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Mixing Frequencies : Stock Returns as a Predictor of Real Output Growth

Author

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  • Anthony S. Tay

    (SMU)

Abstract

We investigate two methods for using daily stock returns to forecast, and update forecasts of, quarterly real output growth. Both methods aggregate daily returns in some manner to form a single stock market variable. We consider (i) augmenting the quarterly AR(1) model for real output growth with daily returns using a nonparametric Mixed Data Sampling (MIDAS) setting, and (ii) augmenting the quarterly AR(1) model with the most recent r -day returns as an additional predictor. We find that our mixed frequency models perform well in forecasting real output growth.

Suggested Citation

  • Anthony S. Tay, 2006. "Mixing Frequencies : Stock Returns as a Predictor of Real Output Growth," Macroeconomics Working Papers 22480, East Asian Bureau of Economic Research.
  • Handle: RePEc:eab:macroe:22480
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    File URL: http://www.eaber.org/node/22480
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    References listed on IDEAS

    as
    1. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    2. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    3. Clements, Michael P & Galv√£o, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data : Forecasting US output growth and inflation," The Warwick Economics Research Paper Series (TWERPS) 773, University of Warwick, Department of Economics.
    4. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
    5. Ramsay, James O. & Ramsey, James B., 2002. "Functional data analysis of the dynamics of the monthly index of nondurable goods production," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 327-344, March.
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    Cited by:

    1. Franco, Ray John Gabriel & Mapa, Dennis S., 2014. "The Dynamics of Inflation and GDP Growth: A Mixed Frequency Model Approach," MPRA Paper 55858, University Library of Munich, Germany.
    2. repec:dug:actaec:y:2017:i:5:p:169-188 is not listed on IDEAS
    3. repec:eee:touman:v:46:y:2015:i:c:p:454-464 is not listed on IDEAS

    More about this item

    Keywords

    Forecasting; Mixed Data Sampling; Functional linear regression; Test for Superior Predictive Ability;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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