Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China

Research Article

Valuation of Spread Options Based on Monte Carlo Simulation and Its Relationship with Asset Correlation

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  • @INPROCEEDINGS{10.4108/eai.28-10-2022.2328454,
        author={Jiaer  Geng and Boyang  Gong and Wenyi  Zhang},
        title={Valuation of Spread Options Based on Monte Carlo Simulation and Its Relationship with Asset Correlation},
        proceedings={Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China},
        publisher={EAI},
        proceedings_a={FFIT},
        year={2023},
        month={4},
        keywords={monte-carlo simulation; option pricing; spread option},
        doi={10.4108/eai.28-10-2022.2328454}
    }
    
  • Jiaer Geng
    Boyang Gong
    Wenyi Zhang
    Year: 2023
    Valuation of Spread Options Based on Monte Carlo Simulation and Its Relationship with Asset Correlation
    FFIT
    EAI
    DOI: 10.4108/eai.28-10-2022.2328454
Jiaer Geng1, Boyang Gong2, Wenyi Zhang3,*
  • 1: Fordham University
  • 2: University of Illinois at Urbana-Champaign
  • 3: College of liberal arts & science major statistics University of Illinois at Urbana-Champaign Urbana
*Contact email: ChampaignWenyiz2@illinois.edu

Abstract

Spread options are relatively young derivative products yet have a growing importance in the financial market for their frequent occurrence in energy derivatives. Two typical types of spread options are spark spreads and crack spreads. The crack spreads define the spread as the price difference between crude and refined oil, offering oil refiners insights into their marginal profits, while spark spreads are the difference between electricity and natural gas, enabling utility companies to predict future profitability. In this paper, we investigate the valuation of spread option products based on the Margrabe model with the Monte Carlo Simulations method. Specifically, two assets are selected (i.e., General Motor Company and Chesapeake Energy) to simulate spark spread. According to simulations, correlation and values of options are inversely related. In this case, it indicates that it will generate more profit when the correlation becomes smaller, and investors can find a balance between profits and safety by selecting stocks with different correlations. Overall, these results shed light on guiding future exploration focusing on spread option pricing.