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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Pattimura International Journal of Mathematics (PIJMath)
Arsanti, Resti
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Decision Sciences, Operations Research & Management Mathematics Transportation

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ESTIMASI VALUE AT RISK (VAR) DENGAN METODE MONTE CARLO UNTUK MENGUKUR RISIKO KERUGIAN PETANI KETIMUN DI KABUPATEN KAPUAS HULU Arsanti, Resti; Sulistianingsih, Evy; Septiawan, Anggi
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 2 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i2.11433

Abstract

Measurement of an estimated loss needs to be done by every business actor. The measurement can be done by calculating the Value at Risk (VaR). VaR is an estimate of the maximum loss that is assumed to be experienced in a certain period at the confidence interval used. Three forms of calculation methods can be used in calculating VaR estimates, namely parametric methods, methods with Monte Carlo simulation approaches, and Historical Simulation Methods. The data used is the average monthly producer price data of cucumber commodities with a period range starting from January 2020 to December 2022. The VaR calculation method in this analysis is the Monte Carlo simulation approach method which has the condition that the return data from the average producer price is normally distributed. The results of the VaR calculation with the Monte Carlo simulation method show that after generating return data with repetition 1000 times for an investment of 1 rupiah, the probability that cucumber farmers in Kapuas Hulu Regency, West Kalimantan Province will experience maximum losses is 5.79% for a confidence level of 80%, 9.08% for a confidence level of 90%, 11.39% for a confidence level of 95%, and 14.81% for a confidence level of 99%.
Forecasting the Stock Price of PT. Dayamitra Telekomunikasi with Single Input Transfer Function Model Arsanti, Resti; Satyahadewi, Neva; Martha, Shantika
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp87-96

Abstract

The unpredictable movement of stock prices is often a challenge for investors, so it requires a deeper understanding and consideration of various factors before making investment decisions. One of the factors that affect stock price movements is trading volume. Therefore, this study uses a single input transfer function model to forecast the daily closing stock price of PT. Dayamitra Telekomunikasi, with the closing stock price as the output variable and the stock trading volume as the input variable. The transfer function is a forecasting model that integrates ARIMA with multiple regression analysis, allowing modeling not only based on the values of the output variables, but also considering the influence of the input variables. ARIMA model estimation is performed on the input series for the prewhitening process, then the order of the transfer function is determined using cross-correlation plots, as well as model diagnostic tests to ensure its feasibility. Model accuracy is calculated to evaluate its performance in forecasting. The data used in this study are daily data from the period July 5, 2022 to October 9, 2024. The transfer function model obtained has an order of (2,0,0), with a MAPE value of 1.09%, which indicates that the model has good accuracy. Based on the forecasting results, it is estimated that there will be a decrease in the share price of PT. Dayamitra Telekomunikasi Tbk for the next five periods
Co-Authors Evy Sulistianingsih Martha, Shantika Neva Satyahadewi Septiawan, Anggi