Index tracking and portfolio optimization are pivotal techniques in modern financial management, aiming to replicate the performance of a benchmark index while minimising discrepancies and risk.

The portfolio optimization model has limited impact in practice because of estimation issues when applied to real data. To address this, we adapt two machine learning methods, regularization and cross ...

We prove that the portfolio problem with transaction costs is equivalent to three different problems designed to alleviate the impact of estimation error: a robust portfolio optimization problem, a ...

Leveraging the power of quantum computing combined with machine learning intelligence enables the opportunity to solve portfolio optimization problems at scales and speeds previously unthinkable.