Empirical findings related to the time series properties of stock returns volatility indicate autocorrelations that decay slowly at long lags. In light of this, several long-memory models have been proposed. However, the possibility of level shifts has been advanced as a possible explanation for...

Extending previous work on mutual fund pricing, this paper introduces the idea of modeling the conditional distribution of mutual fund returns using a fat tailed density and a time-varying conditional variance. This approach takes into account the stylized facts of mutual fund return series,...

The variance risk premium represents the compensation paid to index option sellers for the risk of losses following upward movements in realized market return volatility. Common wisdom connects these spikes with elevated uncertainty on economic fundamentals. I incorporate this link within a...

Based on the fact that realized measures of volatility are affected by measurement errors, we introduce a new family of discrete-time stochastic volatility models having two measurement equations relating both observed returns and realized measures to the latent conditional variance. A...

Many consumption-based models succeed in matching long lists of asset price moments. We propose an alternative, full-information Bayesian evaluation that decomposes the price-dividend ratio (p/d) into contributions from long-run risks, habit, and a residual. We find that long-run risks account...

Unexpected shifts in the realized stock market volatility, often associated with financial crises, carry a significantly negative risk premium across stocks and Treasuries, which suggests the existence of a unified pricing model. Investors require a premium for holding the risky assets (stocks),...

The DCF (Discounted Cash flow) Model provides the theoretical background for the possible impact of interest rate changes on equity prices. This paper examines the spillover effects from the movement of short term interest rates to equity markets within the Euro area. The empirical study is...

We examine the effects of parameter uncertainty and Bayesian learning on equilibrium asset prices when all the structural parameters of the aggregate consumption and dividend growth rate processes are unknown. With realistic calibration of a parsimonious set of prior parameters, the model...

We estimate a generalized version of the Long-Run Risk model in a panel of developed and developing countries using consumption, dividend growth, and asset returns data by utilizing the particle filter, while allowing for measurement errors in consumption data at quarterly and annual...

We embed a news shock, a noisy indicator of the future state, in a two-state Markov-switching growth model. Our framework, combined with parameter learning, features rich history-dependent uncertainty dynamics. We show that bad news that arrives during a prolonged economic boom can trigger a...