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Forecasting Realized Volatility with Changes of Regimes

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  • Giampiero M. Gallo

    () (Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze)

  • Edoardo Otranto

    () (Dipartimento di Scienze Cognitive e della Formazione, Università degli Studi di Messina)

Abstract

Realized volatility of financial time series generally shows a slow–moving average level from the early 2000s to recent times, with alternating periods of turmoil and quiet. Modeling such a pattern has been variously tackled in the literature with solutions spanning from long–memory, Markov switching and spline interpolation. In this paper, we explore the extension of Multiplicative Error Models to include a Markovian dynamics (MS-MEM). Such a model is able to capture some sudden changes in volatility following an abrupt crisis and to accommodate different dynamic responses within each regime. The model is applied to the realized volatility of the S&P500 index: next to an interesting interpretation of the regimes in terms of market events, the MS-MEM has better in–sample fitting capability and achieves good out–of–sample forecasting performances relative to alternative specifications.

Suggested Citation

  • Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
  • Handle: RePEc:fir:econom:wp2014_03
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    Cited by:

    1. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2017. "The impact of oil-market shocks on stock returns in major oil-exporting countries: A Markov-switching approach," MPRA Paper 81638, University Library of Munich, Germany.

    More about this item

    Keywords

    MEM; regime switching; realized volatility; volatility persistence; volatility forecasting;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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