Estimating Portfolioโs Value-at-Risk and Conditional Value-at-Risk: Evidence of Laos Securities Exchange
รหัสดีโอไอ
Creator HER Pheng
Title Estimating Portfolioโs Value-at-Risk and Conditional Value-at-Risk: Evidence of Laos Securities Exchange
Publisher Faculty of Management Science Nakhon Pathom Rajabhat University.
Publication Year 2566
Journal Title Journal of Management Science Nakhon Pathom Rajabhat University
Journal Vol. 10
Journal No. 2
Page no. 118-128
Keyword Value-at-Risk, Conditional Value-at-Risk, Gaussian Distribution
URL Website https://so03.tci-thaijo.org/index.php/JMSNPRU/issue/view/17616
Website title https://so03.tci-thaijo.org/index.php/JMSNPRU/index
ISSN 2392-5817
Abstract This paper, researcher used daily closed price from Lao Securities Exchange during October 11, 2019 to May 27, 2021 (exclude public holidays), equal to 402 days and estimating of portfolioโs risk researcher by Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) models in the aspects of Historical Simulation and Gaussian methods with the confidence interval of 95%, 97.5% and 99% respectively. Result in historical simulation method expressed that VaR of Phousy Construction and Development Public Company (PCD) has highest value and Lao Cement Public Company (LCC) has lowest value. For CVaR function found that PCD remain the company that has highest value and Mahathuen Leasing Public Company (MHTL) has lowest value (95% confidence). For Gaussian Distribution method found that VaR of PCD remain the company that has highest risk and MHTL has lowest and in aspects of CVaR found that PCD and MHTL remains the companies that has highest and lowest value and researcher concluded that CVaR is better than VaR because CVaR gives us an average expected loss while VaR gives us a range of potential losses or it less accurate lower approximation of risk. For comparison of the portfolio of 11 traded stocks in LSX indicated that portfolioโs VaR and CVaR in Gaussian Distribution method is lower than Historical Simulation method and specified Gaussian Distribution analysis is a better risk indicator because it is closer to the actual value
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