Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....

A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and...

A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and...

Sophisticated algorithmic techniques are complementing human judgement across the fund industry. Whatever the type of rebalancing that occurs in the course of a longer horizon, it probably violates the buy-and-hold assumption. In this article, we develop the methodology to predict, dissect and...

Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....

This paper focuses on portfolio risk forecasting in an asymmetrical framework. Risk is defined by two factors; the dependence structure and the volatility. In order to account for asymmetric dependencies, the return series' interdependence is estimated via a Copula approach rather than the...

We revisit the apparent historical success of technical trading rules on daily prices of the DJIA index from 1897 to 2011, and use the False Discovery Rate as a new approach to data snooping. The advantage of the FDR over existing methods is that it selects more outperforming rules which allows...

The consumption-based models have a lack of predictive power for explaining variability of stock returns. This paper examines two well-known models, Campbell and Cochrane (1999)'s habit model and Bansal and Yaron (2004)'s long-run risks model, to see whether they produce a significant power of...

We present a general method to detect and extract from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality. Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval...