Coursework for Modern Optimisation module from MSc Big Data Analytics
This project involved the usage of genetic algorithms and objective functions to find potential solutions to a problem along an optimal front. In this case the goal was to find optimal stock market portfolio investment choices from a dataset of stock market price values from the S&P500 over a year. The evaluation functions were used determine the risk factor and profitability of a stock, where genetic algorithms aimed to optimise portfolio investment weights based on these two factors.
Some code was taken from previous lab examples, but research, objective functions, implementation of GA libraries and results plotting and analysis was all conducted by myself.