Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach

Abstract:

Asset prices reflect expectations of future economic conditions. In this study, we use the property of asset prices, especially stock prices, to forecast the GDP growth rate in Japan. For optimal use of the rich time-series and cross-sectional information of stock prices, we combine MIDAS (mixed-data sampling) regression and factor analysis to examine which dimensions of information contribute to the accuracy of the GDP growth rate forecast. Our results show that the use of factors significantly improves forecast accuracy and that extracting factors from a broader set of stock prices further improves accuracy. This highlights the important role of cross-sectional stock market information in forecasting macroeconomic activity.