A Regime-Switching Conditional Volatility Model Based on the Intraday Range

Murat Mazibas, Richard D. F. Harris

    Research output: Contribution to conferencePaperpeer-review

    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 languageEnglish
    Publication statusPublished - May 2020
    EventInternational Conference on Finance, Empirical Methods and Statistical Techniques - London, London, United Kingdom
    Duration: 21 May 202022 May 2020
    https://waset.org/finance-empirical-methods-and-statistical-techniques-conference-in-may-2020-in-london

    Conference

    ConferenceInternational Conference on Finance, Empirical Methods and Statistical Techniques
    Abbreviated title (ICFEMST 2020)
    Country/TerritoryUnited Kingdom
    CityLondon
    Period21/05/2022/05/20
    Internet address

    Keywords

    • Intraday range
    • Markov regime-switching
    • GARCH
    • Multiplicative error model
    • factor model

    ASJC Scopus subject areas

    • Economics and Econometrics

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