You never fail until you stop trying. (Albert Einstein)
Muddassir Sayeed Siddiqui, Syed Muhammad Noaman Ahmed Shah
27-05-2023
2nd IBA SBS International Conference 2023
Institute of Business Administration (IBA)
Portfolio optimization for better profit generation is the desire of every investor. This study attempted to construct fully optimized diverse portfolio with the objective of maximum expected return and best sharpe ratio, after analyzing each stock fundamentally and technically by using machine learning algorithms for prediction and genetic algorithm for optimization. Random Forest (RF) is used for stock return prediction. Data of 170 companies is included in research from all sectors of Pakistan Stock Exchange (PSX) for the time period of 2000 till April 2022. The tests are conducted in three phases. The whole process is based on 4 layers which are analysis layer, prediction layer, diversification layer and optimization layer. Optimization layer uses genetic algorithm for portfolio optimization. Findings of the analysis concluded that the machine learning effects the portfolio optimization positively and it can be used in Pakistan’s market. The predictions of the returns were significant and portfolios were well diversified. Genetic algorithm optimized the portfolio efficiently. The result of the study is significant. This method can be used by portfolio managers for better diversified portfolio construction and its optimization that will help them to maximize the return on portfolio. The methodology also predicts the stock return which is also useful for managers to foresee the future market.