Discussion on the state of the stock market and the current market cycle is an ongoing debate in financial literature. Trying to time the market correctly has proven to be a difficult task even for professional investors. No perfect guide or rule has yet to emerge that would consistently predict shifts in market cycles has yet been discovered.
The purpose of this thesis is to study the ability to predict bear market cycles using dividend yields. Two different market indices are studied, the S&P 500 and the OMX Helsinki. The data sample consists of monthly observations covering the period 1989-2021. The empirical part of this paper is divided into two parts. First, we study if the dividend yields have any return predicta-bility abilities. Secondly, we study if the dividend yields can be used to forecast future bear mar-kets.
Previous literature has been inconclusive of the predictive power of dividend yields for stock re-turns. While stock return predictability using financial variables has gained a lot of attention in the literature, some recent studies have shifted the focus to bear market predictability. Forecast-ing shifts in market cycles can be a considerable benefit for investors. The hypothesis is that low dividend yields can forecast future low returns.
The results of this paper are divided. Dividend yields show no significant predictive power for the S&P 500. The results for the bear market predictability are similar. For the OMX Helsinki index, the results are more complicated. The results show a negative correlation between the dividend yield and market return, which is against the original hypothesis. There is also evidence for bear market predictability using dividend yields
