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Title:	Pemodelan matematik bagi risiko dalam pengoptimuman portfolio di pasaran saham Malaysia
Authors:	Lam Weng Hoe (P50032)
Supervisor:	Saiful Hafizah Hj. Jaaman, Prof. Madya Dr.
Keywords:	Pelaburan Pengoptimuman portfolio Faktor kepencongan Kurtosis Dissertations, Academic -- Malaysia Universiti Kebangsaan Malaysia -- Dissertations
Issue Date:	11-Apr-2014
Description:	Pelaburan merupakan mekanisme yang penting dalam menambahkan kekayaan pelabur individu dan institusi serta menjana pendapatan negara. Objektif pelaburan adalah untuk menjana keuntungan melalui pulangan. Namun begitu, pelabur terdedah kepada risiko kerugian dalam pelaburan. Suatu strategi penting untuk meminimumkan risiko pelaburan dan memperoleh kadar pulangan yang dijangkakan daripada pelaburan adalah melalui pengoptimuman portfolio. Pengoptimuman portfolio merupakan gabungan pelbagai aset dengan objektif untuk meminimumkan risiko pada suatu tahap jangkaan pulangan. Terdapat pelbagai model pengoptimuman portfolio menggunakan ukuran risiko berlainan, antaranya ukuran varians, semi varians, Gini, sisihan mutlak dan nilai risiko bersyarat. Model pengoptimuman portfolio ini dikenali sebagai model min-risiko yang menggunakan min sebagai jangkaan pulangan dengan ukuran risiko yang berlainan. Kajian kepustakaan menunjukkan kelemahan utama semua model min-risiko adalah tidak mengambil kira faktor kepencongan dan kurtosis. Kedua-dua faktor kepencongan dan kurtosis merupakan intipati penting dalam pengoptimuman portfolio kerana kebarangkalian untuk mendapat risiko kerugian besar dapat dikurangkan jika nilai kepencongan tinggi dan nilai kurtosis rendah. Oleh itu, objektif utama kajian ini adalah untuk membina model matematik pengoptimuman portfolio baharu yang ditambah baik dengan mengambil kira faktor kepencongan dan kurtosis. Lima model baharu dibina dengan menambahkan faktor kepencongan dan kurtosis kepada lima model min-risiko yang sedia ada iaitu model min-varians, model min-semi varians, model min-Gini, model min-sisihan mutlak dan model min-nilai risiko bersyarat. Kaedah pengaturcaraan gol digunakan dalam menyelesaikan model baharu kerana kaedah ini dapat meminimumkan sisihan daripada nilai optimum min, kepencongan dan kurtosis. Dalam kajian ini, data pulangan saham-saham yang membentuk Indeks Komposit Kuala Lumpur dari Julai 1993 hingga Jun 2008 digunakan kerana tempoh kajian ini mewakili satu kitaran ekonomi yang lengkap iaitu pertumbuhan ekonomi, kemelesetan ekonomi dan pemulihan ekonomi. Kajian ini membandingkan prestasi portfolio optimum lima model baharu dengan model minvarians, min-semi varians, min-Gini, min-sisihan mutlak dan min-nilai risiko bersyarat. Keputusan kajian menunjukkan bahawa model baharu yang dikenali sebagai min-nilai risiko bersyarat-kepencongan-kurtosis memberikan prestasi portfolio optimum yang paling baik di antara semua model yang dikaji. Ini menunjukkan model baharu min-nilai risiko bersyaratkepencongan-kurtosis merupakan model yang paling sesuai digunakan dalam pasaran saham Malaysia. Kajian ini adalah penting kerana model pengoptimuman portfolio baharu yang paling sesuai digunakan dalam pasaran saham Malaysia dibina dengan mengambil kira faktor kepencongan dan kurtosis. Model baharu ini akan memberikan manfaat kepada pelabur individu dan institusi dalam meminimumkan risiko, menambahkan kekayaan dan seterusnya menjana pendapatan negara.,Investment is an important mechanism in increasing the wealth of individual and institutional investors, and also in generating the income of a country. The objective of investment is to generate profit through return. Nevertheless, investors are exposed to the risk of loss in investment. An important strategy to minimize investment risk and obtain expected return is through portfolio optimization. Portfolio optimization is combining different assets with the objective to minimize risk at a given level of expected return. There are different portfolio optimization models using different risk measures such as variance, semi variance, Gini, absolute deviation and conditional value at risk. These portfolio optimization models are known as mean-risk models using mean as expected return with different risk measures. As described in past studies, these mean-risk models did not take skewness and kurtosis factors into consideration. This is thus the main weakness of these models. Both skewness and kurtosis factors are important elements in portfolio optimization because the probability of getting large losses will be reduced if the portfolio has high value of skewness and low value of kurtosis. The main objective of this study hence is to construct a new enhanced portfolio optimization mathematical model by taking the skewness and kurtosis factors into