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Factor analysis of permanent and transitory dynamics of the US economy and the stock market

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  • Zeynep Senyuz

Abstract

We analyze dynamics of the permanent and transitory components of the U.S. economic activity and the stock market obtained by multivariate dynamic factor modeling. We capture asymmetries over the phases of economic and stock market trends and cycles using independent Markov-switching processes. We show that both output and stock prices contain significant transitory components, while consumption and dividends are useful to identify their respective permanent components. The extracted economic trend perfectly predicts all post-war recessions. Our results shed light to the nature of the bilateral predictability of the economy and the stock market. The transitory stock market component signals recessions with an average lead of one quarter, whereas the market trend is correlated with the economic trend with varying lead/lag times.
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  • Zeynep Senyuz, 2011. "Factor analysis of permanent and transitory dynamics of the US economy and the stock market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 975-998, September.
    • Handle: RePEc:wly:japmet:v:26:y:2011:i:6:p:975-998
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    Cited by:

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    2. Andrew C. Chang & Phillip Li, 2015. "Is Economics Research Replicable? Sixty Published Papers from Thirteen Journals Say \"Usually Not\"," Finance and Economics Discussion Series 2015-83, Board of Governors of the Federal Reserve System (U.S.).
    3. Richard G. Anderson & Marcelle Chauvet & Barry Jones, 2015. "Nonlinear Relationship Between Permanent and Transitory Components of Monetary Aggregates and the Economy," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 228-254, February.
    4. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2015. "What does financial volatility tell us about macroeconomic fluctuations?," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 340-360.
    5. Chauvet, Marcelle & Senyuz, Zeynep, 2016. "A dynamic factor model of the yield curve components as a predictor of the economy," International Journal of Forecasting, Elsevier, vol. 32(2), pages 324-343.
    6. MeiChi Huang & Tzu-Chien Wang, 2015. "Housing-bubble vulnerability and diversification opportunities during housing boom–bust cycles: evidence from decomposition of asset price returns," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(2), pages 605-637, March.
    7. James Morley & Irina B. Panovska & Tara M. Sinclair, 2014. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41B, School of Economics, The University of New South Wales.
    8. MeiChi Huang & LinYing Yeh, 2015. "Should the Fed take extra action for the recent housing bubble? Evidence from asymmetric transitory shocks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 762-781, October.
    9. James Morley & Irina B. Panovska & Tara M. Sinclair, 2013. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41A, School of Economics, The University of New South Wales.
    10. Wu, Ruirui & Qin, Zhongfeng & Liu, Bing-Yue, 2022. "A systemic analysis of dynamic frequency spillovers among carbon emissions trading (CET), fossil energy and sectoral stock markets: Evidence from China," Energy, Elsevier, vol. 254(PA).

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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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