Volatilitas Kurs dan Saham Mengikuti Model EGARCH(1,1) Berdistribusi Versi Skew Normal dan Student-t

Didit Budi Nugroho; Anggita M Kusumawati; Leopoldus R Sasongko

doi:10.24843/JEKT.2020.v13.i02.p04

Didit Budi Nugroho Universitas Kristen Satya Wacana
Anggita M Kusumawati
Leopoldus R Sasongko

DOI: https://doi.org/10.24843/JEKT.2020.v13.i02.p04

Abstract

Studi ini membandingkan kinerja pencocokan model volatilitas GARCH(1,1) dan EGARCH(1,1) pada return kurs dan saham. Model mengasumsikan empat distribusi berbeda untuk error dari return: Normal, Skew-Normal (SN), Alpha-Skew Normal (ASN), dan Student-t. Data aset keuangan yang digunakan sebagai analisis perbandingan yaitu data kurs beli US Dollar (USD) dalam periode harian dari Januari 2010 sampai Desember 2017 dan data indeks saham FTSE100 dalam periode harian dari Januari 2000 sampai Desember 2013. Studi ini membandingkan metode Generalized Reduced Gradient (GRG) Non-Linier di Solver Excel dan metode Adaptive Random Walk Metropolis (ARWM) untuk mengestimasi model. Hasil menunjukkan bahwa metode GRG Non Linear Solver Excel memberikan estimasi yang serupa dengan metode ARWM dan tidak melanggar kendala model. Lebih lanjut, berdasarkan nilai Akaike Information Criterion (AIC), kedua data pengamatan menyediakan bukti bahwa model dengan distribusi Student-t adalah yang terbaik, diikuti oleh distribusi SN yang lebih baik daripada model dengan distribusi ASN dan Normal. Nilai AIC telah menyarankan model EGARCH(1,1) berdistribusi Student-t sebagai model pencocokan terbaik untuk kedua data pengamatan.

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