Real Option Pricing using Quantum Computers

TL;DR

This paper introduces a novel quantum algorithm for option pricing that combines a new encoding protocol with an improved amplitude estimation technique, demonstrating retained speedups over standard methods through emulation.

Contribution

It proposes a new quantum encoding and amplitude estimation approach for derivatives pricing, enhancing the existing QAMC framework.

Findings

Retains speedups compared to standard QAMC

Uses a new direct encoding protocol

Employs a modified amplitude estimation algorithm

Abstract

In this work we present an alternative methodology to the standard Quantum Accelerated Monte Carlo (QAMC) applied to derivatives pricing. Our pipeline benefits from the combination of a new encoding protocol, referred to as the direct encoding, and a amplitude estimation algorithm, the modified Real Quantum Amplitude Estimation (mRQAE) algorithm. On the one hand, the direct encoding prepares a quantum state which contains the information about the sign of the expected payoff. On the other hand, the mRQAE is able to read all the information contained in the quantum state. Although the procedure we describe is different from the standard one, the main building blocks are almost the same. Thus, all the extensive research that has been performed is still applicable. Moreover, we experimentally compare the performance of the proposed methodology against the standard QAMC employing a quantum emulator and show that we retain the speedups.