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.
Original language | English |
---|---|
Article number | 20160151 |
Journal | Studies in Nonlinear Dynamics and Econometrics |
Volume | 23 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2019 |
Bibliographical note
Funding Information:We would like to thank Bruce Mizrach (the Editor), an Associate Editor, and two anonymous referees for their insightful comments and suggestions on an earlier draft of this article. This work was supported by the 2015 Research Fund of the University of Seoul for Yunmi Kim.
Publisher Copyright:
© 2019 Walter de Gruyter GmbH, Berlin/Boston 2019.
Keywords
- "volatility feedback news" effects
- expected returns
- macroeconomic factors
- market volatility
- regime-switching
ASJC Scopus subject areas
- Analysis
- Social Sciences (miscellaneous)
- Economics and Econometrics