PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016)

Oktafiani Widya Ningrum; Tarno Tarno; Di Asih I Maruddani

doi:10.14710/j.gauss.6.2.231-240

DOI: https://doi.org/10.14710/j.gauss.6.2.231-240

PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016)

*Oktafiani Widya Ningrum -

Tarno Tarno -

Di Asih I Maruddani -

How to cite (IEEE): O. W. Ningrum, T. Tarno, and D. A. I. Maruddani, "PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016)," Jurnal Gaussian, vol. 6, no. 2, pp. 231-240, Apr. 2017. https://doi.org/10.14710/j.gauss.6.2.231-240

How to cite (APA): Ningrum, O. W., Tarno, T., & Maruddani, D. A. I. (2017). PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016). Jurnal Gaussian, 6(2), 231-240. https://doi.org/10.14710/j.gauss.6.2.231-240

How to cite (BCREC): Ningrum, O. W., Tarno, T., Maruddani, D. A. I. (2017). PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016). Jurnal Gaussian, 6 (2), 231-240 (doi:10.14710/j.gauss.6.2.231-240)

How to cite (Chicago): Ningrum, Oktafiani W., Tarno Tarno, and Di A. I. Maruddani. "PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016)." Jurnal Gaussian 6, no. 2 (2017): 231-240. Accessed : April 11, 2025. https://doi.org/10.14710/j.gauss.6.2.231-240

How to cite (Vancouver): Ningrum OW, Tarno T, Maruddani DAI. PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016). Jurnal Gaussian [Online]. 2017 Apr;6(2):231-240. https://doi.org/10.14710/j.gauss.6.2.231-240.

How to cite (Harvard): Ningrum, O. W., Tarno, T., and Maruddani, D. A. I., 2017. PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016). Jurnal Gaussian, [Online] Volume 6(2), pp. 231-240. https://doi.org/10.14710/j.gauss.6.2.231-240 [Accessed : 11 Apr. 2025].

How to cite (MLA8): Ningrum, Oktafiani, Tarno Tarno, and Di Asih I Maruddani. "PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016)." Jurnal Gaussian, vol. 6, no. 2, 20 Apr. 2017, pp. 231-240 , https://doi.org/10.14710/j.gauss.6.2.231-240. Retrieved : 11 Apr. 2025.

BibTex Citation Data :

@article{J.Gauss16952,
    author = {Oktafiani Ningrum and Tarno Tarno and Di Maruddani},
    title = {PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016)},
    journal = {Jurnal  Gaussian},
  volume = {6},
    number = {2},
    year = {2017},
    keywords = {Value at Risk, Copula, GARCH},
    abstract = { Investment is one of the way that is widely performed by people to achieve profitability in the future.Stock data is a data that is obtained from the observation that stock prices can be categorized into time series data, which usually have a tendency to fluctuate rapidly by the time so the variance of the residual will always change all the time or not constant, or often called heteroscedasticity case.  Forecasting and data analysis is intended to minimize the risk and uncertainty factors. The risks can not be avoided but can be managed and estimated using Value at Risk (VaR) measurement tool. Copula theory is one of the tool that can be used to fit the joint distribution because it does not require the assumption of normality of the data so it is flexible enough for a variety of data, especially for financial data. This research is conducted using the method of Copula-GARCH to fit the three stocks of companies return data in Indonesia which have high volatility, those are PT Vale Indonesia Tbk (INCO), PT Bank Central Asia Tbk (BCA), and PT Indocement Tunggal Tbk (INTP) in period of October 13, 2011 to October 12, 2016 into ARIMA-GARCH model. The analysis is followed by copula on two stocks that have the highest ARIMA-GARCH residual correlation, those are BCA and INTP.Copula Gumbel is selected as the best copula with the amount of  is 1,337. The risk derived from the calculation of Value at Risk (VaR) at the 99% confidence level is 3,922%, at the 95% confidence level is 2,397%, and at the 90% confidence level is 1,745%.   Keywords   :  Value at Risk, Copula ,  GARCH   },
   issn = {2339-2541},   pages = {231--240}  doi = {10.14710/j.gauss.6.2.231-240},
    url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/16952}
}

Refworks Citation Data :

@article{{J.Gauss}{16952}, author = {Ningrum, O., Tarno, T., Maruddani, D.}, title = {PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016)}, journal = {Jurnal Gaussian}, volume = {6}, number = {2}, year = {2017}, doi = {10.14710/j.gauss.6.2.231-240}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/16952} }

Citation Format:

Abstract

Investment is one of the way that is widely performed by people to achieve profitability in the future.Stock data is a data that is obtained from the observation that stock prices can be categorized into time series data, which usually have a tendency to fluctuate rapidly by the time so the variance of the residual will always change all the time or not constant, or often called heteroscedasticity case. Forecasting and data analysis is intended to minimize the risk and uncertainty factors. The risks can not be avoided but can be managed and estimated using Value at Risk (VaR) measurement tool. Copula theory is one of the tool that can be used to fit the joint distribution because it does not require the assumption of normality of the data so it is flexible enough for a variety of data, especially for financial data. This research is conducted using the method of Copula-GARCH to fit the three stocks of companies return data in Indonesia which have high volatility, those are PT Vale Indonesia Tbk (INCO), PT Bank Central Asia Tbk (BCA), and PT Indocement Tunggal Tbk (INTP) in period of October 13, 2011 to October 12, 2016 into ARIMA-GARCH model. The analysis is followed by copula on two stocks that have the highest ARIMA-GARCH residual correlation, those are BCA and INTP.Copula Gumbel is selected as the best copula with the amount of is 1,337. The risk derived from the calculation of Value at Risk (VaR) at the 99% confidence level is 3,922%, at the 95% confidence level is 2,397%, and at the 90% confidence level is 1,745%.

Keywords : Value at Risk, Copula, GARCH

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Keywords: Value at Risk, Copula, GARCH

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In Vol 6, No 2 (2017): Jurnal Gaussian