Gamma and vega hedging using deep distributional reinforcement learning

We show how reinforcement learning can be used in conjunction with quantile regression to develop a hedging strategy for a trader responsible for derivatives that arrive stochastically and depend on a single underlying asset. We assume that the trader makes the portfolio delta-neutral at the end of...

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Detalles Bibliográficos
Autores principales: Cao, Jay, Chen, Jacky, Farghadani, Soroush, Hull, John, Poulos, Zissis, Wang, Zeyu, Yuan, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9992725/
https://www.ncbi.nlm.nih.gov/pubmed/36909205
http://dx.doi.org/10.3389/frai.2023.1129370

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9992725/
https://www.ncbi.nlm.nih.gov/pubmed/36909205
http://dx.doi.org/10.3389/frai.2023.1129370

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