文章基本信息

标题：Deep Hedging under Rough Volatility
本地全文：下载
作者：Blanka Horvath ; Blanka Horvath ; Blanka Horvath 等
期刊名称：Risks
印刷版ISSN：2227-9091
出版年度：2021
卷号：9
期号：1
页码：138
DOI：10.3390/risks9070138
语种：English
出版社：MDPI, Open Access Journal
摘要：We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional) Markovian setup. In particular, we analyse the hedging performance of the original architecture under rough volatility models in view of existing theoretical results for those. Furthermore, we suggest parsimonious but suitable network architectures capable of capturing the non-Markoviantity of time-series. We also analyse the hedging behaviour in these models in terms of Profit and Loss (P&L) distributions and draw comparisons to jump diffusion models if the rebalancing frequency is realistically small.