Point process models for extreme returns: Harnessing implied volatility

Rodrigo Herrera and Adam Clements

No 104, NCER Working Paper Series from National Centre for Econometric Research

Abstract: Forecasting the risk of extreme losses is an important issue in the management of financial risk. There has been a great deal of research examining how option implied volatilities (IV) can be used to forecasts asset return volatility. However, the impact of IV in the context of predicting extreme risk has received relatively little attention. The role of IV is considered within a range of models beginning with the traditional GARCH based approach. Furthermore, a number of novel point process models for forecasting extreme risk are proposed in this paper. Univariate models where IV is included as an exogenous variable are considered along with a novel bivariate approach where movements in IV are treated as another point process. It is found that in the context of forecasting Value-at-Risk, the bivariate models produce the most accurate forecasts across a wide range of scenarios.

Keywords: Implied volatility; Hawkes process; Peaks over threshold; Point process; Extreme events (search for similar items in EconPapers)
JEL-codes: C14 C53 (search for similar items in EconPapers)
Pages: 23
Date: 2015-05-06
New Economics Papers: this item is included in nep-for and nep-rmg
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http://www.ncer.edu.au/papers/documents/WP104.pdf (application/pdf)

Related works:
Journal Article: Point process models for extreme returns: Harnessing implied volatility (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:qut:auncer:2015_02

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