A Closer Look at the Relation between GARCH and Stochastic Autoregressive Volatility
AbstractWe show that, for three common SARV models, fitting a minimum mean square linear filter is equivalent to fitting a GARCH model. This suggests that GARCH models may be useful for filtering, forecasting, and parameter estimation in stochastic volatility settings. To investigate, we use simulations to evaluate how the three SARV models and their associated GARCH filters perform under controlled conditions and then we use daily currency and equity index returns to evaluate how the models perform in a risk management application. Although the GARCH models produce less precise forecasts than the SARV models in the simulations, it is not clear that the performance differences are large enough to be economically meaningful. Consistent with this view, we find that the GARCH and SARV models perform comparably in tests of conditional value-at-risk estimates using the actual data. , .
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoArticle provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.
Volume (Year): 1 (2003)
Issue (Month): 3 ()
Contact details of provider:
Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK
Fax: 01865 267 985
Web page: http://jfec.oxfordjournals.org/
More information through EDIRC
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Jacek Osiewalski & Anna Pajor, 2009. "Bayesian Analysis for Hybrid MSF-SBEKK Models of Multivariate Volatility," Central European Journal of Economic Modelling and Econometrics, CEJEME, CEJEME, vol. 1(2), pages 179-202, November.
- Franses, Ph.H.B.F. & van der Leij, M.J. & Paap, R., 2005. "A simple test for GARCH against a stochastic volatility," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute EI 2005-41, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Lars Stentoft, 2011.
"American Option Pricing with Discrete and Continuous Time Models: An Empirical Comparison,"
CREATES Research Papers, School of Economics and Management, University of Aarhus
2011-34, School of Economics and Management, University of Aarhus.
- Stentoft, Lars, 2011. "American option pricing with discrete and continuous time models: An empirical comparison," Journal of Empirical Finance, Elsevier, Elsevier, vol. 18(5), pages 880-902.
- Mark J. Jensen & John M. Maheu, 2008.
"Bayesian semiparametric stochastic volatility modeling,"
Working Paper, Federal Reserve Bank of Atlanta
2008-15, Federal Reserve Bank of Atlanta.
- Jensen, Mark J. & Maheu, John M., 2010. "Bayesian semiparametric stochastic volatility modeling," Journal of Econometrics, Elsevier, Elsevier, vol. 157(2), pages 306-316, August.
- Mark J Jensen & John M Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," Working Papers, University of Toronto, Department of Economics tecipa-314, University of Toronto, Department of Economics.
- Mark J. Jensen & John M. Maheu, 2009. "Bayesian Semiparametric Stochastic Volatility Modeling," Working Paper Series, The Rimini Centre for Economic Analysis 23_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
- Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai, 2012. "GARCH Option Valuation: Theory and Evidence," CREATES Research Papers, School of Economics and Management, University of Aarhus 2012-50, School of Economics and Management, University of Aarhus.
- Fung, Ka Wai Terence & Demir, Ender & Zhou, Lu, 2014. "Capital Asset Pricing Model and Stochastic Volatility: A Case study of India," MPRA Paper 56180, University Library of Munich, Germany.
- Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai, 2009. "Exploring Time-Varying Jump Intensities: Evidence from S&P500 Returns and Options," CIRANO Working Papers, CIRANO 2009s-34, CIRANO.
- Fung, Ka Wai Terence & Lau, Chi Keung Marco & Chan, Kwok Ho, 2013. "The Conditional CAPM, Cross-Section Returns and Stochastic Volatility," MPRA Paper 52469, University Library of Munich, Germany.
- Tsiakas, Ilias, 2008. "Overnight information and stochastic volatility: A study of European and US stock exchanges," Journal of Banking & Finance, Elsevier, Elsevier, vol. 32(2), pages 251-268, February.
- Ilias Tsiakas, 2004. "Analysis of the predictive ability of information accumulated over nights, weekends and holidays," Econometric Society 2004 Australasian Meetings, Econometric Society 208, Econometric Society.
- Fung, Ka Wai Terence & Lau, Chi Keung Marco & Chan, Kwok Ho, 2014. "The conditional equity premium, cross-sectional returns and stochastic volatility," Economic Modelling, Elsevier, Elsevier, vol. 38(C), pages 316-327.
- Christoffersen, Peter & Jacobs, Kris & Ornthanalai, Chayawat, 2012. "Dynamic jump intensities and risk premiums: Evidence from S&P500 returns and options," Journal of Financial Economics, Elsevier, Elsevier, vol. 106(3), pages 447-472.
- Kirby, Chris, 2006. "Linear filtering for asymmetric stochastic volatility models," Economics Letters, Elsevier, Elsevier, vol. 92(2), pages 284-292, August.
- John M Maheu & Thomas H McCurdy, 2007. "Modeling foreign exchange rates with jumps," Working Papers, University of Toronto, Department of Economics tecipa-279, University of Toronto, Department of Economics.
- Ren-Her Wang & John Aston & Cheng-Der Fuh, 2010. "The Role of Additional Information in Option Pricing: Estimation Issues for the State Space Model," Computational Economics, Society for Computational Economics, Society for Computational Economics, vol. 36(4), pages 283-307, December.
- Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2006. "Stochastic Volatility, Trading Volume, and the Daily Flow of Information," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 79(3), pages 1551-1590, May.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press) or (Christopher F. Baum).
If references are entirely missing, you can add them using this form.