A New Approach to Markov-Switching GARCH Models

By Markus Haas, Stefan Mittnik, Marc S. Paolella. 2004

558 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/c3677675afa1362793833b241ba66234f3193467

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Citations in the corpus

ON THE STATIONARITY OF MARKOV-SWITCHING GARCH PROCESSES (2007, unknown): “Furthermore, the MSG-II model is analytically more tractable than MSG-I model [4] and its conditional variance can be straightforwardly constructed since the conditional variance at a specic time does not depend on previous state probabilities but only on previous observations and previous conditio”
Safeguarding food security in volatile global markets. (2011, background): “But because the validity of such multivariate analysis rests on the accurate choice of fundamental variables, other approaches that use price series only (Haas et al., 2004) have emerged.”
MCMC-based estimation of Markov Switching ARMA–GARCH models (2011, methodology): “These models were introduced to the econometric mainstream in the seminal article by Hamilton (1989). The difference is that the process can leave a state (parameter set) and returns with a positive probability.”
Optimally Harnessing Inter-Day and Intra-Day Information for Daily Value-at-Risk Prediction (2013, unknown): “Haas et al. (2004), Guidolin and Timmermann (2006) and, more recently, Sajjad et al. (2008) advocate the use of Markov-switching GARCH (MSGARCH) models to obtain more accurate VaR predictions, particularly, for risks in the far tail (i.e. α = 0.01).”
Markov Switching Models in Empirical Finance (2011, background): “For instance,Haas et al. (2004) have reexamined the forecasting performance of their MS-GARCH(1,1) model against a range of alternative benchmarks popular in the literature, including both standard GARCH(1,1) models as well as GARCH models with nonstandard innovations.”
Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model (2015, unknown): “For instance, a widely used rule is to classify the regimes according to the scale of contemporary volatility (Haas et al., 2004; Haas, 2009; Ho et al., 2013).”
Structural breaks and GARCH models of exchange rate volatility (2008, methodology): “using an expanding window, in light of Klaassen (2002) and Haas et al. (2004). Instead of viewing structural breaks as deterministic, the Markov-switching GARCH(1,1) model treats breaks as governed by a two-state Markov process.”