We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions...

This paper examines both intertemporal and contemporaneous relationship between excess US Treasury futures returns and realized moments - realized volatility, realized skewness and realized kurtosis using high-frequency data. We find realized skewness to have significant negative effect on...

In this paper we investigate the predictive power of cross-sectional volatility, skewness and kurtosis for future stock returns. Adding to the work of Maio (2016), who finds cross-sectional volatility to forecast a decline in the equity premium with high predictive power in-sample as well as...

We study a consumption-based asset pricing model with incomplete information and a- stable shocks. Incomplete information leads to a non-Gaussian filtering problem. Bayesian updating generates fluctuating confidence in the agents' estimate of the persistent component of the dividends' growth...

In the framework of small-scale agent-based financial market models, the paper starts out from the concept of structural stochastic volatility, which derives from different noise levels in the demand of fundamentalists and chartists and the time-varying market shares of the two groups. It...

The volatility specification of the Markov-switching Multifractal (MSM) model is proposed as an alternative mechanism for realized volatility (RV). We estimate the RV-MSM model via Generalized Method of Moments and perform forecasting by means of best linear forecasts derived via the...

We explore the issue of estimating a simple agent-based model of price formation in an asset market using the approach of Alfarano et al. (2008) as an example. Since we are able to derive various moment conditions for this model, we can apply generalized method of moments (GMM) estimation. We...

We study the well-known multiplicative Lognormal cascade process in which the multiplication of Gaussian and Lognormally distributed random variables yields time series with intermittent bursts of activity. Due to the non-stationarity of this process and the combinatorial nature of such a...

The presence of time series momentum effect has been widely documented in the financial markets across asset classes and countries. We find a predictable pattern of the realized semi-variance to the future individual asset return, especially during the stressed states of time series momentum...