Forecasting Stock Market Volatility with Regime-Switching GARCH Models

By Juri Marcucci. 2005

327 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/9ca3a225841765fe2d9d0fc21ec4cc25a9ab46bc

How researchers see this paper

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In Economics and Econometrics

1. Yue‐Jun Zhang
2. S. Basher
3. A. Haug
4. Jinliang Zhang
5. Perry Sadorsky
6. Keven Bluteau
7. Muhammad Shahbaz
8. Mingchih Lee

In Finance

1. Keven Bluteau
2. S. Basher
3. Mingchih Lee
4. Lieven Baele
5. Yue‐Jun Zhang
6. Ting Yao
7. A. Haug
8. Hung‐Chun Liu

Citations in the corpus

• Forecasting risk with Markov-switching GARCH models:A large-scale performance study (2018, methodology): “These models can adapt quickly to variations in the unconditional volatility level, which improves risk predictions (see e.g. Ardia, 2008; Marcucci, 2005).”
• Estimation of value-at-risk for energy commodities via fat-tailed GARCH models (2008, result): “Such conclusions reflect that the quadratic loss function does not take the opportunity cost of capital into account, which are consistent with the findings of Sarma et al. (2003) and Marcucci (2005).”
• 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…”
• Volatility forecasting of crude oil market: A new hybrid method (2018, methodology): “…performance evaluation criteria used in this paper are also well employed in a number of previous studies (Brailsford & Faff, 1996; Lopez, 2001; Marcucci, 2005; Wei et al., 2010): MSE ¼ ∑ n t¼1 r2t− br2t 2 =n (8) MAE ¼ ∑ n t¼1 r2t− br2t =n (9) HMSE ¼ ∑ n t¼1 1−r2t = br2t 2 =n (10) HMAE ¼ ∑…”
• Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model (2015, unknown): “For the real financial data, due to reasons such as the structural breaks in the real economy, regime switching is very likely to exist (Marcucci, 2005; Engle and Rangel, 2008; Beltratti and Morana, 2006).”
• The impact of oil shocks on exchange rates: A Markov-switching approach (2016, background): “14 Marcucci (2005) illustrates the importance of fat tailed innovations, particularly for the purpose of regime identification.”
• Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models? (2019, background): “…chain to have different GARCH behaviors, i.e., different volatility structures, so as to extend the GARCH model to the dynamic forms and realize better estimating and forecasting performance (Haas, Mittnik,& Paolella, 2004; Klaassen, 2002; Marcucci, 2005; Zhang&Wang, 2015; Zhang & Zhang, 2015).”
• Volatility Spillover Effects in European Equity Markets (2005, methodology): “Test statistics are obtained through a generalized method of moment (GMM) procedure similar to Richardson and Smith (1993) and Bekaert and Harvey (1997).”