Bayesian Learning of Impacts of Self-Exciting Jumps in Returns and Volatility

Andras Fulop, Junye Li and Jun Yu
Additional contact information
Andras Fulop: Finance Department, ESSEC Business School, Paris-Singapore, Cergy-Pontoise Cedex, France 95021
Junye Li: Finance Department, ESSEC Business School, Paris-Singapore, 100 Victoria Street, Singapore 188064

No 03-2012, Working Papers from Singapore Management University, School of Economics

Abstract: The paper proposes a new class of continuous-time asset pricing models where negative jumps play a crucial role. Whenever there is a negative jump in asset returns, it is simultaneously passed on to diffusion variance and the jump intensity, generating self-exciting co-jumps of prices and volatility and jump clustering. To properly deal with parameter uncertainty and in-sample over-fitting, a Bayesian learning approach combined with an efficient particle filter is employed. It not only allows for comparison of both nested and non-nested models, but also generates all quantities necessary for sequential model analysis. Empirical investigation using S&P 500 index returns shows that volatility jumps at the same time as negative jumps in asset returns mainly through jumps in diffusion volatility. We find substantial evidence for jump clustering, in particular, after the recent financial crisis in 2008, even though parameters driving dynamics of the jump intensity remain difficult to identify.

Keywords: Self-Excitation; Volatility Jump; Jump Clustering; Extreme Events; Parameter Learning; Particle Filters; Sequential Bayes Factor; Risk Management (search for similar items in EconPapers)
JEL-codes: C11 C13 C32 G12 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2012-01
New Economics Papers: this item is included in nep-ecm, nep-rmg and nep-sea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in SMU Economics and Statistics Working Paper Series

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Related works:
Working Paper: Bayesian Learning of Impacts of Self-Exciting Jumps in Returns and Volatility (2011)
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