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A unified framework jointly explaining business conditions, stock returns, volatility and “volatility feedback news” effects

Author

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  • Kim Chang-Jin

    (Department of Economics, University of Washington, Seattle, WA 98195, USA)

  • Kim Yunmi

    (Department of Economics, University of Seoul, Seoul 02504, Korea)

Abstract

One of central questions to macroeconomics and finance has been whether macroeconomic factors are useful predictors for expected stock returns. The general consensus is somewhat surprising in that financial factors, rather than macroeconomic factors, have predictive power on stock returns. Such predictability of financial factors is justified on the ground that those factors can act as a proxy for future business conditions and undiversifiable risk. Hence, they should be priced in terms of expected returns. However, as suggested by Campbell, S., and F. Diebold. 2009. “Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence.” Journal of Business & Economic Statistics 27 (2): 266–278, such a justification can be puzzling because macroeconomic factors are likely to have a closer and more direct link to future business conditions than financial factors. In this paper, we will attempt to solve this puzzling problem by accounting for market volatility when measuring the relationship between stock returns and macroeconomic factors. As a result, we propose a unified framework in which the three components of macroeconomic factors, market volatility, and stock returns are jointly embedded.

Suggested Citation

  • Kim Chang-Jin & Kim Yunmi, 2019. "A unified framework jointly explaining business conditions, stock returns, volatility and “volatility feedback news” effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-14, April.
    • Handle: RePEc:bpj:sndecm:v:23:y:2019:i:2:p:14:n:3
    DOI: 10.1515/snde-2016-0151
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    References listed on IDEAS

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    More about this item

    Keywords

    expected returns; macroeconomic factors; market volatility; regime-switching; “volatility feedback news” effects;
    All these keywords.

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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