Classification of Volatility in Presence of Changes in Model Parameters
Abstract
The classification of volatility of financial time series has recently received a lot of contributions - in particular using model based clustering algorithms. Recent works have evidenced how volatility structure can vary along time, with gradual or abrupt changes in the coefficients of the model. We wonder if these changes can affect the classification of series in terms of similar volatility structure. We propose to classify the level of the unconditional volatility obtained from Multiplicative Er- ror Models with the possibility of changes in the parameters of the model in terms of regime switching or time varying smoothed coefficients. They provide different unconditional volatility structures with a proper interpretation, useful to represent different situations of interest. The different methodologies are coherent with each other and provide a common synthetic pattern. The procedure is experimented on fifteen stock indices volatilities.Download Info
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Paper provided by Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia in its series Working Paper CRENoS with number 201113.Length:
Date of creation: 2011
Date of revision:
Handle: RePEc:cns:cnscwp:201113
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Related research
Keywords: markov switching; smooth transition; unconditional volatility; clustering; amem;Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-08-02 (All new papers)
- NEP-ECM-2011-08-02 (Econometrics)
- NEP-ETS-2011-08-02 (Econometric Time Series)
References
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- Corduas, Marcella & Piccolo, Domenico, 2008. "Time series clustering and classification by the autoregressive metric," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1860-1872, January.
- Robert F. Engle & Giampiero M. Gallo, 2003.
"A Multiple Indicators Model For Volatility Using Intra-Daily Data,"
Econometrics Working Papers Archive
wp2003_07, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti".
- Engle, Robert F. & Gallo, Giampiero M., 2006. "A multiple indicators model for volatility using intra-daily data," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 3-27.
- Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model for Volatility Using Intra-Daily Data," NBER Working Papers 10117, National Bureau of Economic Research, Inc.
- Dueker, Michael J, 1997.
"Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 15(1), pages 26-34, January.
- Tom Doan, . "RATS programs to replicate Dueker(1997) Markov switching GARCH models," Statistical Software Components RTZ00048, Boston College Department of Economics.
- Michael Dueker, 1995. "Markov switching in GARCH processes and mean reverting stock market volatility," Working Papers 1994-015, Federal Reserve Bank of St. Louis.
- Maharaj, E.A., 1994. "A Significance Test for Classifying ARMA Models," Monash Econometrics and Business Statistics Working Papers 18/94, Monash University, Department of Econometrics and Business Statistics.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002.
"Modeling and Forecasting Realized Volatility,"
Working Papers
02-12, Duke University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
- Otranto, Edoardo, 2008.
"Clustering heteroskedastic time series by model-based procedures,"
Computational Statistics & Data Analysis,
Elsevier, vol. 52(10), pages 4685-4698, June.
- E. Otranto, 2008. "Clustering Heteroskedastic Time Series by Model-Based Procedures," Working Paper CRENoS 200801, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
- BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003.
"Multivariate GARCH models: a survey,"
CORE Discussion Papers
2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
- Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, EconWPA.
- Giampiero Gallo & Edoardo Otranto, 2007.
"Volatility Spillovers, Interdependence and Comovements: A Markov Switching Approach,"
Econometrics Working Papers Archive
wp2007_11, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti".
- Gallo, Giampiero M. & Otranto, Edoardo, 2008. "Volatility spillovers, interdependence and comovements: A Markov Switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3011-3026, February.
- Theodossiou, Panayiotis & Lee, Unro, 1993. "Mean and Volatility Spillovers across Major National Stock Markets: Further Empirical Evidence," Journal of Financial Research, Southern Finance Association & Southwestern Finance Association, vol. 16(4), pages 337-50, Winter.
- Pattarin, Francesco & Paterlini, Sandra & Minerva, Tommaso, 2004. "Clustering financial time series: an application to mutual funds style analysis," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 353-372, September.
- Caiado, Jorge & Crato, Nuno & Pena, Daniel, 2006. "A periodogram-based metric for time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2668-2684, June.
- Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-50, July.
- Edoardo Otranto & Giampiero Gallo, 2002.
"A Nonparametric Bayesian Approach To Detect The Number Of Regimes In Markov Switching Models,"
Econometric Reviews,
Taylor and Francis Journals, vol. 21(4), pages 477-496.
- Edoardo Otranto & Giampiero M. Gallo, 2001. "A Nonparametric Bayesian Approach to Detect the Number of Regimes in Markov Switching Models," Econometrics Working Papers Archive wp2001_04, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti".
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394.
- Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
- Zacharias Psaradakis & Nicola Spagnolo, 2003. "On The Determination Of The Number Of Regimes In Markov-Switching Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 237-252, 03.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Giampiero M. Gallo & Edoardo Otranto, 2012. "Volatility Swings in the US Financial Markets," Econometrics Working Papers Archive 2012_03, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti", revised Jul 2012.
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