Case Study: Portfolio Optimisation for an Asset Manager

Client

A buy-side asset manager.

Problem

The client faced significant challenges in optimising portfolios under complex constraints. Traditional optimization methods were inadequate for handling cardinality constraints and risk constraints to the client’s specifications. These limitations resulted in suboptimal asset allocations, impacting the ability to maximise returns while controlling risk.

How We Helped

We developed an end-to-end bespoke global optimisation solution for the client’s portfolio optimisation problem. Our solution uniquely handled the mathematical complexities of an extended Markowitz model, which included cardinality constraints and tracking error constraints. This advanced capability enabled the client to accurately model and solve optimization problems that were previously unsolvable.

Impact

By accurately solving non-convex optimization problems, the client could now generate Pareto frontiers for portfolios with fixed cardinalities, achieving much better risk-return trade-offs. This allowed the client to identify optimal asset combinations and make more informed investment decisions. As a result, the client experienced significant enhancements in portfolio performance, with a marked increase in returns and better risk management. Our approach provided clarity and precision that heuristic methods could not match, ensuring that the client’s strategies were both robust and reliable.