Can stock returns be predicted? This master's thesis investigates the question empirically for the German stock market. Using monthly price data for all DAX constituents from 1983 to 2013, it develops and tests its own forecasting models: a multivariate regression based on micro- and macroeconomic variables (P/E ratio, EPS, credit spread, oil price, GDP and others), an ARMA time-series model and a naive benchmark. The complete methodology is demonstrated using the BASF share, with forecasting quality assessed through in-sample and out-of-sample tests via RMSE, MAE and MAPE.
The study first provides a solid grounding in the theoretical foundations — capital market efficiency, portfolio management, technical and fundamental analysis — together with a comprehensive literature review. The findings are as honest as they are insightful: over the long run, returns can be approximately explained by a few economic factors, while in the short run the market remains largely unpredictable. Essential reading for economics and finance students, analysts and anyone interested in quantitative equity valuation.
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- Marc Seibert (Autor), 2015, Are stock returns predictable?, Múnich, GRIN Verlag, https://www.grin.com/document/1737281