There is a generalized conviction that variation in dividend yields is exclusively related to expected returns and not to expected dividend growth - e.g. Cochrane's presidential address (Cochrane (2011)). We show that this pattern, although valid for the aggregate stock market, is not true for...

This paper studies the information content of some Ifo indicators. In particular, we investigate whether two Ifo indicators, one on the current business situation, the other on current production development, provide information on revisions of German industrial production. A new feature of our...

This paper studies the information content of some Ifo indicators. In particular, we investigate whether two Ifo indicators, one on the current business situation, the other on current production development, provide information on revisions of German industrial production. A new feature of our...

This paper studies the information content of some Ifo indicators. In particular, we investigate whether two Ifo indicators, one on the current business situation, the other on current production development, provide information on revisions of German industrial production. A new feature of our...

Recent empirical evidence suggests that the variance risk premium predicts aggregate stock market returns. We demonstrate that statistical finite sample biases cannot “explain” this apparent predictability. Further corroborating the existing evidence of the U.S., we show that country...

Recent empirical evidence suggests that the variance risk premium predicts aggregate stock market returns. We demonstrate that statistical finite sample biases cannot “explain” this apparent predictability. Further corroborating the existing evidence of the U.S., we show that country...

Rogers-Satchell (RS) measure is an efficient volatility measure. This paper proposes quantile RS (QRS) measure to ensure robustness and correct the downward bias of RS measure with an additive term. Moreover scaling factors are provided for different interquantile ranges to ensure unbiasedness....

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

We develop a novel method to impose constraints on univariate predictive regressions of stock returns. Unlike the previous approaches in the literature, we implement our constraints directly on the predictor, setting it to zero whenever its value falls below the variable's past 12-month high....