shape. Dividends paid at the
leg reset times.
Default value: None which maps to zero dividend.
* `is_equity_receiver`: A boolean `Tensor` of shape compatible with
`batch_shape`. Indicates whether the swap holder is equity holder or
receiver.
Default value: None which means that all swaps are equity reiver swaps.
* `dtype`: `tf.Dtype`. If supplied the dtype for the input and output `Tensor`s.
Default value: None which maps to the default dtype inferred from
`rate_leg_coupon_rates`.
* `name`: Python str. The name to give to the ops created by this function.
Default value: None which maps to 'equity_swap_price'.
#### Returns:
A `Tensor` of the same `dtype` as `rate_leg_coupon_rates` and of shape
`batch_shape`. Present values of the equity swaps.