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Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets

Author

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  • Beatriz Vaz de Melo Mendes

    (Federal University at Rio de Janeiro)

  • Victor Bello Accioly

    (Federal University at Rio de Janeiro)

Abstract

This paper empirically shows that (E)GARCH volatility forecasts may be improved by inserting an appropriate exogenous variable in the volatility equation. Several realized measures were tested as regressors and the robust to microstructure effects and/or jumps realized range-based measures provided the best results. The out-of-sample forecasts were computed in two steps. Firstly, the (E)GARCH-X model was estimated. Secondly, an ARFIMA forecast of the realized range was plugged into the volatility prediction formula. The methodology was illustrated in a comprehensive study involving fifteen market indices from developed stock markets. It was also shown that the inclusion of realized range-based measures as regressors reduces persistence and renders the past squared returns with no remaining explanatory power. We use two evaluation criteria to compare the forecasting performance of the (E)GARCH-X model and the Realized GARCH model.

Suggested Citation

  • Beatriz Vaz de Melo Mendes & Victor Bello Accioly, 2017. "Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 631-658, October.
    • Handle: RePEc:spr:jecfin:v:41:y:2017:i:4:d:10.1007_s12197-017-9386-x
    DOI: 10.1007/s12197-017-9386-x
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    More about this item

    Keywords

    (E)GARCH-X and realized GARCH models; Realized range; ARFIMA model; Two-step GARCH-X forecasts;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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