Bayesian Model Averaging (BMA) has recently been discussed in the financial literature as an effective way to account for model uncertainty. In this paper we compare BMA to a new model uncertainty framework introduced by Yang (2004), called Aggregate Forecasting Through Exponential Reweighting,...

We evaluate how non-normality of asset returns and the temporal evolution of volatility and higher moments affects the conditional allocation of wealth. We show that if one neglects these aspects, as would be the case in a mean-variance allocation, a significant cost would arise. The performance...

Economic cycles are the key credit portfolio risk driver and they are autocorrelated over time. We then show that it is economically meaningful to define risk for credit portfolios in a multi period setup. Since one period expected shortfall fails to measure risk adequately in a multi period...

We prove that under very weak conditions optimal financial products have to be co-monotone with the inverted state price density. Optimality is meant in the sense of the maximization of an arbitrary preference model, e.g. Expected Utility Theory or Prospect Theory. The proof is based on methods...

The paper examines a dynamic model of a financial market with endogenous asset prices determined by short run equilibrium of supply and demand. Assets pay dividends that are partially consumed and partially reinvested. The traders use fixed-mix investment strategies (portfolio rules),...

This paper analyzes competition between mutual funds in a multiple fundsversion of the model of Hugonnier and Kaniel [18]. We characterize the setof equilibria for this delegated portfolio management game and show thatthere exists a unique Pareto optimal equilibrium. The main result of thispaper...

This paper conducts an empirical analysis of the heterogeneity of recessions in monthly U.S. coincident and leading indicator variables. Univariate Markovswitching models indicate that it is appropriate to allow for two distinct recession regimes, corresponding with 'mild' and 'severe'...

This paper presents new results on the identification of heteroskedastic structural vector autoregressive (HSVAR) models. Point identification of HSVAR models fails when some shifts in the variances of the structural shocks are suspected to be statistically indistinguishable from each other....

Markov models introduce persistence in the mixture distribution. In time series analysis, the mixture components relate to different persistent states characterizing the state-specific time series process. Model specification is discussed in a general form. Emphasis is put on the functional form...

We propose a novel Bayesian model combination approach where the combination weights depend on the past forecasting performance of the individual models entering the combination through a utility-based objective function. We use this approach in the context of stock return predictability and...