Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Monte Carlo Simulation for Option Pricing with Multiple Assets

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322853,
        author={Qinwen  Deng and Hongying  Wu and Yang  Wu and Zhiqiang  Zhou},
        title={Monte Carlo Simulation for Option Pricing with Multiple Assets},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={multi-asset options monte carlo simulation normal distribution correlative coefficient},
        doi={10.4108/eai.17-6-2022.2322853}
    }
    
  • Qinwen Deng
    Hongying Wu
    Yang Wu
    Zhiqiang Zhou
    Year: 2022
    Monte Carlo Simulation for Option Pricing with Multiple Assets
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322853
Qinwen Deng1,*, Hongying Wu1, Yang Wu1, Zhiqiang Zhou1
  • 1: Xiangnan University
*Contact email: 827727129@qq.com

Abstract

It is a challenged topic of option pricing with multi-asset. This paper uses Monte Carlo (MC) simulation to valuate options which possess multiple assets. Firstly, given correlative coefficients, an algorithm to generate normal distributed random variables is established. Then, MC scheme is proposed for pricing European, American, Asian and Lookback options. Numerical experiments illustrate that MC simulation is an efficient and accurate method. With MC path number 8000, the relative errors of numerical European options are less than 0.5%. The stability experiments of MC algorithm are also carried out. As an advantage, the proposed MC algorithm can be extended to more general options such as Strangles and CEV options.