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Topics in Theoretical and Applied Statistics pp 263–273Cite as

A Comparison of Different Procedures for Combining High-Dimensional Multivariate Volatility Forecasts

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Part of the book series: Studies in Theoretical and Applied Statistics ((STASSPSS))

Abstract

The paper investigates the effect of model uncertainty on multivariate volatility prediction. Our aim is twofold. First, by means of a Monte Carlo simulation, we assess the accuracy of different techniques in estimating the combination weights assigned to each candidate model. Second, in order to investigate the economic profitability of forecast combination, we present the results of an application to the optimization of a portfolio of the US stock returns. Our main finding is that, for both real and simulated data, the results are highly sensitive not only to the choice of the model but also to the specific combination procedure being used.

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Notes

  1. 1.

    We remark that, although the DGPs considered in the simulation study do impose a convexity constraint on the combination weights, we do not impose this constraint at the estimation stage.

  2. 2.

    The data can be freely downloaded from the online data archive of the Journal of Applied Econometrics. The same data are also used in the paper by Golosnoy et al. [8].

  3. 3.

    Due to space constraints, we omit reporting the estimates of the elements of the conditional correlation matrix for the CCC model but this will be made available upon request.

References

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Author information

Authors and Affiliations

  1. Department of Economics and Statistics (DiSES) & Statlab, University of Salerno, Via Ponte Don Melillo, 84084, Fisciano (SA), Italy

    Alessandra Amendola & Giuseppe Storti

Authors
  1. Alessandra Amendola
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  2. Giuseppe Storti
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Corresponding author

Correspondence to Giuseppe Storti .

Editor information

Editors and Affiliations

  1. MEMOTEF, Sapienza University of Rome, Rome, Italy

    Giorgio Alleva

  2. Dept. of Statistcs & Informatics, University of Florence, Florence, Italy

    Andrea Giommi

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Amendola, A., Storti, G. (2016). A Comparison of Different Procedures for Combining High-Dimensional Multivariate Volatility Forecasts. In: Alleva, G., Giommi, A. (eds) Topics in Theoretical and Applied Statistics. Studies in Theoretical and Applied Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-27274-0_23

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