It is often argued that intraday returns can be used to construct covariance estimates that are more accurate than those based on daily returns. However, it is still unclear whether high frequency data provide more precise covariance estimates in markets more contaminated from microstructure...

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...