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All Journal Media Statistika Jurnal Gaussian TRANSIENT: Jurnal Ilmiah Teknik Elektro
Rita Rahmawati
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro
Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Other

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EXPECTED SHORTFALL DENGAN SIMULASI MONTE-CARLO UNTUK MENGUKUR RISIKO KERUGIAN PETANI JAGUNG Rita Rahmawati; Agus Rusgiyono; Abdul Hoyyi; Di Asih I Maruddani
MEDIA STATISTIKA Vol 12, No 1 (2019): 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 (526.428 KB) | DOI: 10.14710/medstat.12.1.117-128

Abstract

In risk management, risk measurement plays an important role in allocating capital as well as in controlling (and avoiding) worse risk. Estimating the risk value can be done by using a risk measure. The most popular method for evaluating risk is Value at Risk (VaR). But VaR does not fulfill the coherency as a measure of risk effectiveness. In this paper, we propose Expected Shortfall (ES) which has coherency nature. ES is defined as the conditional expectation of losses beyond VaR of the same confidence level over the same holding period. For measuring ES, we use Monte-Carlo Simulation Method. This method is applied for measuring risk that will be faced by corn’s farmers due to the changes in corn prices in Pemalang city. The results show that the ES value is 0.085472 at 95% confidence level and one-month holding period. This number means that a farmer will face 8.5472% of investment as maximum loss exceeding of VaR.
PERBANDINGAN METODE REGRESI LINIER MULTIVARIABEL DAN REGRESI SPLINE MULTIVARIABEL DALAM PEMODELAN INDEKS HARGA SAHAM GABUNGAN Ihdayani Banun Afa; Suparti Suparti; Rita Rahmawati
MEDIA STATISTIKA Vol 11, No 2 (2018): 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 (340.648 KB) | DOI: 10.14710/medstat.11.2.147-158

Abstract

The composite stock price index or Indonesia Composite Index (ICI) is a composite index of all stocks listed on the Indonesia Stock Exchange and its movements indicate conditions that occur in the capital market. For investors, the ICI movement is one of the important indicator to make a decision whether the stocks will be sold, held or bought new shares. The ICI movement (y) was influenced by several factors including Inflation (x1), Exchange Rate (x2) and SBI interest rate (x3). This study aims to compare the ICI modeling  using the parameric and nonparametric approaches, namely multivariable linear regression and multivariable spline regression. Determination of the better model is based on the smaller MSE and the larger R2. The best regression model is multivariable spline regression with x1, x2 and x3, each with a sequence orde (3,2,2) and the number of knot points (1,2,2).Keywords: Indonesia Composite Index, Multiple Linear Regression, Multivariable Spline Regression, MSE, R2
PERHITUNGAN VALUE AT RISK DENGAN PENDEKATAN THRESHOLD AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY-GENERALIZED EXTREME VALUE Mutik Dian Prabaning Tyas; Di Asih I Maruddani; Rita Rahmawati
MEDIA STATISTIKA Vol 12, No 1 (2019): 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 (537.145 KB) | DOI: 10.14710/medstat.12.1.73-85

Abstract

Stock is the most popular type of financial asset investment. Before buying a stock, an investor must estimate the risks which will be received. Value at Risk (VaR) is one of the methods that can be used to measure the level of risk. When investing in stock, if an investor wants to earn high returns, then he must be prepared to face higher risks. Most of stock return data have volatility clustering characteristic or there are cases of heteroscedasticity and the distribution of stock returns has heavy tail. One of the time series models that can be used to overcome the problem of heteroscedasticity is the ARCH/GARCH model, while the method for analyzing heavy tail data is Extreme Value Theory (EVT). In this study used an asymmetrical ARCH model with the Threshold ARCH (TARCH) and EVT methods with Generalized Extreme Value (GEV) to calculate VaR of the stock return from PT Bumi Serpong Damai Tbk for the period of September 2012 to October 2018. The best chosen model is AR([3])–TARCH(1). At the 95% confidence level, the maximum loss an investor will be received within the next day by using the TARCH-GEV calculation is 0.18%.
Co-Authors Abdul Hoyyi Abdur Rofiq Agus Rusgiyono Ajub Ajulian Zahra Macrina Alika Ramadhani Amalina Sari Dewi Arianti Suhartini Bambang Winardi Budi Warsito Denny Jales Manalu Di Asih I Maruddani Diah Safitri Dina Rahma Prihatiningsih Dwi Ispriyanti Eka Destiyani Eka Lestari Ekky Rosita Singgih Wigati Enggartya Andini Ihdayani Banun Afa Ihdayani Banun Afa Jeffri Nelwin J. O. Siburian Merinda Pangestikasari Mustafid Mustafid Mutik Dian Prabaning Tyas Riski Arum Pitaloka Rukun Santoso Sensiani Sensiani Sudarno Sudarno Sugito Sugito Suparti Suparti Suparti Suparti Tatik Widiharih Triastuti Wuryandari Umiyatun Muthohiroh Vetranella .T.R.A. Sinaga Windy Rohalidyawati