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Dynamic modeling under linear-exponential loss

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  • Anatolyev, Stanislav

Abstract

We develop a methodology of parametric modeling of time series dynamics when the underlying loss function is linear-exponential (Linex). We propose to directly model the dynamics of the conditional expectation that determines the optimal predictor. The procedure hinges on the exponential quasi maximum likelihood interpretation of the Linex loss and nicely fits the multiple error modeling framework. Many conclusions relating to estimation, inference and forecasting follow from results already available in the econometric literature. The methodology is illustrated using data on United States GNP growth and Treasury bill returns.

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Bibliographic Info

Article provided by Elsevier in its journal Economic Modelling.

Volume (Year): 26 (2009)
Issue (Month): 1 (January)
Pages: 82-89

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Handle: RePEc:eee:ecmode:v:26:y:2009:i:1:p:82-89

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Web page: http://www.elsevier.com/locate/inca/30411

Related research

Keywords: Linear-exponential loss Optimal predictor Quasi-maximum likelihood Multiplicative error model Autoregressive conditional durations;

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References

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  1. Robert F. Engle, 1996. "The Econometrics of Ultra-High Frequency Data," NBER Working Papers 5816, National Bureau of Economic Research, Inc.
  2. Shlomo Benartzi & Richard H. Thaler, 1993. "Myopic Loss Aversion and the Equity Premium Puzzle," NBER Working Papers 4369, National Bureau of Economic Research, Inc.
  3. Weiss, Andrew A, 1996. "Estimating Time Series Models Using the Relevant Cost Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 539-60, Sept.-Oct.
  4. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
  5. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
  6. Christoffersen & Diebold, . "Optimal Prediction Under Asymmetric Loss," Home Pages 167, 1996., University of Pennsylvania.
  7. Andrew Ang & Monika Piazzesi & Min Wei, 2003. "What does the yield curve tell us about GDP growth?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  8. Tim Bollerslev & Jeffrey M. Wooldridge, 1988. "Quasi-Maximum Likelihood Estimation of Dynamic Models with Time-Varying Covariances," Working papers 505, Massachusetts Institute of Technology (MIT), Department of Economics.
  9. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
  10. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
  11. Meitz, Mika & Terasvirta, Timo, 2006. "Evaluating Models of Autoregressive Conditional Duration," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 104-124, January.
  12. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model For Volatility Using Intra-Daily Data," Econometrics Working Papers Archive wp2003_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  13. Christoffersen & Diebold, . "Further Results on Forecasting and Model Selection Under Asymmetric Loss," Home Pages _059, University of Pennsylvania.
  14. Peter Christoffersen & Kris Jacobs, 2003. "The Importance of the Loss Function in Option Valuation," CIRANO Working Papers 2003s-52, CIRANO.
  15. 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.
  16. Batchelor, Roy & Peel, David A., 1998. "Rationality testing under asymmetric loss," Economics Letters, Elsevier, vol. 61(1), pages 49-54, October.
  17. Michael Artis & Massimiliano Marcellino, 2001. "Fiscal forecasting: The track record of the IMF, OECD and EC," Econometrics Journal, Royal Economic Society, vol. 4(1), pages S20-S36.
  18. Fernandes, Marcelo & Grammig, Joachim, 2003. "A family of autoregressive conditional duration models," Economics Working Papers (Ensaios Economicos da EPGE) 501, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  19. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2005. "Biases In Macroeconomic Forecasts: Irrationality Or Asymmetric Loss?," CAMA Working Papers 2005-14, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  20. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  21. Skouras, Spyros, 2007. "Decisionmetrics: A decision-based approach to econometric modelling," Journal of Econometrics, Elsevier, vol. 137(2), pages 414-440, April.
  22. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
  23. John H. Cochrane & Monika Piazzesi, 2002. "Bond Risk Premia," NBER Working Papers 9178, National Bureau of Economic Research, Inc.
  24. Allan Timmermann & Andrew J. Patton, 2004. "Properties of Optimal Forecasts," Econometric Society 2004 North American Winter Meetings 234, Econometric Society.
  25. repec:cup:etheor:v:13:y:1997:i:6:p:808-17 is not listed on IDEAS
  26. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
  27. Chou, Ray Yeutien, 2005. "Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 561-82, June.
  28. Kenneth D. West & Hali J. Edison & Dongchul Cho, 1992. "A Utility Based Comparison of Some Models of Exchange Rate Volatility," NBER Technical Working Papers 0128, National Bureau of Economic Research, Inc.
  29. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
  30. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
  31. Anatolyev, Stanislav, 2006. "Kernel estimation under linear-exponential loss," Economics Letters, Elsevier, vol. 91(1), pages 39-43, April.
  32. Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
  33. Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 53-89.
  34. Soosung Hwang & John Knight & Stephen E. Satchell, 2001. "Forecasting Nonlinear Functions of Returns Using LINEX Loss Functions," Annals of Economics and Finance, Society for AEF, vol. 2(1), pages 187-213, May.
  35. Kristensen, Dennis & Rahbek, Anders, 2005. "ASYMPTOTICS OF THE QMLE FOR A CLASS OF ARCH(q) MODELS," Econometric Theory, Cambridge University Press, vol. 21(05), pages 946-961, October.
  36. Lee, Sang-Won & Hansen, Bruce E., 1994. "Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 10(01), pages 29-52, March.
  37. Zellner, Arnold, 1985. "Bayesian Econometrics," Econometrica, Econometric Society, vol. 53(2), pages 253-69, March.
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Citations

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Cited by:
  1. Liu, Xiaochun, 2011. "Modeling the time-varying skewness via decomposition for out-of-sample forecast," MPRA Paper 41248, University Library of Munich, Germany.
  2. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).

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