Abstract
In this paper, we develop a component Markov switching conditional volatility model based on the intraday range and evaluate its performance in forecasting the weekly volatility of the S&P 500 index. We compare the performance of the range-based Markov switching model with that of a number of well-established return-based and range-based volatility models, namely the EWMA, GARCH and FIGARCH models, the Markov Regime-Switching GARCH model of Klaassen (2002), the hybrid EWMA model of Harris and Yilmaz (2010) and the CARR model of Chou (2005). We show that the range based Markov switching conditional volatility models produce more accurate out-of sample forecasts, contain more information about true volatility and exhibit similar or better performance when used for the estimation of value at risk.
| Original language | English |
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| Publication status | Published - May 2020 |
| Event | International Conference on Finance, Empirical Methods and Statistical Techniques - London, London, United Kingdom Duration: 21 May 2020 → 22 May 2020 https://waset.org/finance-empirical-methods-and-statistical-techniques-conference-in-may-2020-in-london |
Conference
| Conference | International Conference on Finance, Empirical Methods and Statistical Techniques |
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| Abbreviated title | (ICFEMST 2020) |
| Country/Territory | United Kingdom |
| City | London |
| Period | 21/05/20 → 22/05/20 |
| Internet address |
Keywords
- Intraday range
- Markov regime-switching
- GARCH
- Multiplicative error model
- factor model
ASJC Scopus subject areas
- Economics and Econometrics