TY - EJOU
AU - Hu, Jian-Guo
AU - Wu, Shao-Yi
AU - Yang, Yi
AU - Zhu, Qin-Sheng
AU - Li, Xiao-Yu
AU - Yang, Shan
TI - Study on Quantum Finance Algorithm: Quantum Monte Carlo Algorithm based on European Option Pricing
T2 - Journal of Quantum Computing
PY - 2022
VL - 4
IS - 1
SN - 2579-0145
AB - As one of the major methods for the simulation of option pricing, Monte Carlo method assumes random fluctuations in the distribution of asset prices. Under certain uncertainties process, different evolution paths could be simulated so as to finally yield the expectation value of the asset price, which requires a lot of simulations to ensure the accuracy based on huge and expensive calculations. In order to solve the above computational problem, quantum Monte Carlo (QMC) has been established and applied in the relevant systems such as European call options. In this work, both MC and QM methods are adopted to simulate European call options. Based on the preparation of quantum states in QMC algorithm and the construction of quantum circuits by simulating a quantum hardware environment on a traditional computer, the amplitude estimation (AE) algorithm is found to play a secondary role in accelerating the pricing of European options. More importantly, the payoff function and the time required for the simulation in QMC method show some improvements than those in MC method.
KW - Monte carlo method (MC); option pricing; quantum monte carlo (QMC); amplitude estimation (AE); payoff function
DO - 10.32604/jqc.2022.027683