On The Value at Risk Using Bayesian Mixture Laplace Autoregressive Approach for Modelling the Islamic Stock Risk Investment

International Conference on Mathematics: Education, Theory and Application

数学;教育

Miftahurrohmah, Brina^1 ; Iriawan, Nur^1 ; Fithriasari, Kartika^1

Statistics Department of Mathematics and Natural Sciences, Faculty of Institut Teknologi Sepuluh Nopember, Indonesia^1

关键词: Auto-regressive;    Bayesian markov chain monte carlo;    Bayesian mixture;    Normal mixtures;    Risk investment;    Risk measurement;    Stock returns;    Value at Risk;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/855/1/012026/pdf
DOI  :  10.1088/1742-6596/855/1/012026

学科分类：发展心理学和教育心理学

来源: IOP

【 摘 要 】

Stocks are known as the financial instruments traded in the capital market which have a high level of risk. Their risks are indicated by their uncertainty of their return which have to be accepted by investors in the future. The higher the risk to be faced, the higher the return would be gained. Therefore, the measurements need to be made against the risk. Value at Risk (VaR) as the most popular risk measurement method, is frequently ignore when the pattern of return is not uni-modal Normal. The calculation of the risks using VaR method with the Normal Mixture Autoregressive (MNAR) approach has been considered. This paper proposes VaR method couple with the Mixture Laplace Autoregressive (MLAR) that would be implemented for analysing the first three biggest capitalization Islamic stock return in JII, namely PT. Astra International Tbk (ASII), PT. Telekomunikasi Indonesia Tbk (TLMK), and PT. Unilever Indonesia Tbk (UNVR). Parameter estimation is performed by employing Bayesian Markov Chain Monte Carlo (MCMC) approaches.