Robust portfolio optimization refers to finding an asset allocation strategy whose behavior
under the worst possible realizations of the uncertain inputs, eg, returns and covariances, is …

The concepts of portfolio optimization and diversification have been instrumental in the
development and understanding of financial markets and financial decision making. In light …

Robust models have a major role in portfolio optimization for resolving the sensitivity issue of
the classical mean–variance model. In this paper, we survey developments of worst-case …

Machine learning (ML) is progressively reshaping the fields of quantitative finance and
algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers …

This paper reviews recent advances in robust portfolio selection problems and their
extensions, from both operational research and financial perspectives. A multi-dimensional …

While portfolio optimization is generally based on the return and risk of a portfolio, goal-
based investing primarily focuses on achieving financial goals of individuals, which has …

This paper uses a novel numerical optimization technique–robust optimization–that is well
suited to solving the asset–liability management (ALM) problem for pension schemes. It …

Robust optimization has become a widely implemented approach in investment
management for incorporating uncertainty into financial models. The first applications were …

As the largest coal and the second largest crude oil consumer in the world, China has urgent
task to develop its renewable energy industry quickly. By now, there are over 80 renewable …

This paper formulates a relaxed risk parity optimization model to control the balance of risk
parity violation against the total portfolio performance. Risk parity has been criticized as …