Analisis Risiko Investasi Saham Syariah Menggunakan Metode Value at Risk Dengan Pendekatan Bayesian Mixture Laplace Autoregressive (MLAR)

Miftahurrohmah, Brina (2017) Analisis Risiko Investasi Saham Syariah Menggunakan Metode Value at Risk Dengan Pendekatan Bayesian Mixture Laplace Autoregressive (MLAR). Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Investasi saham merupakan salah satu hal yang sangat menarik di bidang bisnis. Hal itu dikarenakan dengan melakukan investasi, banyak keuntungan yang akan didapatkan. Namun, investasi saham juga rawan terhadap risiko terjadinya kerugian. Oleh sebab itu, sebelum melakukan investasi, investor perlu mengetahui kemungkinan risiko yang akan terjadi. Value at Risk (VaR) sebagai metode pengukuran risiko yang paling populer, sering mengabaikan pola data yang tidak Normal uni-modal. Perhitungan risiko menggunakan metode VaR dengan Mixture Normal Autoregressive (MNAR) telah dilakukan. Laporan ini mengusulkan VaR dengan Mixture Laplace Autoregressive (MLAR) yang akan dilakukan untuk menganalisis data return saham syariah tiga perusahaan yang tergabung dalam JII dengan kapitalisasi terbesar, yaitu PT. Astra International Tbk (ASII), PT. Telekomunikasi Indonesia Tbk (TLMK) dan PT. Unilever Indonesia Tbk (UNVR). Estimasi parameter dilakukan dengan menggunakan pendekatan Bayesian Markov Chain Monte Carlo (MCMC). Hasil analisis menunjukkan bahwa Risiko tertinggi hingga terendah secara berturut-turut dalam investasi akan dialami saham ASII, UNVR, dan TLKM. ========================================================= ================================== Investment in stocks is something very interesting in the field of business. It is because by investing, a lot of profit to be obtained. However, investments in stocks are also vulnerable to the risk of loss. Therefore, before investing, investors need to be aware of the possibility that the risk will occur. 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 analyzing 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. Results of analysis showed that the highest risk to the lowest level of investment will be experienced by ASII, TLKM, and UNVR stocks.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Mixture Normal Autoregressive (MNAR); Mixture Laplace Autoregressive (MLAR); Bayesian; Markov Chain Monte Carlo (MCMC)
Subjects: H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models.
H Social Sciences > HG Finance
Q Science > QA Mathematics > QA75 Electronic computers. Computer science. EDP
Divisions: Faculty of Mathematics and Science > Statistics > (S2) Master Theses
Depositing User: BRINA MIFT BRINA MIFTAHURROHMAH
Date Deposited: 06 Apr 2017 06:50
Last Modified: 06 Mar 2019 06:45
URI: http://repository.its.ac.id/id/eprint/3153

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