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Mochamad Ridwan, Mochamad
UNTAG Samarinda
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Journal : Scientific Journal of Informatics

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Comparison of ARIMA and GRU Models for High-Frequency Time Series Forecasting. Ridwan, Mochamad; Sadik, Kusman; Afendi, Farit Mochamad
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.45965

Abstract

Purpose: The purpose of this research is to assess the efficacy of ARIMA and GRU models in forecasting high-frequency stock price data, specifically minute-level stock data from HIMBARA banks. In time series analysis, time series data exhibit interesting interdependence among observations. Despite its popularity in time series forecasting, the ARIMA model has limitations in capturing complicated nonlinear patterns. Forecasting high-frequency data is becoming more popular as technology advances and more high-frequency data becomes available.Methods: In this study, we compare the ARIMA and GRU models in forecasting minute-level stock prices of HIMBARA banks. The data used consists of 62,921 minute-level stock data points for each bank in the HIMBARA group, collected in the year 2022. The GRU model was chosen because it is capable of capturing complex nonlinear patterns in time series data. Each method's predicting performance is assessed using the Mean Absolute Percentage Error (MAPE) statistic.Results: In terms of forecasting accuracy, the GRU model outperforms the ARIMA model. The GRU model achieves a MAPE of 0.77% for BMRI stock, while the ARIMA model achieves a MAPE of 4.09%. The GRU model predicts a MAPE of 0.34% for BBRI stock, while the ARIMA model predicts a MAPE of 3.02%. For BBNI stock, the GRU model obtains a MAPE of 0.63%, while the ARIMA model achieves a MAPE of 1.52%. The GRU model achieves a MAPE of 0.58% for BBTN stock, while the ARIMA model achieves a MAPE of 6.2%.Novelty: In terms of minute-level time series data modeling, research in Indonesia has been limited. This study adds a new perspective to the discussion by comparing two modeling approaches: the traditional ARIMA model and the sophisticated deep learning GRU model, both of which are applied to high-frequency data. Beyond the present scope, there are several promising future directions to pursue, such as anticipating intraday stock fluctuations. This unexplored zone not only contributes to the field of financial modeling but also has the ability to uncover intricate patterns in minute-level data, an area that has not been extensively studied in the Indonesian context.
Co-Authors Abdul Rachman Syam Tuasikal Abdullah, Khairul Hafezad Adelina Dhinik Puspitasari Advendi Kristiyandaru Afandi, Mokh Salis Agista, Yeskia Yudiana Ahmedov, Farruh Akbar, M. Khoirul Andhega Wijaya Anggara, Jaka Anung Priambodo Aprilia, Ema Apriyanti, Cikit Ardiyansyah, Nabilah Fafriliani Cendana, Wiputra Demir, Gí¶ní¼l TekkurÅŸun Dewantoro, Nova Dwi Dona Sandy Yudasmara Dopong, Maulana Malik Dwi Cahyo Kartiko Dwi Purwanto, Bagus Edi Setiawan Edi Supriyadi Elizabeth Yohanes Fadhila, Saptania Faridha Nurhayati Farit Mochamad Afendi Fernanda, Alfina Wahyu Firmansyah Prawironastro, Muhammad Bagas Gazali, Novri Gazali, Zeinol Gigih Siantoro Gusti Noorlitaria Achmad Hadistyana Mutiarahmi Hari Wisnu, Hari Hartati, Merri Sri HASANAH APRILIA, NISWATIN Heryanto Nur Muhammad Hofmeister, Martin Hutapia IRMA FEBRIYANTI Ishak, Asmadi Ismail, Ghulam Zaky Juheri Jumareng, Hasanuddin Juniarisca, Dwi Lorry Juniarto, Pudji Ketut Sukiyono Khumairoh, Vika Amel Kumara, Bima Prasetya Kusharyanti, Rina Kusman Sadik Kusuma, Sagita La Ode Ahmad Safar Tosungku, La Ode Ahmad Safar Lesmana, Diky M. E. Winarno Mahmudi, Agus Mardiansyah, Oktyanus Marvianissa, Eghie Maulana Malik, Aditya Maulana, Bagus Yudha Dwi Maulidya, Ayu Ningrum Mochamad Afif Baihaqi Mubarok, Muhammad Azmy Muchamad Arif Al Ardha Mudzaky, Azhar Nurin Mugiasih, Tri Restu Muhaiminul Aziz, Aat Mujtahidin, Afiq Hakim Ndhanni, Alvina Rahma Ningsih, Yuni Fitriyah Noorfitri, Karin Cetta Putri Nurokhman, Muhammad Habibu Nurrul Riyad Fadhli Octarrum, Devina Pelupessy, Yohanes Kristopel Prasetyanti, Nada Amelia Pratiwi, Alfina Diva Prawisma, Tri Jaka Setiyo Priambodo, R. Ervin Agung Prihanto, Junaidi Budi Putra, Wahyudi Nuryanto Dwi R Dimas Adityo Rahma Ndhanni, Alvina Rahman, Rizky Mulia Rahmawati, Indriya Ramania, Vanesa Gerdian Rani Sugiarni Rasifa, Nur Rohman, Mohamad Fathur Romdhon, Mustofa Romi Gunawan, Romi Sampurno, Moh. Wahyu Budi Sapto Wibowo Schwerer, Leon SETIYO HARTOTO Sharma, Muhammad Rexi Sholikhah, Anindya Mar'atus Siskha Putri Sayekti Sofiansyah, Agus Sri Panca Setyawati Suhada, Umi Suryaninungrum, Anis Taufik Taufik Taufiq Hidayat Theresia Amelia Pawitra Trisnawati, Silva Ayu Tuasikal, Abdul Rahman Syam Twiska Naufal Arsyah Ghiffari Vega Candra Dinata Waldi Novi Yarsah Wardoyo, Tri Yovhandra Ockta Yulianto, Achmad Yusnida Zhuka, Erika Mahardini