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Forecasting value-at-risk and expected shortfall for emerging markets using FIGARCH models

Author

Listed:
  • Alex Sandro Monteiro De Moraes

    (Pontifícia Universidade Católica do Rio de Janeiro)

  • Antonio Carlos Figueiredo Pinto

    (Pontifícia Universidade Católica do Rio de Janeiro)

  • Marcelo Cabus Klotzle

    (Pontifícia Universidade Católica do Rio de Janeiro)

Abstract

This paper compares the performance of long-memory models (FIGARCH) with short-memory models (GARCH) in forecasting volatility for calculating value-at-risk (VaR) and expected shortfall (ES) for multiple periods ahead for six emerging markets stock indices. We used daily data from 1999 to 2014 and an adaptation of the Monte Carlo simulation to estimate VaR and ES forecasts formultiple steps ahead (1, 10 and 20 days ), using FIGARCH and GARCH models for four errors distributions. The results suggest that, in general, the FIGARCH models improve the accuracy of forecasts for longer horizons; that the error distribution used may influence the decision about the best model; and that only for FIGARCH models the occurrence of underestimation of the true VaR is less frequent with increasing time horizon. However, the results suggest that rolling sampled estimated FIGARCH parameters change less smoothly over time compared to the GARCH models.

Suggested Citation

  • Alex Sandro Monteiro De Moraes & Antonio Carlos Figueiredo Pinto & Marcelo Cabus Klotzle, 2015. "Forecasting value-at-risk and expected shortfall for emerging markets using FIGARCH models," Brazilian Review of Finance, Brazilian Society of Finance, vol. 13(3), pages 394-437.
    • Handle: RePEc:brf:journl:v:13:y:2015:i:3:p:394-437
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    More about this item

    Keywords

    Expected shortfall; long-memory; volatility forecast; multiple steps ahead forecast; value-at-risk;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G1 - Financial Economics - - General Financial Markets

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