Lam Weng Siew

Investigation on the Efficiency of Financial Companies in Malaysia with Data Envelopment Analysis Model

Financial ratio and risk are important financial indicators to evaluate the financial performance or efficiency of the companies. Therefore, financial ratio and risk factor are needed to be taken into consideration to evaluate the efficiency of the companies with Data Envelopment Analysis (DEA) model. In DEA model, the efficiency of the company is measured as the ratio of sum-weighted outputs to sum-weighted inputs. The objective of this paper is to propose a DEA model by incorporating the financial ratio and risk factor in evaluating and comparing the efficiency of the financial companies in Malaysia. In this study, the listed financial companies in Malaysia from year 2004 until 2015 are investigated. The results of this study show that AFFIN, ALLIANZ, APEX, BURSA, HLCAP, HLFG, INSAS, LPI, MNRB, OSK, PBBANK, RCECAP and TA are ranked as efficient companies. This implies that these efficient companies have utilized their resources or inputs optimally to generate the maximum outputs. This study is significant because it helps to identify the efficient financial companies as well as determine the optimal input and output weights in maximizing the efficiency of financial companies in Malaysia.

Portfolio optimization in enhanced index tracking with goal programming approach

Enhanced index tracking is a popular form of passive fund management in stock market. Enhanced index tracking aims to generate excess return over the return achieved by the market index without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio to maximize the mean return and minimize the risk. The objective of this paper is to determine the portfolio composition and performance using goal programming approach in enhanced index tracking and comparing it to the market index. Goal programming is a branch of multi-objective optimization which can handle decision problems that involve two different goals in enhanced index tracking, a trade-off between maximizing the mean return and minimizing the risk. The results of this study show that the optimal portfolio with goal programming approach is able to outperform the Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasi...

Portfolio optimization with mean-variance model

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

Portfolio optimization for index tracking modelling in Malaysia stock market

Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.

Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach

Enhanced index tracking is a popular form of portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.