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Autocontours: Dynamic Specification Testing

Author

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  • Gloria González-Rivera
  • Zeynep Senyuz
  • Emre Yoldas

Abstract

We propose a new battery of dynamic specification tests for the joint hypothesis of iid-ness and density function based on the fundamental properties of independent random variables with identical distributions. We introduce a device-the autocontour-whose shape is very sensitive to departures from the null in either direction, thus providing superior power. The tests are parametric with asymptotic t and chi-squared limiting distributions and standard convergence rates. They do not require a transformation of the original data or a Kolmogorov style assessment of goodness-of-fit, explicitly account for parameter uncertainty, and have superior finite sample properties. An application to autoregressive conditional duration (ACD) models for trade durations shows that the difficulty with the assumed densities lies on the probability assigned to very small durations. Supplemental materials for this article are available online.

Suggested Citation

  • Gloria González-Rivera & Zeynep Senyuz & Emre Yoldas, 2011. "Autocontours: Dynamic Specification Testing," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 186-200, January.
    • Handle: RePEc:taf:jnlbes:v:29:y:2011:i:1:p:186-200
    DOI: 10.1198/jbes.2010.08144
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    Cited by:

    1. González-Rivera, Gloria & Sun, Yingying, 2017. "Density forecast evaluation in unstable environments," International Journal of Forecasting, Elsevier, vol. 33(2), pages 416-432.
    2. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    3. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    4. Igor L. Kheifets, 2015. "Specification tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 67-94, February.
    5. Rossi, Barbara & Sekhposyan, Tatevik, 2019. "Alternative tests for correct specification of conditional predictive densities," Journal of Econometrics, Elsevier, vol. 208(2), pages 638-657.
    6. Gloria Gonzalez-Rivera & Emre Yoldas, 2010. "Multivariate Autocontours for Specification Testing in Multivariate GARCH Models," Working Papers 201436, University of California at Riverside, Department of Economics.
    7. Harvey, Andrew, 2010. "Exponential conditional volatility models," DES - Working Papers. Statistics and Econometrics. WS ws103620, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Yves Dominicy & Hiroaki Ogata & David Veredas, 2013. "Inference for vast dimensional elliptical distributions," Computational Statistics, Springer, vol. 28(4), pages 1853-1880, August.
    9. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    10. Gonçalves Mazzeu, Joao Henrique & González-Rivera, Gloria & Ruiz Ortega, Esther & Veiga, Helena, 2016. "A Bootstrap Approach for Generalized Autocontour Testing," DES - Working Papers. Statistics and Econometrics. WS 23457, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. González-Rivera, Gloria & Sun, Yingying, 2015. "Generalized autocontours: Evaluation of multivariate density models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 799-814.
    12. Gloria Gonzalez-Rivera & Yun Luo, 2023. "A Truncated Mixture Transition Model for Interval-valued Time Series," Working Papers 202315, University of California at Riverside, Department of Economics.
    13. Jonas Dovern & Hans Manner, 2020. "Order‐invariant tests for proper calibration of multivariate density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 440-456, June.
    14. Bermejo Mancera, Miguel Ángel & Peña, Daniel & Sánchez, Ismael, 2011. "Densidad de predicción basada en momentos condicionados y máxima entropía : aplicación a la predicción de potencia eólica," DES - Working Papers. Statistics and Econometrics. WS ws111813, Universidad Carlos III de Madrid. Departamento de Estadística.

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