Abstract - Predictive Regression and Robust Hypothesis Testing: Predictability Hidden by Anomalous Observations

[Translate to Englisch:] Testing procedures for predictive regressions with lagged autoregressive variables imply a suboptimal inference in presence of small violations of ideal assumptions. We propose a novel testing framework resistant to such violations, which is consistent with nearly integrated regressors and applicable to multi-predictor settings, when the data may only approximately follow a predictive regression model. The Monte Carlo evidence demonstrates large efficiency improvements of our approach, while the empirical analysis produces a strong robust evidence of market return predictability, using predictive variables such as the dividend yield, the volatility risk premium or labor income.

Fabio Trojani
Swiss Finance Institute, University of Lugano
08.May 2012

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