We have previously developed a fixed-income sector optimization methodology to facilitate tradeoffs between various sectors based on their contribution to the total portfolio return and risk. We maximize portfolio return subject to constraints including value-at-risk (VaR) and other downside risk measures, both absolute and relative to a benchmark (market and liability-based). Our method optimizes interest rate, curve, credit, and volatility exposures to achieve the highest expected return (view-oriented, historically based, or quantitatively forecast) within the allowed risk space defined by various specified risk constraints. This work advances the state-of-the-art in the risk-controlled optimization process for cases where there are a large number of subsector decision variables. These advances include: 1) introduction of a multi-level optimization process to avoid ill-conditioned joint risk characterization of a large number of subsectors, and to reduce required length of time histories, 2) refinement of our previous VaR and CVaR methodologies to add opportunistic nondollar bonds as well as high yield and emerging markets, and 3) ability to control risk at subsector levels as well as the total portfolio.
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