Masterarbeit, 2011
32 Seiten, Note: 81 %
This work explores the concept of predictive regressions and its application in forecasting stock returns using dividend yields. The main objective is to assess whether the predictive power of dividend yields is stable over time, particularly focusing on the presence of structural breaks. The study aims to determine if the excess stock returns are predictable using dividend yields and if this predictability is consistent over time. The analysis also seeks to identify potential structural breaks in the model and analyze their impact on predictive power.
The main keywords and focus topics of this work include linear predictive regressions, dividend yields, stock returns, structural breaks, Wald test, SupWald statistic, predictive power, financial markets, economic forecasting, and econometric methodology.
It is an econometric model used to forecast a noisy explained variable (like stock returns) using a lagged, persistent regressor (like the dividend-price ratio).
The study investigates this possibility, noting that while dividend yields are often used as predictors, their predictive power can be unstable due to structural breaks in the market.
Structural breaks are sudden shifts in the relationship between variables, often caused by major economic events, which can make historical forecasting models inaccurate.
The framework uses statistical tests like the Wald test and the SupWald statistic to identify the location and significance of potential breaks in the model's coefficients.
In econometrics, persistence means the variable's current value is highly correlated with its past values, often behaving similarly to a unit root process, which requires specific modeling techniques.
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