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  • Open Access


    Study on Quantum Finance Algorithm: Quantum Monte Carlo Algorithm based on European Option Pricing

    Jian-Guo Hu1,*, Shao-Yi Wu1,*, Yi Yang1, Qin-Sheng Zhu1, Xiao-Yu Li1, Shan Yang2

    Journal of Quantum Computing, Vol.4, No.1, pp. 53-61, 2022, DOI:10.32604/jqc.2022.027683

    Abstract 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… More >

  • Open Access


    How Load Aggregators Avoid Risks in Spot Electricity Market: In the Framework of Power Consumption Right Option Contracts

    Jiacheng Yang1, Xiaohe Zhai1, Zhongfu Tan1,2,*, Zhenghao He1

    Energy Engineering, Vol.119, No.3, pp. 883-906, 2022, DOI:10.32604/ee.2022.018033

    Abstract There is uncertainty in the electricity price of spot electricity market, which makes load aggregators undertake price risks for their agent users. In order to allow load aggregators to reduce the spot market price risk, scholars have proposed many solutions, such as improving the declaration decision-making model, signing power mutual insurance contracts, and adding energy storage and mobilizing demand-side resources to respond. In terms of demand side, calling flexible demand-side resources can be considered as a key solution. The user's power consumption rights (PCRs) are core contents of the demand-side resources. However, there have been few studies on the pricing… More >

  • Open Access


    An ETD Method for American Options under the Heston Model

    Rafael Company1, Vera N. Egorova2, Lucas Jódar1,*, Ferran Fuster Valls3

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 493-508, 2020, DOI:10.32604/cmes.2020.010208

    Abstract A numerical method for American options pricing on assets under the Heston stochastic volatility model is developed. A preliminary transformation is applied to remove the mixed derivative term avoiding known numerical drawbacks and reducing computational costs. Free boundary is treated by the penalty method. Transformed nonlinear partial differential equation is solved numerically by using the method of lines. For full discretization the exponential time differencing method is used. Numerical analysis establishes the stability and positivity of the proposed method. The numerical convergence behaviour and effectiveness are investigated in extensive numerical experiments. More >

  • Open Access


    Simulation of Multi-Option Pricing on Distributed Computing

    J.E. Lee1and S.J. Kim2

    CMES-Computer Modeling in Engineering & Sciences, Vol.86, No.2, pp. 93-112, 2012, DOI:10.3970/cmes.2012.086.093

    Abstract As the option trading nowadays has become popular, it is important to simulate efficiently large amounts of option pricings. The purpose of this paper is to show valuations of large amount of options, using network distribute computing resources. We valuated 108 options simultaneously on the self-made cluster computer system which is very inexpensive, compared to the supercomputer or the GPU adopting system. For the numerical valuations of options, we developed the option pricing software to solve the Black-Scholes partial differential equation by the finite element method. This yielded accurate values of options and the Greeks with reasonable computational times. This… More >

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