Portfolio optimization using mean-variance model and single index model: Evidence from Indonesian and Malaysian capital markets

Abstract

This study explores the application of investment theories, explicitly focusing on portfolio optimization using the Mean-Variance Model by Markowitz and the Single Index Model by Sharpe in the Indonesian and Malaysian capital markets. Focused on the IDX30 and FTSE Bursa Malaysia KLCI indices, representing major stocks in Indonesia and Malaysia, the study underscores the complexities in portfolio formation due to market fluctuations, economic uncertainties, and regulatory changes. Historical data from the year 2010 to 2023 is utilized, employing both models to form optimal portfolios. Findings suggest that the mean-variance model provides more optimal results, with certain stocks dominating portfolio compositions, highlighting the importance of efficient asset selection over sheer quantity for effective diversification. The study concludes that the use of the Mean-Variance Model provides more optimal results compared to the Single Index Model in portfolio formation involving both the IDX30 index and the FTSE Bursa Malaysia KLCI index, with their fund proportions dominated by BBCA stocks for the IDX30 index and 4707 or Nestle (Malaysia) stocks for the FTSE Bursa Malaysia KLCI index. Therefore, the key to effective diversification lies not solely in the number of assets forming the portfolio but rather in the efficient selection of those portfolio assets.