Analisis Pebandingan Metode Newton-Raphson dan Algoritma Genetika untuk Mengestimasi Implied Volatility Opsi Call Basket

Firdausiah, Tri Darien Nahwa (2025) Analisis Pebandingan Metode Newton-Raphson dan Algoritma Genetika untuk Mengestimasi Implied Volatility Opsi Call Basket. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5002211122-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (4MB) | Request a copy

Abstract

Estimasi implied volatility merupakan aspek penting dalam penentuan harga opsi, khususnya dalam model Black-Scholes. Dua metode yaitu metode Newton-Raphson dan algoritma genetika telah dibandingkan dalam penelitian ini untuk mengestimasi implied volatility pada opsi call Basket. Model harga opsi call Basket berdasarkan pendekatan Black-Scholes untuk opsi multi-aset dibangun dan diimplementasikan hingga mendekati harga opsi pasar saat itu. Kedua metode estimasi, Newton-Raphson dan algoritma genetika, diterapkan untuk mencari implied volatility dari formula harga opsi Basket. Hasil simulasi menunjukkan bahwa Metode Newton-Raphson secara konsisten mencapai konvergensi dalam waktu yang lebih singkat, serta menghasilkan nilai implied volatility yang mirip. Algoritma genetika terbukti lebih robust terhadap variasi dan mampu mendapatkan implied volatility yang lebih beragam. Metode algoritma genetika juga memerlukan jumlah iterasi atau evaluasi fungsi yang lebih banyak.
==========================================================================================================================================
The estimation of implied volatility is an important aspect in option pricing, especially in the Black-Scholes model. Two methods, namely the Newton-Raphson method and the
genetic algorithm, have been compared in this study to estimate the implied volatility in the call Basket option. A call Basket option pricing model based on the Black-Scholes approach for multi-asset options is constructed and implemented to approximate the current market option price. The two estimation methods, Newton-Raphson and genetic algorithm, are applied to find the implied volatility from the option pricing formula. Simulation results
show that the Newton-Raphson method consistently achieves convergence in a shorter time, as well as produces similar values of implied volatility. The genetic algorithm proved to be more robust to variation and was able to obtain a wider range of implied volatility. The genetic algorithm method also requires a larger number of iterations or function evaluations.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Implied Volatility, Newton-Raphson, Algoritma Genetika, Opsi Call Basket, Black-Scholes, Implied Volatility, Newton-Raphson, Genetic Algorithm, Basket Call Option, Black-Scholes.
Subjects:	H Social Sciences > HG Finance H Social Sciences > HG Finance > HG4529.5 Portfolio management Q Science > QA Mathematics > QA371 Differential equations--Numerical solutions
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Tri Darien Nahwa Firdausiah
Date Deposited:	23 Jul 2025 02:06
Last Modified:	23 Jul 2025 02:07
URI:	http://repository.its.ac.id/id/eprint/120728

Actions (login required)

View Item