PERAMALAN RETURN SAHAM BANK CENTRAL ASIA MENGGUNAKAN SELF EXCITING THRESHOLD AUTOREGRESSIVE – GENETIC ALGORITHM

Tesalonika Putri, Irhamah Irhamah
Submission Date: 2016-01-26 08:07:43
Accepted Date: 2016-04-28 10:46:38

Abstract


Tujuan utama investor melakukan investasi adalah mendapatkan return investasi yang sesuai dengan apa yang telah diinvestasikannya. Untuk mendapatkan hasil investasi yang te-pat, investor perlu mengetahui kondisi return saham di masa yang akan datang dengan tingkat resiko yang kecil. BCA meru-pakan salah satu perusahaan yang paling diminati oleh investor karena BCA menduduki peringkat ke 4 berdasarkan pengu-kuran kinerja perusahaan dalam peningkatan kekayaan yang dihasilkan perusahaan di atas return minimal. Kasus return sa-ham BCA mengikuti pola deret waktu nonlinear sehingga dide-kati dengan salah satu metode deret waktu nonlinear Self Exci-ting Threshold Autoregressive (SETAR). Model SETAR mem-bagi data menjadi beberapa regime berdasarkan nilai threshold yang diambil dari lag deret waktu return saham BCA tersebut. Namun sering dijumpai permasalahan dalam memperoleh model terbaik. Pada penelitian ini dilakukan optimasi estimasi para-meter model SETAR dengan genetic algorithm (GA) untuk me-ngatasi hal tersebut. GA melakukan proses pencarian solusi ter-baik berdasarkan kumpulan solusi. Pemodelan return saham BCA dilakukan menggunakan model SETAR, SETAR GA dan ARIMA. Model terbaik adalah model subset SETAR (2,[1,3,4],1) menggunakan optimasi genetic algorithm, karena menghasilkan akurasi peramalan paling tinggi dibandingkan model.

Keywords


Return Saham;Self Exciting Threshold Autoregressive;Genetic Algorithm;ARIMA

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