This article illustrates, by means of a case study, how the recently released Optimizer module of Cosmos-Global can be used to construct global fixed income portfolios. The basic approach the Cosmos Global Optimizer takes is mean-variance optimization. The user may define additional regulatory or investment policy constraints.
Risk aversion depends on the investor's preferences.
It measures the investor's tradeoff between return and risk. A portfolio generated with a high risk aversion will be close to the benchmark, while a risk aversion of zero will give the highest-returning portfolio without regard to risk. Investors may not have a precise estimate for their respective risk aversions. Fortunately, as we'll see, the Optimizer can also generate an efficient frontier of portfolios with different risk aversions, each of which has the highest level of return for its level of risk. In addition to risk and return parameters, the case discussed below also includes transaction costs and constraints.