We examine asset prices in a representative-agent model of general equilibrium. Assuming only that individuals are risk averse, we determine conditions on the changes in asset risk that are both necessary and sufficient for the asset price to fall. We show that these conditions neither imply,...

This paper is concerned with empirical and theoretical basis of the Efficient Market Hypothesis (EMH). The paper begins with an overview of the statistical properties of asset returns at different frequencies (daily, weekly and monthly), and considers the evidence on return predictability, risk...

This paper shows that non-linearities imposed by a neoclassical production function alone can generate time-varying and asymmetric risk premia over the business cycle. These (empirical) key features become relevant, and asset market implications improve substantially when we allow for...

We analyze optimal monetary policy and its implications for asset prices, when aggregate demand has inertia and responds to asset prices with a lag. If there is a negative output gap, the central bank optimally overshoots aggregate asset prices (asset prices are initially pushed above their...

We study the role of asset revaluation in the monetary transmission mechanism. We build an analytical heterogeneous-agents model with two main ingredients: i) rare disasters; ii) heterogeneous beliefs. The model captures time-varying risk premia and precautionary savings in a setting that nests...

We study optimal monetary policy during temporary supply contractions when aggregate demand has inertia and expansionary policy is constrained. In this environment, it is optimal to run the economy hot until supply recovers. Positive output gaps in the low-supply phase lessen the negative output...

We estimate the transmission of the pandemic shock in 2020 to prices in the residential and commercial real estate market by causal machine learning, using new granular data at the municipal level for Germany. We exploit differences in the incidence of Covid infections or short-time work at the...

We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with existing approaches. We conduct a systematic comparison of their predictive accuracy in settings with different cross-sectional (N) and time (T) dimensions and varying degrees of...