Ethereum Value Forecasting Model using Autoregressive Integrated Moving Average (ARIMA)

Authors

  • Didik Gunawan Department of Management, Sekolah Tinggi Ilmu Ekonomi Bina Karya, Tebing Tinggi, Sumatera Utara, Indonesia
  • Indriana Febrianti Department of Management, Sekolah Tinggi Ilmu Ekonomi Bina Karya, Tebing Tinggi, Sumatera Utara, Indonesia

DOI:

https://doi.org/10.56225/ijassh.v2i1.151

Keywords:

ARIMA, Cryptocurrency, Ethereum, Blockchain, Forecasting

Abstract

The purpose of this study is to test the ability of the ARIMA model to predict the value of Ethereum, especially during economic shocks such as the current COVID-19 pandemic. The population in this study is Ethereum value weekly data for the period January 2017 to December 2020, so there are 208 samples in this study. The results showed that the use of the ARIMA method in predicting the value of Ethereum got poor results, where the forecast value was very much different from the actual value. This is evidenced from the results of the accuracy test using MAPE which got a result of 51.94%. On the other hand, the economic conditions that are experiencing uncertainty due to the COVID-19 pandemic and the emergence of deficit (decentralized finance) in early 2021 have pushed up a very significant increase in the value of Ethereum so that the error standard is higher and reduces the ability of the ARIMA model to predict the value of Ethereum. Further research is recommended to use a more advanced model such as the Autoregressive Fractionally Integrated Moving Average (AFRIMA) in order to obtain a better forecast value.

References

Antonopoulos, A. M., & Wood, G. (2018). Mastering Ethereum: building smart contracts and dapps. O’reilly Media.

Arviana, G. N. (2023). Cryptocurrency: Arti, Fungsi, Jenis-Jenis, Kelebihan, dan Kekurangan. Cryptocurrency: Pengertian, Fungsi, Jenis, Cara Kerja Dan Manfaat Mengenal. https://glints.com/id/lowongan/cryptocurrency-adalah/#.ZArW5HZBy5c

Chowdhury, R., Rahman, M. A., Rahman, M. S., & Mahdy, M. R. C. (2020). An approach to predict and forecast the price of constituents and index of cryptocurrency using machine learning. Physica A: Statistical Mechanics and Its Applications, 551, 124569. https://doi.org/10.1016/j.physa.2020.124569

David, S. A., Inacio, C. M. C., Nunes, R., & Machado, J. A. T. (2021). Fractional and fractal processes applied to cryptocurrencies price series. Journal of Advanced Research, 32, 85–98. https://doi.org/10.1016/j.jare.2020.12.012

Hartati. (2017). Penggunaan Metode Arima Dalam Meramal Pergerakan Inflasi. Jurnal Matematika, Saint Dan Teknlogi, 18, 1–10.

Huda, N., & Hambali, R. (2020). Risiko dan Tingkat Keuntungan Investasi Cryptocurrency. 17, 72–84.

Kim, H. M., Bock, G. W., & Lee, G. (2021). Predicting Ethereum prices with machine learning based on Blockchain information. Expert Systems with Applications, 184(February 2020), 115480. https://doi.org/10.1016/j.eswa.2021.115480

Lilipaly, G. S., Hatidja, D., & Kekenusa, J. S. (2014). Prediksi Harga Saham PT. BRI, Tbk. Menggunakan Metode Arima (Autoregressive Integrated Moving Average). 14.

Nugraha, I., & Sutopo, W. (2018). Perkembangan Teknologi Blockchain Dalam Traceability System: Studi Kasus Penelitian Terindeks Scopus. 22005(2007), 199–208.

Poongodi, M., Sharma, A., Vijayakumar, V., Bhardwaj, V., Sharma, A. P., Iqbal, R., & Kumar, R. (2020). Prediction Of The Price Of Ethereum Blockchain Cryptocurrency In An Industrial Finance System. Computers and Electrical Engineering, 81. https://doi.org/10.1016/j.compeleceng.2019.106527

Salwa, N., Tatsara, N., Amalia, R., & Zohra, A. F. (2018). Peramalan Harga Bitcoin Menggunakan Metode ARIMA ( Autoregressive Integrated Moving Average ). 1(1), 21–31.

Susanti, R., & Adji, A. R. (2020). Analisis Peramalan Ihsg Dengan Time Series Modeling Arima ( Analysis Of Indonesia Composite Index ( Ihsg ) Forecasting With Arima Time Series Modeling ). Jurnal Manajemen Kewirausahaan, 17(01), 97–106.

Tandon, C., Revankar, S., Palivela, H., & Parihar, S. S. (2021). How can we predict the impact of the social media messages on the value of cryptocurrency? Insights from big data analytics. International Journal of Information Management Data Insights, 1(2), 100035. https://doi.org/10.1016/j.jjimei.2021.100035

Utami, D. N. (2021). Beda Pandangan Pelaku Pasar Soal Kripto vs Saham Artikel ini telah tayang di Bisnis.com dengan judul “Beda Pandangan Pelaku Pasar Soal Kripto vs Saham”. https://market.bisnis.com/read/20210416/94/1381906/beda-pandangan-pelaku-pasar-soal-kripto-vs-saham

Downloads

Published

2023-02-28

How to Cite

Gunawan, D., & Febrianti, I. (2023). Ethereum Value Forecasting Model using Autoregressive Integrated Moving Average (ARIMA). International Journal of Advances in Social Sciences and Humanities, 2(1), 29–35. https://doi.org/10.56225/ijassh.v2i1.151
Abstract viewed = 211 times