Raymond Yeh

Comparison of Portfolio Optimisation Techniques — Monte Carlo vs SLSQP vs Bayesian

Goal

Given a basket of assets, how would you allocation your capital across the different assets to maximize returns and minimize risk? This problem can be seen as a classic optimisation problem in data science. In this experiment, I will attempt to compare the performance of three different techniques, Monte Carlo, Sequential Least SQuares Programming (SLSQP) and Bayesian Optimisation, on a simple 3-Fund Portfolio for investors in Singapore.