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A new class of independence tests for interval forecasts evaluation

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  • Araújo Santos, P.
  • Fraga Alves, M.I.

Abstract

Interval forecasts evaluation can be reduced to examining the unconditional coverage and independence properties of the hit sequence. A new class of exact independence tests for the hit sequence and a definition for tendency to clustering of violations are proposed. The tests are suitable for detecting models with a tendency to generate clusters of violations and are based on an exact distribution that does not depend on an unknown parameter. The asymptotic distribution is also derived. The choice of one test within the class is studied. Moreover, a simulation study provides evidence that, in order to test the independence hypothesis, the suggested tests perform better than other tests presented in the literature. An empirical application is given for a period that includes the 2008 financial crisis.

Suggested Citation

  • Araújo Santos, P. & Fraga Alves, M.I., 2012. "A new class of independence tests for interval forecasts evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3366-3380.
    • Handle: RePEc:eee:csdana:v:56:y:2012:i:11:p:3366-3380
    DOI: 10.1016/j.csda.2010.10.002
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    1. Argyropoulos, Christos & Panopoulou, Ekaterini, 2019. "Backtesting VaR and ES under the magnifying glass," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 22-37.
    2. Sarafrazi, Soodabeh & Hammoudeh, Shawkat & AraújoSantos, Paulo, 2014. "Downside risk, portfolio diversification and the financial crisis in the euro-zone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 368-396.
    3. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    4. Araújo Santos, P. & Fraga Alves, M.I., 2013. "Forecasting Value-at-Risk with a duration-based POT method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 295-309.
    5. Araújo Santos, Paulo & Fraga Alves, Isabel & Hammoudeh, Shawkat, 2013. "High quantiles estimation with Quasi-PORT and DPOT: An application to value-at-risk for financial variables," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 487-496.
    6. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    7. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    8. Liu, Tengdong & Hammoudeh, Shawkat & Santos, Paulo Araújo, 2014. "Downside risk and portfolio diversification in the euro-zone equity markets with special consideration of the crisis period," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 47-68.

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