Modelling Stochastic Volatility with Leverage and Jumps: A Simulated Maximum Likelihood Approach via Particle Filtering

Sheheryar Malik and Michael K. Pitt

No 271302, Economic Research Papers from University of Warwick - Department of Economics

Abstract: In this paper we provide a unified methodology in order to conduct likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space form, approximating the likelihood for the parameters is conducted with output generated by the particle filter. Methods are employed to ensure that the approximating likelihood is continuous as a function of the unknown parameters thus enabling the use of Newton-Raphson type maximization algorithms. Our approach is robust and efficient relative to alternative Markov Chain Monte Carlo schemes employed in such contexts. In addition it provides a feasible basis for undertaking the non-trivial task of model comparison. The technique is applied to daily returns data for various stock price indices. We find strong evidence in favour of a leverage effect in all cases. Jumps are an important component in two out of the four series we consider.

Keywords: Financial; Economics (search for similar items in EconPapers)
Pages: 29
Date: 2009-04-03
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://ageconsearch.umn.edu/record/271302/files/twerp_897.pdf (application/pdf)
https://ageconsearch.umn.edu/record/271302/files/twerp_897.pdf?subformat=pdfa (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:ags:uwarer:271302

DOI: 10.22004/ag.econ.271302

Access Statistics for this paper

More papers in Economic Research Papers from University of Warwick - Department of Economics
Bibliographic data for series maintained by AgEcon Search ().