consideration. Five new models are constructed by adding the skewness and kurtosis factors into five existing mean-risk models which are mean-variance model, mean-semi variance model, mean-Gini model, mean-absolute deviation model and mean-conditional value at risk model. The goal programming method is used in solving the new model because this method can minimize the deviations from the optimal values of mean, skewness and kurtosis. Data used in this study are returns of Index Composite Kuala Lumpur component shares from July 1993 to June 2008 because this period of study represents the complete economic cycle which are economic growth, economic crisis and economic recovery. This study compares the optimal portfolio performance of five new models with mean-variance model, mean-semi variance model, mean-Gini model, mean-absolute deviation model and mean-conditional value at risk model. The results of this study show that the optimal portfolio of the new model which is known as mean-conditional value at risk-skewness-kurtosis model gives the best performance among all the studied models. It shows that the new mean-conditional value at risk-skewness-kurtosis model is the most suitable model to be used in the Malaysia stock market. This study is important because the new portfolio optimization model which is the most suitable model to be used in the Malaysia stock market is constructed by taking skewness and kurtosis factors into consideration. The new model will benefit the individual and institutional investors in minimizing risk, increasing wealth and generating income of the country.,Ph.D.,Investment is an important mechanism in increasing the wealth of individual and institutional investors, and also in generating the income of a country. The objective of investment is to generate profit through return. Nevertheless, investors are exposed to the risk of loss in investment. An important strategy to minimize investment risk and obtain expected return is through portfolio optimization. Portfolio optimization is combining different assets with the objective to minimize risk at a given level of expected return. There are different portfolio optimization models using different risk measures such as variance, semi variance, Gini, absolute deviation and conditional value at risk. These portfolio optimization models are known as mean-risk models using mean as expected return with different risk measures. As described in past studies, these mean-risk models did not take skewness and kurtosis factors into consideration. This is thus the main weakness of these models. Both skewness and kurtosis factors are important elements in portfolio optimization because the probability of getting large losses will be reduced if the portfolio has high value of skewness and low value of kurtosis. The main objective of this study hence is to construct a new enhanced portfolio optimization mathematical model by taking the skewness and kurtosis factors into consideration. Five new models are constructed by adding the skewness and kurtosis factors into five existing mean-risk models which are mean-variance model, mean-semi variance model, mean-Gini model, mean-absolute deviation model and mean-conditional value at risk model. The goal programming method is used in solving the new model because this method can minimize the deviations from the optimal values of mean, skewness and kurtosis. Data used in this study are returns of Index Composite Kuala Lumpur component shares from July 1993 to June 2008 because this period of study represents the complete economic cycle which are economic growth, economic crisis and economic recovery. This study compares the optimal portfolio performance of five new models with mean-variance model, mean-semi variance model, mean-Gini model, mean-absolute deviation model and mean-conditional value at risk model. The results of this study show that the optimal portfolio of the new model which is known as mean-conditional value at risk-skewness-kurtosis model gives the best performance among all the studied models. It shows that the new mean-conditional value at risk-skewness-kurtosis model is the most suitable model to be used in the Malaysia stock market. This study is important because the new portfolio optimization model which is the most suitable model to be used in the Malaysia stock market is constructed by taking skewness and kurtosis factors into consideration. The new model will benefit the individual and institutional investors in minimizing risk, increasing wealth and generating income of the country. v
Pages:	178
Call Number:	HG4529.L344 2014 tesis
Publisher:	UKM, Bangi
Appears in Collections:	Faculty of Science and Technology / Fakulti Sains dan Teknologi

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