Quantum Amplitude Estimation for Expected Loss Computation Under a Discretized Latent-factor Model

Author(s)	Arghya Ghosh, Dr. Ramesh Bhavisetti
Country	India
Abstract	We present a quantum algorithm for estimating the expected loss of a credit portfolio driven by a latent risk factor. The method discretizes a continuous latent variable, encodes its probability distribution into quantum amplitudes, embeds the loss function via controlled rotations on an ancilla qubit, and applies Grover-style amplitude amplification. The resulting state admits a two-subspace decomposition enabling estimation of the expected loss using Quantum Amplitude Estimation (QAE) or a maximum-likelihood estimator (MLE) based on Grover power measurements. The approach achieves a quadratic speedup over classical Monte Carlo methods.
Keywords	Quantum amplitude estimation, Grover operator, credit risk, expected loss, latent factor models.
Field	Engineering
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-01-22
DOI	https://doi.org/10.36948/ijfmr.2026.v08i01.67306

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