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FixedIncomePricing#

class FixedIncomePricing(num_qubits, pca_matrix, initial_interests, cash_flow, rescaling_factor, bounds, uncertainty_model)[source]#

Bases: EstimationApplication

An estimation application for the fixed income pricing problem. evaluate the expected value of the total value \(V\) of the assets

\[V = \sum_{t=1}^T \frac{c_t}{(1+r_t)^t}.\]
[1]: Woerner, S., & Egger, D. J. (2018).

Quantum Risk Analysis. arXiv:1806.06893

Parameters:

  • num_qubits (List[int]) – A list specifying the number of qubits used to discretize the assets.

  • pca_matrix (ndarray) – The PCA matrix for the changes in the interest rates, \(\delta_r\).

  • initial_interests (List[int]) – The initial interest rates / offsets for the interest rates.

  • cash_flow (List[float]) – The cash flow time series.

  • rescaling_factor (float) – The scaling factor used in the Taylor approximation.

  • bounds (List[Tuple[float, float]]) – The list of the tuple of the bounds, (min, max), for return values the assets can attain.

  • attain. (The bounds for return values the assets can) –

  • uncertainty_model (QuantumCircuit) – A circuit for encoding a problem distribution

Methods

interpret(result)[source]#

Convert the calculation result of the problem (qiskit_algorithms.AmplitudeEstimatorResult) to the answer of the problem.

Parameters:

result (AmplitudeEstimatorResult) – The calculated result of the problem

Returns:

The estimation value after the post_processing.

Return type:

float

to_estimation_problem()[source]#

Convert a problem instance into a qiskit_algorithms.EstimationProblem

Returns:

The qiskit_algorithms.EstimationProblem created from the Fixed problem instance.

Return type:

EstimationProblem