This thesis investigates macroeconomic variables as stock return predictors inspired by Møller et al. (2020).We introduce three novel macroeconomic predictor variables –cyclical GDP, cyclical industrial production, and cyclical investment –and show that they capture a significant fraction of the variation in expected stock returns at various horizons ranging from one quarter to five years over the postwar period. Their predictive properties are in general terms on the same level as cyclical consumption presented by Møller et al. (2020). The results imply that the cyclical component of consumption is not unique as stock return predictor relative to the cyclical component of other macroeconomic aggregates, such as GDP, industrial production, and investment. Furthermore, the findings constitute new evidence of time-varying risk premia that link stock return predictability directly to fluctuations in GDP, industrial production, and investment. In other words, our empirical evidence lends support to the idea that stock return predictability is the rational response to changing business conditions. When GDP, industrial production, and investment increase, stock prices rise, and future expected returns fall and vice versa. This is consistent with the theoretical explanations of asset prices and the role of habit formation by Campbell and Cochrane (1999). Lastly, using the cyclical macroeconomic variables, we present forecasts of the expected annual return from stocks over the next five years. Our results reveal that returns are expected to be low.
|Educations||MSc in Applied Economics and Finance, (Graduate Programme) Final Thesis|
|Number of pages||155|