Portfolio management using traditional machine learning algorithms

Classical implementation

Portfolio optimization is a problem related to the financial services and banking industry that emerged with Markovitz’s seminal paper in 1952 (https://onlinelibrary.wiley.com/doi/full/10.1111/j.1540-6261.1952.tb01525.x). The model describes a set of assets x i ∈ X from which a subset needs to be picked to maximize the revenue, while minimizing the risk at 𝑡 future time steps. For a given period, each asset has an expected return linked to it, and the covariance between assets sets the risk amount in terms of diversification (for the sake of simplicity). The idea behind this diversification is that if we only invest in the assets with the highest revenue, the risk of them being driven by the same factors if our investment fails is bigger than if we diversify our portfolio. We will focus on a single-time-step process, assuming that local optima are part of the longer...