Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/237274 
Year of Publication: 
2021
Citation: 
[Journal:] Financial Innovation [ISSN:] 2199-4730 [Volume:] 7 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2021 [Pages:] 1-16
Publisher: 
Springer, Heidelberg
Abstract: 
In this paper we consider the problem of estimating expected shortfall (ES) for discrete time stochastic volatility (SV) models. Specifically, we develop Monte Carlo methods to evaluate ES for a variety of commonly used SV models. This includes both models where the innovations are independent of the volatility and where there is dependence. This dependence aims to capture the well-known leverage effect. The performance of our Monte Carlo methods is analyzed through simulations and empirical analyses of four major US indices.
Subjects: 
Expected shortfall
Stochastic volatility
Value-at-risk
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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