Quantum portfolio value forecasting

TL;DR

This paper introduces a quantum algorithm for estimating the long-term value of asset portfolios, demonstrating its feasibility on current quantum hardware with improved accuracy over classical methods.

Contribution

The paper presents a novel quantum algorithm using amplitude estimation for portfolio valuation, enabling practical pricing of multi-asset portfolios on existing quantum computers.

Findings

Successfully priced a five-asset portfolio on current quantum hardware.

Quantum estimates showed smaller statistical errors than classical benchmarks.

Demonstrated feasibility of quantum portfolio valuation with available technology.

Abstract

We present an algorithm which efficiently estimates the intrinsic long-term value of a portfolio of assets on a quantum computer. The method relies on quantum amplitude estimation to estimate the mean of a novel implementation of the Gordon-Shapiro formula. The choice of loading and readout algorithms makes it possible to price a five-asset portfolio on present day quantum computers, a feat which has not been realised using quantum computing to date. We compare results from two available trapped ion quantum computers. Our results are consistent with classical benchmarks, but result in smaller statistical errors for the same computational cost.