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Shrinkage estimation of semiparametric multiplicative error models

  • Brownlees, Christian T.
  • Gallo, Giampiero M.

Within models for nonnegative time series, it is common to encounter deterministic components (trends, seasonalities) which can be specified in a flexible form. This work proposes the use of shrinkage type estimation for the parameters of such components. The amount of smoothing to be imposed on the estimates can be chosen using different methodologies: Cross-Validation for dependent data or the recently proposed Focused Information Criterion. We illustrate such a methodology using a semiparametric autoregressive conditional duration model that decomposes the conditional expectations of durations into their dynamic (parametric) and diurnal (flexible) components. We use a shrinkage estimator that jointly estimates the parameters of the two components and controls the smoothness of the estimated flexible component. The results show that, from the forecasting perspective, an appropriate shrinkage strategy can significantly improve on the baseline maximum likelihood estimation.

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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 27 (2011)
Issue (Month): 2 ()
Pages: 365-378

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Handle: RePEc:eee:intfor:v:27:y:2011:i:2:p:365-378
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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  1. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  2. Allan Timmermann & Andrew Patton, 2004. "Properties of Optimal Forecasts under Asymmetric Loss and Nonlinearity," Working Papers wp04-05, Warwick Business School, Finance Group.
  3. Peter F. Christoffersen & Francis X. Diebold, . "Optimal Prediction Under Asymmetric Loss," CARESS Working Papres 97-20, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
  4. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model for Volatility Using Intra-Daily Data," NBER Working Papers 10117, National Bureau of Economic Research, Inc.
  5. Christian T. Brownlees & Giampiero Gallo, 2008. "Comparison of Volatility Measures: a Risk Management Perspective," Econometrics Working Papers Archive wp2008_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  6. Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," Review of Economic Studies, Oxford University Press, vol. 72(4), pages 1107-1125.
  7. Fernandes, Marcelo & Grammig, Joachim, 2006. "A family of autoregressive conditional duration models," Journal of Econometrics, Elsevier, vol. 130(1), pages 1-23, January.
  8. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," CFS Working Paper Series 2009/18, Center for Financial Studies (CFS).
  9. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(3), pages 489-518, Summer.
  10. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
  11. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  12. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
  13. Hansen, Bruce E., 2005. "Challenges For Econometric Model Selection," Econometric Theory, Cambridge University Press, vol. 21(01), pages 60-68, February.
  14. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-35, April.
  15. Leeb, Hannes & P tscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(01), pages 21-59, February.
  16. White, Halbert, 2006. "Approximate Nonlinear Forecasting Methods," Handbook of Economic Forecasting, Elsevier.
  17. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(3), pages 450-493.
  18. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
  19. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
  20. Christoffersen & Diebold, . "Further Results on Forecasting and Model Selection Under Asymmetric Loss," Home Pages _059, University of Pennsylvania.
  21. repec:cup:cbooks:9780521780506 is not listed on IDEAS
  22. Racine, Jeff, 2000. "Consistent cross-validatory model-selection for dependent data: hv-block cross-validation," Journal of Econometrics, Elsevier, vol. 99(1), pages 39-61, November.
  23. Christian T. Brownlees & Giampiero M. Gallo, 2008. "On Variable Selection for Volatility Forecasting: The Role of Focused Selection Criteria," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(4), pages 513-539, Fall.
  24. Hjort N.L. & Claeskens G., 2003. "Frequentist Model Average Estimators," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 879-899, January.
  25. repec:cup:cbooks:9780521785167 is not listed on IDEAS
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