The Dependence Structure of risk and return using CAPM model for the financial and industrial sector of Thailand stock market: a copula approach

โครงสร้างความสัมพันธ์ของความเสี่ยงและผลตอบแทนด้วยแบบจำลองซีเอ็มพีเอ็มของภาคการเงินและภาคอุตสาหกรรมในตลาดหลักทรัพย์ประเทศไทยด้วยวิธีโคปูลา

Name: Sreynich Preap

ThaSH: Financial statements -- Analysis

Classification :.DDC: 657.3

ThaSH: Investment analysis

ThaSH: Risk management

ThaSH: Stock exchanges -- Thailand

Abstract: This paper investigates the coefficients beta of Capital Asset Pricing Model of the financial and industrial stock return of the Stock Exchange of Thailand (SET) in association with market risk, consumer price index, and the movement of the world oil price. Both financial and industrial stock return is modeled under the framework of CAPM and estimated by Generalized Linear Model and Seemingly Unrelated Regression Copula regression. The weekly returns of both stock markets are conducted from November 2008 to October 2014 with 304 observations. First, we estimated individually the financial and industrial returns with market risk, consumer price index, and movement of oil price by GLM estimation method. Secondly, we combined two equations of the financial and industrial sectors with the concept of SURE and modeled with SURE copula regression. Five copula functions are chosen with respond to their number of parameters. The best copula functions were chosen depending on the value of Akaike's Information Criterion (AIC) and Bayesian information criterion (BIC). The first estimation of GLM generated risk betas equal to 0.85879 and 0.82086, respectively, for the financial stock market and industrial stock market. In this estimation part, consumer price index and the movement of oil price performed insignificantly to the return of the financial and industrial stock market. In second part of SURE copula estimation, Gaussian and Frank copula function generated a best beta due to the smallest AIC and BIC value. This step generated beta of 0.44935 for the financial stock and 0.82153 for the industrial stock market with respect to Gaussian copula. In the case of frank copula function, beta risk is equal to 0.22165 and 0.81504 for the financial and industrial stock market, respectively. Consumer price index performed negatively in generating the return of both the financial and industrial stock market. The movement of oil price negatively affected to the return of both financial and industrial stock return during the US Quantitative Easing period. We conclude that SURE copula is the best method to estimate the equation of CAPM of the financial and industrial stock market return because this method has ability to capture the effect of other variables rather than GLM estimation method

Chiang Mai University Library

Address: Chiang Mai

Email: cmulibref@cmu.ac.th

Name: Wanvilai Chulaphan

Role: Chairman

Name: Pathairat Paspipatkul

Role: Member

Name: Chaiwat Nimanussornkul

Role: Member

Created: 2015

Modified: 2020-01-08

Issued: 2020-01-08

วิทยานิพนธ์/Thesis

application/pdf

CallNumber: Th 657.3 S774D

eng

DegreeName: Master of Economics

Level: Master's Degree

Descipline: Economics

Grantor: Chiang Mai University

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