The value of Monte Carlo model-based variance reduction technology in the pricing of financial derivatives

Yunyu Zhang

PLOS ONE, 2020, vol. 15, issue 2, 1-13

Abstract: The purpose of the study is to reduce the error in the pricing process of financial derivatives, as well as to obtain more accurate product values, thereby reducing transaction costs, accelerating transaction speed, establishing a larger investment scale, and enabling investors to obtain excellent returns under market conditions as much as possible. Based on the variance reduction technology, a Monte Carlo model that can effectively analyze financial prices is added to analyze price fluctuations and find the optimal holding time for users of financial derivatives, thereby reducing the risk of holding the financial derivatives. The results show that the Monte Carlo model-based variance reduction technology can significantly improve the simulation efficiency of financial derivatives pricing. In addition, the importance sampling method is used to optimize the selection, thereby making it closer to the theoretical values. The proposed method is easy to implement and has higher computational efficiency, which can ensure the financial benefits of users holding financial derivatives during the holding period. It can be seen that the Monte Carlo model-based variance reduction technology has high application value in the pricing of financial derivatives, and it is of great significance for the pricing of other products.

Date: 2020
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0229737

DOI: 10.1371/journal.pone.0229737

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