Present value calculations require predictions of cash flows both at near and distant future points in time. Such predictions are generally surrounded by considerable uncertainty and may critically depend on assumptions about parameter values as well as the form and stability of the data...

Present value calculations require predictions of cash flows both at near and distant future points in time. Such predictions are generally surrounded by considerable uncertainty and may critically depend on assumptions about parameter values as well as the form and stability of the data...

This paper reconsiders the effect of investor sentiment on stock prices. Using survey-based sentiment indicators from Germany and the US we confirm previous findings of predictability at intermediate time horizons. The main contribution of our paper is that we also analyze the immediate price...

Bayesian learning provides the core concept of processing noisy information. In standard Bayesian frameworks, assessing the price impact of information requires perfect knowledge of news' precision. In practice, however, precision is rarely dis- closed. Therefore, we extend standard Bayesian...

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only...

We construct a slope factor from changes in federal funds futures of different horizons. Slope predicts stock returns at the weekly frequency: faster monetary policy easing positively predicts excess returns. Investors can achieve increases in weekly Sharpe ratios of 20% conditioning on the...

We propose a new measure of the expected variance risk premium that is based on a forecast of the conditional variance from a GARCH-MIDAS model. We find that the new measure has strong predictive ability for future U.S. aggregate stock market returns and rationalize this result by showing that...

Suppose a fund manager uses predictors in changing port-folio allocations over time. How does predictability translate into portfolio decisions? To answer this question we derive a new model within the Bayesian framework, where managers are assumed to modulate the systematic risk in part by...

This paper extends the benchmark Macro-Finance model by introducing, next to the standard macroeconomic factors, additional liquidity-related and return forecasting factors. Liquidity factors are obtained from a decomposition of the TED spread while the return-forecasting (risk premium) factor...

This paper extends the benchmark Macro-Finance model by introducing, next to the standard macroeconomic factors, additional liquidity-related and return forecasting factors. Liquidity factors are obtained from a decomposition of the TED spread while the return-forecasting (risk premium) factor...