Perbandingan Perhitungan Harga Opsi Beli Indeks S&P 500 Menggunakan Model Black-Scholes dan Artificial Neural Network = Comparison of Pricing Call Options of S&P 500 Index Funds Using Black-Scholes and Artificial Neural Network

Priscilla, Stella (2019) Perbandingan Perhitungan Harga Opsi Beli Indeks S&P 500 Menggunakan Model Black-Scholes dan Artificial Neural Network = Comparison of Pricing Call Options of S&P 500 Index Funds Using Black-Scholes and Artificial Neural Network. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Opsi mengalami perkembangan yang signifikan dalam perdagangan derivatif belakangan ini. Terdapat berbagai metode untuk perhitungan harga opsi, yakni metode tradisional yang masih bergantung pada batasan dan asumsi, serta metode machine learning yang sedang dikembangkan. Penelitian ini bertujuan membandingkan metode Black-Scholes dan artificial neural network dalam option pricing. Data yang digunakan merupakan data opsi beli untuk indeks saham Standard and Poor 500 dengan lima maturitas yang berbeda. Data kemudian dipartisi berdasarkan moneyness (in-the-money dan out-of-the-money) dan waktu menuju maturitas (pendek, menengah, panjang). Penerapan homonegenity hint juga digunakan pada metode artificial neural network. Perhitungan harga opsi dengan artificial neural network dilakukan menggunakan algoritma backpropagation. Galat dan akurasi selanjutnya dicari untuk setiap perhitungan harga opsi oleh kedua metode. Hasil dari penelitian ini menyatakan bahwa metode artificial neural network secara umum lebih unggul daripada Black-Scholes. Selain itu, partisi data berdasarkan moneyness tidak meningkatkan performa dari jaringan, sedangkan partisi data berdasarkan maturitas menghasilkan galat yang lebih kecil dan akurasi yang lebih tinggi. Penambahan variabel homogeneity hint sebagai input meningkatkan performa jaringan pada data out-of-the-money, maturitas menengah, dan maturitas panjang. Akan tetapi, penggunaan homogeneity hint tanpa stock price dan strike justru menurunkan kinerja dari neural network, sekalipun mengurangi durasi dari training

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Priscilla, StellaNIM00000016632UNSPECIFIED
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorSaputra, Kie Van IvankyNIDN0401038203UNSPECIFIED
Thesis advisorFerdinand, Ferry VincenttiusNIDN0323059001UNSPECIFIED
Additional Information: SK 112-15 PRI p 2019; 31001000245093
Uncontrolled Keywords: Artificial neural network; Black-Scholes; Backpropagation; Opsi; Moneyness; Homogeneity hint
Subjects: Q Science > QA Mathematics
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Depositing User: Nicholas Sio Pradiva
Date Deposited: 11 Nov 2021 07:13
Last Modified: 11 Nov 2021 07:13
URI: http://repository.uph.edu/id/eprint/43151

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