In this paper, we analyze the forecasting performance of several parametric extensions of the popular Dynamic Nelson-Siegel (DNS) model for the yield curve. Our focus is on the role of additional and time-varying decay parameters, conditional heteroscedasticity, and macroeconomic variables. We...

We devise a novel approach to combine predictions of high dimensional conditional covariance matrices using economic criteria based on portfolio selection. The combination scheme takes into account not only the portfolio objective function but also the portfolio characteristics in order to...

We propose a novel approach to measure risk in fixed income portfolios in terms of value-at-risk (VaR). We use closed-form expressions for the vector of expected bond returns and for the covariance matrix of bond returns based on a general class of well established term structure factor models,...

Dynamic factor models for the yield curve have been extensively applied to fit and forecast the yield curve. We propose a novel utilization of these models in bond portfolio optimization. Specifically, we derive closed-form expressions for the vector of expected bond returns and for its...

We present a semiparametric portfolio optimization method in which portfolio weights are parameterized as a non-linear function of firm characteristics. This approach generalizes the linear parametric portfolio policy of Brandt et al. (2009) and can be applied to high-dimensional problems at a...

Two crucial aspects to the problem of portfolio selection are the specification of the model for expected returns and their covariances, as well as the choice of the investment policy to be adopted. A common trade-off is to consider dynamic covariance specifications vis-a-vis static models such...