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

B Miftahurrohmah, N Iriawan… - Journal of Physics …, 2017 - iopscience.iop.org
Journal of Physics: Conference Series, 2017iopscience.iop.org
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 …
Abstract
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.
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