This is my thesis I wrote during my masters at the University of Toronto.
We study an asset allocation problem for a multi-asset fund where multiple decentralized managers implement investment strategies in separate asset classes. To control for portfolio measures at the fund, it is a common practice to follow a traditional asset allocation methodology to obtain optimal target weights and force the investment managers to stay close to the target. However, the sophistication and high level of specialization involved in alternative investment strategies create uncertainty in investment managers achieving the target weight; hence causing misallocations. Therefore, we develop two asset allocation models that provide a range of portfolio allocations (i.e. bounds) for individual investment managers to operate in order to maintain desirable firm wise portfolio measures while accounting for potential misallocations. Also, the proposed optimization problems have potentially large number of constraints, so we suggest a procedure to reduce the number of constraints before the optimization.