Wasserstein Distributionally Robust Option Pricing
Received:January 20, 2020  Revised:October 24, 2020
Key Words: option pricing   Wasserstein distance   distributionally robust optimization  
Fund Project:Supported by the National Natural Science Foundation of China (Grant Nos.11571061; 11401075; 11971092) and the Fundamental Research Funds for the Central Universities (Grant No.DUT17RC(4)38).
Author NameAffiliation
Wei LIU School of Mathematical Sciences, Dalian University of Technology, Liaoning 116024, P. R. China
School of Applied Mathematics, Beijing Normal University, Zhuhai, Guangdong 519087, P. R. China 
Li YANG School of Mathematical Sciences, Dalian University of Technology, Liaoning 116024, P. R. China 
Bo YU School of Mathematical Sciences, Dalian University of Technology, Liaoning 116024, P. R. China 
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Abstract:
      In this paper, the option pricing problem is formulated as a distributionally robust optimization problem, which seeks to minimize the worst case replication error for a given distributional uncertainty set (DUS) of the random underlying asset returns. The DUS is defined as a Wasserstein ball centred the empirical distribution of the underlying asset returns. It is proved that the proposed model can be reformulated as a computational tractable linear programming problem. Finally, the results of the empirical tests are presented to show the significance of the proposed approach.
Citation:
DOI:10.3770/j.issn:2095-2651.2021.01.010
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