Peramalan indeks harga saham empat negara di Asia dengan metode ARMA-GARCH dan RNN sewaktu pandemi COVID-19 = Forecasting stock prices indices for four countries in Asia using ARMA-GARCH and RNN method during the COVID-19 pandemic

Michelle, Michelle (2022) Peramalan indeks harga saham empat negara di Asia dengan metode ARMA-GARCH dan RNN sewaktu pandemi COVID-19 = Forecasting stock prices indices for four countries in Asia using ARMA-GARCH and RNN method during the COVID-19 pandemic. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Indeks harga saham menjadi salah satu faktor penentu kemajuan ekonomi sebuah negara. Oleh karena itu, diperlukan pemodelan indeks harga saham. Indeks harga saham merupakan suatu bentuk deret waktu yang sekuensial dalam suatu rentang waktu tertentu. Maka dari itu, pemodelan untuk indeks harga saham menggunakan metode deret waktu Autoregressive Moving Average-Generalized Autoregressive Heteroscedasticity (ARMA-GARCH) dan Recurrent Neural Network (RNN). Model indeks harga saham ini dilakukan untuk empat negara di Asia yaitu Cina, Indonesia, Jepang dan Korea Selatan. Data saham yang diperoleh akan dimodelkan dengan metode deret waktu ARMA-GARCH dan metode RNN yang digunakan untuk meramalkan harga saham selama dua periode selama pandemi COVID-19 yaitu dari Januari 2020 hingga Desember 2021 untuk tujuh hari ke depan. Hasil akhir dari R square dari kedua model yang digunakan akan dibandingkan untuk mendapatkan model terbaik dalam melakukan peramalan terhadap indeks harga saham keempat negara di Asia sewaktu pandemi. Berdasarkan hasil R Square didapatkan bahwa metode RNN memiliki nilai R Square yang lebih tinggi yaitu Cina sebesar 0,72789521, Indonesia 0,72295446, Jepang 0,85231171, dan Korea Selatan sebesar 0,92161454. Sedangkan untuk R Square model ARMA-GARCH untuk keempat negara yaitu Cina sebesar 0,1803618, Indonesia 0,1927775, Jepang 0,1335843, dan Korea Selatan 0,1511188. / Stock price index is one of the factors that determines a country’s economic growth. Therefore, stock price index modeling is needed. The stock price index is a form of sequential time series in a certain time span. Therefore, the modeling for the stock price index uses the time series method Autoregressive Moving Average-Generalized Autoregressive Heteroscedasticity (ARMA-GARCH) and Recurrent Neural Network (RNN). This stock price index model is carried out for four countries in Asia, namely China, Indonesia, Japan and South Korea. The stock data obtained will be modeled with the time series ARMA-GARCH model and RNN model which are used to forecast stock prices for two periods during the COVID-19 pandemic from January 2020 to December 2021 for the next seven days. The final result of R square from the two models used will be compared to get the best model for forecasting the stock price indexes of the four Asian countries during the pandemic. Based on the results of R Square, it was found that the RNN method had a higher value of R Square, namely China at 0,72789521, Indonesia 0,72295446, Japan 0,85231171, and Korea at 0,92161454. Meanwhile for R Square the ARMA-GARCH model for the four countries namely China is 0,1803618, Indonesia is 0,1927775, Japan is 0,1335843, and South Korea is 0,1511188.

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• Peramalan indeks harga saham empat negara di Asia dengan metode ARMA-GARCH dan RNN sewaktu pandemi COVID-19 = Forecasting stock prices indices for four countries in Asia using ARMA-GARCH and RNN method during the COVID-19 pandemic. (deposited 07 Jul 2022 01:42) [Currently Displayed]

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