tf_quant_finance.rates.analytics.swap.equity_swap_price

Last updated: 2023-03-16.

tf_quant_finance.rates.analytics.swap.equity_swap_price#

View source

Computes prices of a batch of equity swaps.

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#

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 Tensors. 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.

Contents