Predicting GDP Growth with Stock and Bond Markets: Do They Contain Different Information?

Citation

McMillan D (2021) Predicting GDP Growth with Stock and Bond Markets: Do They Contain Different Information?. International Journal of Finance and Economics, 26 (3), pp. 3651-3675. https://doi.org/10.1002/ijfe.1980

Abstract
This paper examines the ability of bond and stock markets to predict subsequent GDP growth over a range of horizons for twelve international countries. The results, using linear, probit, time- and regime-varying in-sample regressions and out-of-sample forecasting, confirm the view that both financial markets exhibit predictive power for future output growth. Moreover, there is notable variation within the strength of the predictive relation, for example, predictive power increases during the financial crisis period. Results suggest that while the term structure arguably exhibits stronger predictive power, both series contain distinct predictive information. Notably, predictive power emanating from the stock return series appears stronger over shorter (up to four-quarter) time horizons, while the term structure series exhibits more consistent predictive power over a range of horizons. Considering different regimes, we observe that the bond market exhibits greater predictive power for a flatter yield curve and lower stock prices relative to fundamentals, while the stock market exhibits greater predictive power for a steeper yield curve and higher relative stock prices. This suggests that the two financial markets exhibit different information content for future output growth. This view is further supported by forecast results whereby a model that includes both financial series outperforms a model that only includes one. Forecast encompassing tests further support the view that stock returns contain additional information over that presented by the term structure alone.

Keywords
Stocks; Bonds; GDP Growth; Predictabilit;, Forecasting; Variation

Journal
International Journal of Finance and Economics: Volume 26, Issue 3

• Gdp Ts R Revised