ANALISIS PORTOFOLIO MODEL MIXTURE MENGGUNAKAN BAYESIAN MARKOV CHAIN MONTE CARLO (MCMC)

LAELY USWATUN NUR KHASANAH, NIM. 13610011 (2018) ANALISIS PORTOFOLIO MODEL MIXTURE MENGGUNAKAN BAYESIAN MARKOV CHAIN MONTE CARLO (MCMC). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Portfolio is a combination or a set of assets in the form of real assets and financial assets owned by investors. A good portfolio is an optimal portfolio.The portfolio will be optimized when the portfolio is able to generate a maximum return with limited risk. In this research, portfolio analysis Mixture model using Bayesian Markov Chain Monte Carlo (MCMC) which then continued by calculating the big investment risk using Value at Risk (VaR). The data used are stocks that are always consistent entry in the stock Jakarta Islamic Index (JII). 4 (four) shares were selected consistently entered into JII shares from 01 July 2014 to 31 March 2017. This research is based on Mixture of Mixture model obtained by optimal portfolio model with the biggest proportion that is 49,95% for AKRA stock, next biggest proportion is 25,67% for UNVR share, then 18,90% for TLKM stock and smallest proportion that is 5,48 % on ADRO shares. With expected return obtained by 0,00199 (0,199%), and maximum risk of portfolio 0,01003 (1,003%).

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