EconPapers    
Economics at your fingertips  
 

EGARCH and Stochastic Volatility: Modeling Jumps and Heavy-tails for Stock Returns

Jouchi Nakajima

No 08-E-23, IMES Discussion Paper Series from Institute for Monetary and Economic Studies, Bank of Japan

Abstract: This paper proposes the EGARCH model with jumps and heavy- tailed errors, and studies the empirical performance of different models including the stochastic volatility models with leverage, jumps and heavy-tailed errors for daily stock returns. In the framework of a Bayesian inference, the Markov chain Monte Carlo estimation methods for these models are illustrated with a simulation study. The model comparison based on the marginal likelihood estimation is provided with data on the U.S. stock index.

Keywords: Bayesian analysis; EGARCH; Heavy-tailed error; Jumps; Marginal likelihood; Markov chain Monte Carlo; Stochastic volatility (search for similar items in EconPapers)
JEL-codes: C11 C15 G12 (search for similar items in EconPapers)
Date: 2008-09
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-fmk and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.imes.boj.or.jp/research/papers/english/08-E-23.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ime:imedps:08-e-23

Access Statistics for this paper

More papers in IMES Discussion Paper Series from Institute for Monetary and Economic Studies, Bank of Japan Contact information at EDIRC.
Bibliographic data for series maintained by Kinken ().

 
Page updated 2020-04-07
Handle: RePEc:ime:imedps:08-e-23