Stock Selection, risk measurement and portfolio optimization in the Hong Kong stock exchange

การเลือกหลักทรัพย์ การวัดค่าความเสี่ยง และการหาค่าเหมาะสมที่สุดของหลักทรัพย์การลงทุนเพื่อให้ได้ผลตอบแทนสูงสุดในตลาดหลักทรัพย์ฮ่องกง

Name: Biren, Hu

ThaSH: Securities

Classification :.DDC: 332.632

ThaSH: International trade

ThaSH: Financial risk management

ThaSH: Investments

Abstract: In this paper, we focus on systematic analyses of stock selection, risk and portfolio in the Hong Kong Stock Exchange (HKSE). The data daily was collected from the 1st of January 2010 to the 15th of December 2016. During the process of stock selection, we use the traditional and modified Sharpe ratio (SR) methods to select three groups of target portfolios from 1300 stocks in the HKSE. By ranking the Sharpe ratio, 15 stocks have been divided into 3 portfolios with 5 for each. The stock price matrix is transferred into log return for the further research. We apply the Copula-GARCH models to fit the stock return data. On the one hand, we measure the Value at Risk (VaR) of the equally weight portfolios using the best Copula-GARCH models. On the other hand, we use portfolio optimization methods, such as the Maximum Return method, the Minimum Risk method and the Maximum Sharpe ratio method to optimize portfolios of the HKSE. The empirical findings are as below: Firstly, copula functions explicitly capture the dependence structure of the selected stocks. According to AIC criteria, the t-Copula-GARCH-sstd model with unstructured correlation matrix is the best fitted model for every single stocks in these three portfolios. Secondly, we perform the VaR forecasting for portfolios. We find that the t-CopulaGARCH-sstd model is much better when measuring the Value at Risk. The t-Copula-GARCH with unstructured correlation matrix is the best model for VaR forecasting in all the three portfolios. Finally, the Max Sharpe Ratio method has the best performance when doing the portfolio optimization and it is the most appropriate to forecast portfolio optimization for Hong Kong Stock Exchange using this method in the year 2016.

Chiang Mai University Library

Address: Chiang Mai

Email: cmulibref@cmu.ac.th

Name: Orakanya Kanjanatarakul

Role: Chairman

Name: Jianxu Liu

Role: Member

Name: Jirakom Sirisrisakulchai

Role: Member

Role: Pathairat Pastpipatkul

Email : Member

Created: 2017

Modified: 2018-09-28

Issued: 2018-09-28

วิทยานิพนธ์/Thesis

application/pdf

CallNumber: Th 332.632 B618S

eng

DegreeName: Master of Economics

Level: Master's Degree

Grantor: Chiang Mai University

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