Optimal Option Hedging with Policy Gradient

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationProceedings - 21st IEEE International Conference on Data Mining Workshops, ICDMW 2021
EditorsBing Xue, Mykola Pechenizkiy, Yun Sing Koh
PublisherIEEE Computer Society
Pages1112-1119
ISBN (Electronic)9781665424271
ISBN (Print)9781665424288
Publication statusPublished - Dec 2021

Publication series

NameIEEE International Conference on Data Mining Workshops, ICDMW
Volume2021-December
ISSN (Print)2375-9232
ISSN (Electronic)2375-9259

Conference

Title21st IEEE International Conference on Data Mining (ICDM 2021)
LocationVirtual
PlaceNew Zealand
CityAuckland
Period7 - 10 December 2021

Abstract

For the option hedging problem, we propose a reinforcement learning framework to statistically hedge generic financial options under the setting of non-zero risk-free interest rate and transaction cost. Instead of minimizing the risk of final wealth, we maximize the cumulative reward during the whole hedging process to find the optimal hedging strategies. In particular, we define the fundamental elements of reinforcement learning for the hedging problem. To illustrate the formulation, we utilize the Monte Carlo policy gradient with baseline onto both synthetic and realistic data to learn the state-value function and optimal policy function. Empirical evaluations demonstrate the effectiveness and performance of the proposed approach.

Research Area(s)

  • Option Hedging, Policy Gradient, Reinforcement Learning

Citation Format(s)

Optimal Option Hedging with Policy Gradient. / Xiao, Bo; Yao, Wuguannan; Zhou, Xiang.

Proceedings - 21st IEEE International Conference on Data Mining Workshops, ICDMW 2021. ed. / Bing Xue; Mykola Pechenizkiy; Yun Sing Koh. IEEE Computer Society, 2021. p. 1112-1119 (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2021-December).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review