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All Journal Media Statistika Jurnal Ilmu Dasar Jurnal Gaussian Jurnal Kajian Akuntansi Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Di Asih I Maruddani
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Journal : Media Statistika

 1 
PENGUKURAN VALUE AT RISK PADA ASET TUNGGAL DAN PORTOFOLIO DENGAN SIMULASI MONTE CARLO Maruddani, Di Asih I; Purbowati, Ari
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (277.501 KB) | DOI: 10.14710/medstat.2.2.93-104

Abstract

Value at Risk (VaR) is the established standard for measuring market risk. VaR measures the worst expected loss under normal market conditions over a specific time interval at a given confidence level. A VaR statistic has three components: a time period, a confidence level and a loss amount (or loss percentage). The Monte Carlo simulation method calculates the change in the value of positions by using a random sample generated by price scenarios. Instead of using the past value of risk factors, Monte Carlo simulation generates models to estimate the risk factors from past portfolio returns by specifying the distributions and their parameters. Using these distributions and parameters, we can generate thousands of hypothetical scenarios for risk factors and, finally, we can determine future prices or rates based on hypothetical scenarios. VaRs can be derived from the cumulative distribution of future prices or rates for given confidence levels. In this paper, we calculate VaR at PT Astra International Tbk., PT Telekomunikasi Tbk., and the portfolio of the two assets. PT. Astra International Tbk has higher VaR than PT. Telekomunikasi Tbk. The VaR of a portfolio has lower result than VaR of each single asset.   Keywords : Value at Risk, Time Period, Confidence Level, Monte  Carlo Simulation.
UJI STASIONERITAS DATA INFLASI DENGAN PHILLIPS-PERON TEST Maruddani, Di Asih I; Tarno, Tarno; Anisah, Rokhma Al
MEDIA STATISTIKA Vol 1, No 1 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (71.414 KB) | DOI: 10.14710/medstat.1.1.27-34

Abstract

The classical regression model was devised to handle relationships between stationary variables. It should not be applied to nonstationary series. A time series is therefore said to be stationary is its mean, variance, and covariances remain constant over time. A problem associated with nonstationary variables, and frequently faced by econometricians when dealing with time series data, is the spurious regression. An apparent indicator of such spurious regression was a particularly low level for the Durbin-Watson statistics, combined with an acceptable R2. Statistical test for stationarity have proposed by Dickey and Fuller (1979). The distribution theory supporting the Dickey-Fuller test assumes that the errors are statistically independent and have a constant variance. Phillips and Peron (1988) developed a generalization of the Dickey-Fuller procedure that the error terms are correlated and not have constant variance. In this paper, we use Phillips-Peron test for inflation data in Indonesia for the time period 1996-2003. The data showed upward trend and the error terms are correlated. The empirical results showed that the inflation data in Indonesia is a nonstationary series.   Keywords : stationarity, non autocorrelation, Phillips-Peron Test, inflation
Perbandingan Sensitivitas Harga Obligasi Berdasarkan Durasi Macaulay dan Durasi Eksponensial dengan Pengaruh Konveksitas (Studi Empiris pada Data Obligasi Korporasi Indonesia yang Terbit Tahun 2015) Maruddani, Di Asih I; Hoyyi, Abdul
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (355.47 KB) | DOI: 10.14710/medstat.10.1.25-36

Abstract

Macaulay duration has often been used as a measure of the bond prices sensitivity to changes in interest rates. For a small change in interest rates, the duration provides a good approximation of the actual change in price. As the change in interest rates gets larger, the duration approximation has larger errors. The convexity of bond prices change is often used as a way to improve the accuracy of the approximation. Several authors have pointed out that the natural logarithm of bond price is a better measure of percentage changes in bond prices as interest rates change. Based on this idea, this paper derives an accurate method of estimating percentage bond price changes in response to changes in interest rates, which is called exponential duration. This paper gives new estimation of bond prices using exponential duration with convexity approach. It will be shown that the new estimation bond prices is always more accurate than by Macaulay duration with convexity approach. For empirical study, it is used corporate bond data, which is published by Indonesian Bond Pricing Agency in 2015. The result support the theory that error value of Macaulay duration with convexity is more than the error value of exponential duration with convexity.Keywords:Bond Price, Convexity, Exponential Duration, Macaulay Duration, Modified Duration
ANALISIS DATA PANEL UNTUK MENGUJI PENGARUH RISIKO TERHADAP RETURN SAHAM SEKTOR FARMASI DENGAN LEAST SQUARE DUMMY VARIABLE Astuti, Tutut Dewi; Maruddani, Di Asih I
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (408.769 KB) | DOI: 10.14710/medstat.2.2.71-80

Abstract

Panel data analysis is a method of studying pooling observations on a cross-section of subjects over several time periods. There are several types of panel data analytic models, constant coefficients models, fixed effects models, and random effects models. Fixed effects models would have constant slopes but intercepts that differ according to the cross-sectional (group) unit. While the intercept is cross-section (group) specific, it may or may not differ over time. To show how to test for the presence of statistically significant group and/or time effects, i-1 dummy variables are used to designate the particular group, so we use Least Squares Dummy Variable method. In this paper, we use this method for testing the relationship between risk and stock return at farmation sector data in Indonesia for the time period 2007-2008. The empirical results showed that the model is statistically significant time effects.   Keywords : Risk, Stock Return, Panel Data, Least Square Dummy Variable
RISK ASSESSMENT OF STOCKS PORTFOLIO THROUGH ENSEMBLE ARMA-GARCH AND VALUE AT RISK (CASE STUDY: INDF.JK AND ICBP.JK STOCK PRICE) Tarno, Tarno; Trimono, Trimono; Maruddani, Di Asih I; Wilandari, Yuciana; Utami, Rianti Siswi
MEDIA STATISTIKA Vol 14, No 2 (2021): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.14.2.125-136

Abstract

Stocks portfolio is a form of investment that can be used to minimize the risk of loss. In a stock portfolio, the Value at Risk (VaR) can be predicted through the portfolio return. If portfolio return variance is heteroskedastic risk prediction can be done by using VaR with ARIMA-GARCH or Ensemble ARIMA-GARCH model approach. Furthermore, the accuracy of VaR is tested through Backtesting test. In this study, the portfolio is formed from PT Indofood CBP Sukses Makmur (ICBP.JK) and PT Indofood Sukses Makmur Tbk (INDF.JK) stocks from 01/01/2018 to 07/30/2021. The results showed that the best model is  Ensemble ARMA-GARCH with MSE 1.3231×10-6. At confidence level of 95% and 1 day holding period, the VaR of the Ensemble ARMA-GARCH was -0.0213. Based on the Backtesting test, it is proven to be very accurate to predict the value of loss risk because the value of the Violation Ratio (VR) is equal to 0.
Co-Authors Abdul Hoyyi Abdurakhman Abdurakhman Ari Purbowati Arief Rachman Hakim Danang Chandra Pradana, Danang Chandra Emy Siswanah Faadillah, Muhamad Nabil Hasbi Yasin Mas'ad, Mas'ad Rokhma Al Anisah Samosir, Jessika Aurora Sinambela, Nadiyah Hafidah Sudarno Sudarno Sugito - Tarno Tarno Trimono, Trimono Tutut Dewi Astuti Utami, Rianti Siswi Yuciana Wilandari Yulia Agnis Sutarno