Global Asset Allocation with Multirisk Considerations

Abstract

Multirisk asset allocations help investors optimally balance their desire for expected return with their aversion to two types of risk—absolute volatility and tracking error relative to a benchmark. Zhang empirically tests a multirisk optimization model by allocating funds among global equity markets. The results suggest that mean– variance tracking error optimization may provide more efficient portfolios than the traditional approach of mean–variance with constraints.