tf_quant_finance.rates.analytics.cashflows.present_value

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Last updated: 2023-03-16.

tf_quant_finance.rates.analytics.cashflows.present_value#

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Computes present value of a stream of cashflows given discount factors.

tf_quant_finance.rates.analytics.cashflows.present_value(
    cashflows, discount_factors, dtype=None, name=None
)


  # 2 and 3 year bonds with 1000 face value and 4%, 6% semi-annual coupons.
  # Note that the first four entries in the cashflows are the cashflows of
  # the first bond (group=0) and the next six are the cashflows of the second
  # bond (group=1).
  cashflows = [[20, 20, 20, 1020, 0, 0],
               [30, 30, 30, 30, 30, 1030]]

  # Corresponding discount factors for the cashflows
  discount_factors = [[0.96, 0.93, 0.9, 0.87, 1.0, 1.0],
                      [0.97, 0.95, 0.93, 0.9, 0.88, 0.86]]

  present_values = present_value(
      cashflows, discount_factors, dtype=np.float64)
  # Expected: [943.2, 1024.7]

Args:#

  • cashflows: A real Tensor of shape batch_shape + [n]. The set of cashflows of underlyings. n is the number of cashflows per bond and batch_shape is the number of bonds. Bonds with different number of cashflows should be padded to a common number n.

  • discount_factors: A Tensor of the same dtype as cashflows and of compatible shape. The set of discount factors corresponding to the cashflows.

  • dtype: tf.Dtype. If supplied the dtype for the input and output Tensors. Default value: None which maps to the default dtype inferred from cashflows.

  • name: Python str. The name to give to the ops created by this function. Default value: None which maps to ‘present_value’.

Returns:#

Real Tensor of shape batch_shape. The present values of the cashflows.

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