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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Transformasi : Jurnal Pendidikan Matematika dan Matematika
Radinasari, Nur Ismi
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Decision Sciences, Operations Research & Management Education Mathematics Transportation

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PERBANDINGAN ESTIMASI VOLATILITAS HARGA OPSI BELI SAHAM APPLE INC. (AAPL) DENGAN METODE BISECTION DAN SECANT Radinasari, Nur Ismi; Sulistianingsih, Evy; Martha, Shantika
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 1 (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.v18i1.11638

Abstract

Stock price volatility is a measure of how far a stock price moves in a given Stock price volatility is a measure of how far a stock price moves in a given time. The theory developed by Black-Scholes states that every option price with the same 'underlying asset' and the same time to maturity but with different exercise values will have the same Implied Volatility value. However, this is not always the case in the market. Therefore, it is necessary to estimate volatility known as Implied Volatility, which is considered an appropriate method in estimating volatility values. This study compares the Bisection and Secant methods to estimate the volatility of Apple Inc. (Aapl) stock. This study uses data on the closing price of the stock in the period September 29, 2022 to September 29, 2023. Volatility estimation for the Bisection and Secant methods by determining the initial approximation and limiting it to a maximum of 100 simulations and iteration stops if it has produced a relative error smaller than  = . The  is an error tolerance limit, the smaller the error tolerance, the more accurate it is. According to the research results, the Bisection method produces an estimated volatility value of 0.498212 at the 9th iteration, while the Secant method produces an estimated value of 0.498590 at the 10th iteration. The Secant method produces a smaller relative error value of 0.000096, indicating that the Secant method is more accurate than the Bisection method.
PEMODELAN SEKTOR UNGGULAN PROVINSI KALIMANTAN BARAT DENGAN MENGGUNAKAN PRINCIPAL COMPONENT ANALYSIS Satyahadewi, Neva; Aprizkiyandari, Siti; Radinasari, Nur Ismi
TRANSFORMASI Vol 7 No 2 (2023): TRANSFORMASI: Jurnal Pendidikan Matematika dan Matematika
Publisher : Pendidikan Matematika FMIPA Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/tr.v7i2.2760

Abstract

West Kalimantan is the province with the fourth largest area in Indonesia, namely 147,307 square km. West Kalimantan has 12 districts and 2 cities, one of which is Ketapang Regency which covers an area of ​​31,240.74 km2. The research is limited to three leading sectors which have the largest average contribution to GRDP in West Kalimantan Province, namely the agriculture, forestry and fisheries sectors; industrial processing; as well as wholesale and retail trade, and car and motorcycle repair. The focus of this research is aimed at modeling the leading sector for the West Kalimantan economy. The results of the modeling showed multicollinearity so it was continued with the Principal Component Analysis. The results of the analysis with the model show that there is no element of multicollinearity between the dependent variables.
Co-Authors Aprizkiyandari, Siti Evy Sulistianingsih Martha, Shantika Neva Satyahadewi