Publication Type

Journal Article

Version

acceptedVersion

Publication Date

3-2015

Abstract

The paper proposes a self-exciting asset pricing model that takes into account co-jumps between prices and volatility and self-exciting jump clustering. We employ a Bayesian learning approach to implement real-time sequential analysis. We find evidence of self-exciting jump clustering since the 1987 market crash, and its importance becomes more obvious at the onset of the 2008 global financial crisis. We also find that learning affects the tail behaviors of the return distributions and has important implications for risk management, volatility forecasting, and option pricing.

Keywords

stock-prices, excess volatility, financial-markets, levy processes, predictability, returns, simulation, finite, risk

Discipline

Finance | Finance and Financial Management

Research Areas

Econometrics

Publication

Review of Financial Studies

Volume

28

Issue

3

First Page

876

Last Page

912

ISSN

0893-9454

Identifier

10.1093/rfs/hhu078

Publisher

Oxford University Press

Embargo Period

2-23-2020

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1093/rfs/hhu078

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