Machine Learning and Financial Planning

The area of finance has been relatively immune to the ML technology, except for a few exceptions such as high-frequency trading and credit scoring for loans. Significant financial decisions are made with reference to formal decision models. The first, and most famous, example is the Markowitz portfolio model. This model has been endlessly enhanced. Institutional investors build structured asset allocation and asset-liability management models for a variety of reasons, including the desire to improve performance and others, such as satisfying governance procedures. Regulators may charge institutional investors with imprudence if there is no formal analysis of their portfolio selection decisions and large losses occur. Due to the levels of uncertainties and time-lags in strategic decisions, it can be difficult to evaluate the quality of the recommendations, thus complicating the search for ML breakthroughs. Recall the need for measurements of correctness in supervised learning.