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                                                     Seminar

             Department of Systems Engineering and Engineering Management
The Chinese University of Hong Kong

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Title	:	Stochastic Volatility and Jumps: Exponentially Affine Yes or No? An Empirical Analysis of S&P500 Dynamics
Speaker	:	Ms. Katja Ignatieva
		Economics and Finance at Macquarie University Sydney, Australia and Goethe University Frankfurt, Germany
Date	:	Nov 24th, 2010 (Wednesday)
Time	:	4:30 p.m. - 5:30 p.m.
Venue	:	Room 513
		William M.W. Mong Engineering Building
		(Engineering Building Complex Phase 2)
		CUHK

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Abstract:
　

This paper analyzes exponentially affine and non-affine stochastic volatility models with jumps in returns and volatility. Markov Chain Monte Carlo technique is applied within a Bayesian inference framework to estimate model parameters and latent variables using daily returns from the S&P 500 stock index. There are two approaches to overcome the problem of misspecification of the square root stochastic volatility model. The first approach investigates non-affine alternatives of the volatility process. The second approach consists in examining more heavily parameterized models by adding jumps to the return and possibly to the volatility process. The aim of this paper is to combine both model frameworks and to test by using statistical and economical measures whether the class of affine models is outperformed by the class of non-affine models if we include jumps into the stochastic processes. We conclude that the non-affine model structure have
promising statistical properties and are worth further investigations. Further, we find affine models with jump components that perform similar to the non-affine models without jump components. Since non-affine models yield economically unrealistic parameter estimates, and research is rather developed for the affine model structures we have a tendency to prefer the affine jump diffusion models.

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Biography:
　

Katja Ignatieva is a PhD candidate in Economics and Finance at Macquarie University Sydney, Australia and Goethe University Frankfurt, Germany. Prior to joining the PhD program, Katja has received her MSc in Mathematics and Statistics at Humboldt University Berlin, Germany and yet another MSc(R) in Statistics at Glasgow University, UK. She further has several years of experience working in the department of risk management in one of the leading financial institutions in Frankfurt, Germany.

Katja's primary fields of interest are derivative pricing, empirical research in derivatives markets, asset pricing, international macroeconomics and finance, Markov Chain Monte Carlo (MCMC) methods in finance, and risk management.

************************* ALL ARE WELCOME ************************

Host	:	Prof. Nan Chen
Tel	:	(852)2609-8237
Email	:	nchen@se.cuhk.edu.hk
Enquiries	:	Prof. Nan Chen or Prof. Sean X. Zhou
	:	Department of Systems Engineering and Engineering Management
		CUHK
Website	:	http://www.se.cuhk.edu.hk/~seem5201
Email	:	seem5201@se.cuhk.edu.hk

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