Using data from the S&P 500 stocks from 1990 to 2015, we address the uncertainty of distribution of assets' returns in Conditional Value-at-Risk (CVaR) minimization model by applying multidimensional mixed Archimedean copula function and obtaining its robust counterpart. We implement a dynamic...

Statistical arbitrage strategies, such as pairs trading and its generalizations, rely on the construction of mean- reverting spreads with a certain degree of predictability. This paper applies cointegration tests to identify stocks to be used in pairs trading strategies. In addition to...

We propose an economically motivated forecast combination strategy in which model weights are related to portfolio returns obtained by a given forecast model. An empirical application based on an optimal mean-variance bond portfolio problem is used to highlight the advantages of the proposed...

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 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...

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...