A New Approach to Markov-Switching GARCH Models

Haas, Markus; Mittnik, Stefan; Paolella, Marc S.

doi:10.1093/jjfinec/nbh020

Cited by 425 publications

(335 citation statements)

References 42 publications

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“…More importantly, in our case, we found the GARCH (1, 1) model to fit the data better than the GARCH (2, 2) model, both in-and out-of-sample. 1 Given that, observed the so-called "leverage effect" in the volatility of returns of the TOP40 index using the Glosten et al, (1983)-GARCH (GJR-GARCH) model, we too look into the issue by considering not only the GJR-GARCH(1, 1) model, but also the Markov Switching-GARCH (MS-GARCH) framework (Klassen, 2002;Haas et al, 2004) in terms of forecasting relative to our benchmark GARCH (1, 1) model. Note, the so-called leverage effect refers to the situation where negative returns shocks are correlated with larger increases in volatility than positive returns shocks.…”

Section: Introductionmentioning

confidence: 99%

Structural breaks and GARCH models of stock return volatility: The case of South Africa

et al. 2012

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This paper investigates the empirical relevance of structural breaks in forecasting stock return volatility using both in-sample and out-of-sample tests and daily returns for the Johannesburg Stock Exchange (JSE) All Share Index from 07/02/1995 to 08/25/2010. We find evidence of structural breaks in the unconditional variance of the stock returns series over the period, with high levels of persistence and variability in the parameter estimates of the GARCH (1, 1) model across the sub-samples defined by the structural breaks. This indicates that structural breaks are empirically relevant to stock return volatility in South Africa. In out-of-sample tests, we find that combining forecasts from different benchmark and competing models that accommodate structural breaks in volatility improves the accuracy of volatility forecasting. Furthermore, for shorter horizons, the MS-GARCH model better captures asymmetry in stock return volatility than the GJR-GARCH (1, 1) model, which better suited to longer horizons, but in general, the asymmetric models fail to outperform the GARCH (1,1) model. Keywords: stock return volatility, structural breaks, in-sample tests, out-of-sample tests, GARCH Models.JEL classification: C22, C53, G11, G12 ♦ We would like to thank Professor Mehmet Bacilar for many helpful comments. However, any errors are solely ours.

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Section: Introductionmentioning

confidence: 99%

Structural breaks and GARCH models of stock return volatility: The case of South Africa

et al. 2012

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“…SWGARCH: the SWGARCH models in this work were based on Haas et al (2004) and on Valls and Almeida (2000). Each series was modeled with a univariate SWGARCH model, with GARCH (1, 1).…”

Section: Equation 3: Expected Regime Durationmentioning

confidence: 99%

“…The SWGARCH (1, 1) univariate models were tested for all the 92 series. The equations followed Haas et al (2004) and Valls and Almeida (2000), 15 with the coefficients defined after maximizing the log-likelihood of the SWGARCH parameters. Several volatility regimes could be tested (parameter k), yet for parsimony tests were restricted to three and two regimes.…”

Section: Equation 9: Expected Daily Loss Evaluated From Currency Exchmentioning

confidence: 99%

Value-at-Risk Approach to Currency Crises: A Brazilian Example With the Central Bank and Currency Based Assets

2013

CBR

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“…Simpli…cations of the model that circumvent this problem can be found in Gray (1996) and Klaassen (2002). A good discussion about their models can be found in Haas, Mittnik and Paolella (2004). These authors present another Markov-switching (MS-) GARCH model whose fourthmoment structure they are able to work out.…”

Section: Markov-switching Arch and Garchmentioning

confidence: 99%

“…That does not seem possible for the other models. The MS-GARCH model of Haas et al (2004) is de…ned as follows:…”

Section: Markov-switching Arch and Garchmentioning

confidence: 99%

An Introduction to Univariate GARCH Models

Teräsvirta

2009

Handbook of Financial Time Series

103

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A New Approach to Markov-Switching GARCH Models

Cited by 425 publications

References 42 publications

Structural breaks and GARCH models of stock return volatility: The case of South Africa

Structural breaks and GARCH models of stock return volatility: The case of South Africa

Value-at-Risk Approach to Currency Crises: A Brazilian Example With the Central Bank and Currency Based Assets

An Introduction to Univariate GARCH Models

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