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Re-inforcement Learning for Pricing & Hedging of Derivatives - A Simplified Showcase

descriptionPublicationkeyboard_double_arrow_right Research , Other literature type 12 Mar 2019 Switzerland English Publisher:Zenodo
Authors: Krabichler, Thomas;

doi: 10.5281/zenodo.2590927 , 10.5281/zenodo.2590928

Re-inforcement Learning for Pricing & Hedging of Derivatives - A Simplified Showcase

Abstract

This work is inspired by [1]. We provide a technical documentation of how one can exploit reinforcement learning in order to price & hedge financial derivatives in the presence of transaction cost. The concepts are illustrated exemplarily for a European call option in the one-step case.

+ Reihe: IFZ Working Paper, 0008/2019 + ISSN: 1662-520X

Country
Switzerland
Related Organizations
Keywords

Re-inforcement learning, Hedging, Transaction cost, Pricing, Neural networks

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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