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Evaluating Combined Forecasts for Realized Volatility Using Asymmetric Loss Functions

Author

Listed:
  • Giovanni De Luca

    (Universita degli Studi di Napoli "Parthenope", Italy)

  • Giampiero M. Gallo

    (Università degli Studi di Firenze, Italy)

  • Danilo Carità

    (Universita degli Studi di Napoli "Parthenope", Italy)

Abstract

In this work we provide the findings of a forecast combination analysis carried out on the realized volatility series of three market indexes (DAX, CAC, and AEX). Two volatility types (5 minutes, kernel) have been considered. Different loss functions suggest that forecasts computed through combining models are generally more accurate than those provided by single models. However, the choice of the latter can significantly affect the goodness of the results.

Suggested Citation

  • Giovanni De Luca & Giampiero M. Gallo & Danilo Carità, 2017. "Evaluating Combined Forecasts for Realized Volatility Using Asymmetric Loss Functions," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(2), pages 99-111, December.
    • Handle: RePEc:sgh:erfinj:v:2:y:2017:i:2:p:99-111
    DOI: 10.33119/ERFIN.2017.2.2.3
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    References listed on IDEAS

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    Cited by:

    1. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.

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    More about this item

    Keywords

    realized volatility; forecast combinations; loss functions;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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