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Predicting US recessions with leading indicators via neural network models

  • Qi, Min
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    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 17 (2001)
    Issue (Month): 3 ()
    Pages: 383-401

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    Handle: RePEc:eee:intfor:v:17:y:2001:i:3:p:383-401
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    1. Arturo Estrella & Frederic S. Mishkin, 1995. "Predicting U.S. Recessions: Financial Variables as Leading Indicators," NBER Working Papers 5379, National Bureau of Economic Research, Inc.
    2. Kling, John L, 1987. "Predicting the Turning Points of Business and Economic Time Series," The Journal of Business, University of Chicago Press, vol. 60(2), pages 201-38, April.
    3. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-75, July.
    4. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
    5. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-91, July.
    6. Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 347-359, October.
    7. Garcia, Rene & Gencay, Ramazan, 2000. "Pricing and hedging derivative securities with neural networks and a homogeneity hint," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 93-115.
    8. Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994. " A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks," Journal of Finance, American Finance Association, vol. 49(3), pages 851-89, July.
    9. Arturo Estrella, 1997. "A new measure of fit for equations with dichotomous dependent variables," Research Paper 9716, Federal Reserve Bank of New York.
    10. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
    11. Andrew J. Filardo, 1999. "How reliable are recession prediction models?," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 35-55.
    12. Qi, Min, 1999. "Nonlinear Predictability of Stock Returns Using Financial and Economic Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 419-29, October.
    13. Vishwakarma, Keshav P, 1994. "Recognizing Business Cycle Turning Points by Means of a Neural Network," Computational Economics, Society for Computational Economics, vol. 7(3), pages 175-85.
    14. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
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