Adaptively combined forecasting for discrete response time series
Adaptive combining is generally a desirable approach for forecasting, which, however, has rarely been explored for discrete response time series. In this paper, we propose an adaptively combined forecasting method for such discrete response data. We demonstrate in theory that the proposed forecast is of the desired adaptation with respect to the widely used squared risk and other significant risk functions under mild conditions. Furthermore, we study the issue of adaptation for the proposed forecasting method in the presence of model screening that is often useful in applications. Our simulation study and two real-world data examples show promise for the proposed approach.
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- George Monokroussos, 2011.
"Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy,"
Journal of Money, Credit and Banking,
Blackwell Publishing, vol. 43, pages 519-534, 03.
- George Monokroussos, 2005. "Dynamic Limited Dependent Variable Modeling and US Monetary Policy," Computing in Economics and Finance 2005 460, Society for Computational Economics.
- George Monokroussos, 2006. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Discussion Papers 06-02, University at Albany, SUNY, Department of Economics.
- Zou, Hui & Yang, Yuhong, 2004. "Combining time series models for forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 69-84.
- David Hirshleifer & Tyler Shumway, 2003. "Good Day Sunshine: Stock Returns and the Weather," Journal of Finance, American Finance Association, vol. 58(3), pages 1009-1032, 06.
- David Hirshleifer & TYLER G. SHUMWAY, 2004. "Good Day Sunshine: Stock Returns and the Weather," Finance 0412004, EconWPA.
- Yuan, Zheng & Yang, Yuhong, 2005. "Combining Linear Regression Models: When and How?," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1202-1214, December.
- Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
- Victor Aguirregabiria & Pedro mira, 2007. "Dynamic Discrete Choice Structural Models: A Survey," Working Papers tecipa-297, University of Toronto, Department of Economics.
- Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3455-3480.
- Carlo Altavilla & Paul De Grauwe, 2006. "Forecasting and Combining Competing Models of Exchange rate Determination," Discussion Papers 5_2006, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
- Carlo Altavilla & Paul De Grauwe, 2006. "Forecasting and Combining Competing Models of Exchange Rate Determination," CESifo Working Paper Series 1747, CESifo Group Munich.
- Michael J. Dueker, 1999. "Measuring monetary policy inertia in target Fed funds rate changes," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 3-10.
- Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
- Francis X. Diebold & Glenn D. Rudebusch, 1987. "Scoring the leading indicators," Special Studies Papers 206, Board of Governors of the Federal Reserve System (U.S.).
- Hansen, Bruce E., 2008. "Least-squares forecast averaging," Journal of Econometrics, Elsevier, vol. 146(2), pages 342-350, October.
- Zvi Eckstein & Kenneth I. Wolpin, 1989. "The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 24(4), pages 562-598.
- Granger, Clive W.J. & Machina, Mark J., 2006. "Forecasting and Decision Theory," Handbook of Economic Forecasting, Elsevier.
- Leung, Mark T. & Daouk, Hazem & Chen, An-Sing, 2000. "Forecasting stock indices: a comparison of classification and level estimation models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 173-190.
- Yang, Yuhong, 2004. "Combining Forecasting Procedures: Some Theoretical Results," Econometric Theory, Cambridge University Press, vol. 20(01), pages 176-222, February.
- Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578.
- Ou, Jane A. & Penman, Stephen H., 1989. "Financial statement analysis and the prediction of stock returns," Journal of Accounting and Economics, Elsevier, vol. 11(4), pages 295-329, November.
- Yang Y., 2001. "Adaptive Regression by Mixing," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 574-588, June.
- Wan, Alan T.K. & Zhang, Xinyu & Zou, Guohua, 2010. "Least squares model averaging by Mallows criterion," Journal of Econometrics, Elsevier, vol. 156(2), pages 277-283, June.
- Akhtar, Sohail & Scarf, Philip, 2012. "Forecasting test cricket match outcomes in play," International Journal of Forecasting, Elsevier, vol. 28(3), pages 632-643.
- Hansen, Bruce E. & Racine, Jeffrey S., 2012. "Jackknife model averaging," Journal of Econometrics, Elsevier, vol. 167(1), pages 38-46.
- Liang, Hua & Zou, Guohua & Wan, Alan T. K. & Zhang, Xinyu, 2011. "Optimal Weight Choice for Frequentist Model Average Estimators," Journal of the American Statistical Association, American Statistical Association, vol. 106(495), pages 1053-1066.
- repec:taf:jnlbes:v:30:y:2012:i:1:p:132-142 is not listed on IDEAS
- Henry W. Chappell, Jr. & Rob Roy McGregor & Todd A. Vermilyea, 2007. "The Role of the Bias in Crafting Consensus: FOMC Decision Making in the Greenspan Era," International Journal of Central Banking, International Journal of Central Banking, vol. 3(2), pages 39-60, June.
- David E. Rapach & Jack K. Strauss, 2008. "Forecasting US employment growth using forecast combining methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 75-93.
- Bruce E. Hansen, 2007. "Least Squares Model Averaging," Econometrica, Econometric Society, vol. 75(4), pages 1175-1189, 07.
- Ghosh, D. & Yuan, Z., 2009. "An improved model averaging scheme for logistic regression," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1670-1681, September. Full references (including those not matched with items on IDEAS)
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