Improving GARCH volatility forecasts with regime-switching GARCH

By Franc J. G. M. Klaassen. 2002

472 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/99c2f05d22626fb3377708f6080a09fca133b577

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Citations in the corpus

The Use of GARCH Models in VaR Estimation (2004, methodology): “The statistical adequacy will be tested based on Kupiec’s (1995) and Christoffersen’s (1998) backtesting measures, while the comparison between models of equivalent ability, in terms of statistical adequacy, will be performed via a loss function.”
Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model (2015, unknown): “However, as noted by Klaassen (2002), Ardia (2009) and Haas (2009), if regimes (states) are not Normal but leptokurtic, the use of within-regime normality can seriously affect the identification of the regime process.”
The impact of oil shocks on exchange rates: A Markov-switching approach (2016, background): “…pro- and counter-cyclicality of monetary and fiscal policies across countries, their exchange rate regimes, the degree of trade and financial openness, and the types of nonlinearities (e.g., real wage rigidities) that are present in the product and labor markets. period” (Klaassen, 2002; p. 368).”
Nonlinearity in cap-and-trade systems: The EUA price and its fundamentals (2013, methodology): “The model used in this paper is based on Gray (1996) and Klaassen (2002), who extend Hamilton’s original approach by including a generalized autoregressive conditional heteroscedasticity (GARCH) structure into the MRS model.”
Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models? (2019, methodology): “6 The main reasons for us to adopt the regime switching GARCH models of Klaassen (2002) other than those by Gray (1996) or Haas et al. (2004) are as follows.”
Forecasting risk with Markov-switching GARCH models:A large-scale performance study (2018, methodology): “We first use the UC test of Kupiec (1995) and the DQ test of Engle and Manganelli (2004) to evaluate the accuracy of each of the 32 methods considered in terms of predicting the VaR at the”
An Introduction to Univariate GARCH Models (2006, background): “Simpli cations of the model that circumvent this problem can be found in Gray (1996) and Klaassen (2002).”
ON THE STATIONARITY OF MARKOV-SWITCHING GARCH PROCESSES (2007, unknown): “…observations+ Klaassen proposed modifying Gray’s model by conditioning the expectation of previous conditional variances on all available observations and also on the current regime+A different concept of Markov-switching GARCH model has recently been introduced by Haas et al+ ~2004b!+…”
Forecasting crude oil price volatility (2018, unknown): “In this paper we follow Klaassen (2002) and Marcucci (2005) and replace h t1 by its expectation conditional on the information set at t 1 plus the current state variable, namely, h (i) t = (i) 0 + (i) 1 " 2 t1 + (i) 1 E t1 h h (i) t1 j S t i ; where E t1 h h (i) t1 j S t i = 2 X j=1 p ji;t1 (j) t1…”