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Next-Day Bitcoin Price Forecast

School of Business and Law, University of Agder, 4630 Kristiansand, Norway
Department of Maritime Operations, University of South-Eastern Norway, 3184 Borre, Norway
Taylor’s Business School, Taylor’s University, 47500 Subang Jaya, Malaysia
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2019, 12(2), 103;
Received: 30 April 2019 / Revised: 10 June 2019 / Accepted: 14 June 2019 / Published: 20 June 2019
(This article belongs to the Special Issue Blockchain and Cryptocurrencies)
PDF [3326 KB, uploaded 20 June 2019]


This study analyzes forecasts of Bitcoin price using the autoregressive integrated moving average (ARIMA) and neural network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and without re-estimation of the forecast model for each step. For cross-validation of forecast results, we consider two different training and test samples. In the first training-sample, NNAR performs better than ARIMA, while ARIMA outperforms NNAR in the second training-sample. Additionally, ARIMA with model re-estimation at each step outperforms NNAR in the two test-sample forecast periods. The Diebold Mariano test confirms the superiority of forecast results of ARIMA model over NNAR in the test-sample periods. Forecast performance of ARIMA models with and without re-estimation are identical for the estimated test-sample periods. Despite the sophistication of NNAR, this paper demonstrates ARIMA enduring power of volatile Bitcoin price prediction. View Full-Text
Keywords: ARIMA; artificial neural network; Bitcoin; cryptocurrency; static forecast ARIMA; artificial neural network; Bitcoin; cryptocurrency; static forecast

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Munim, Z.H.; Shakil, M.H.; Alon, I. Next-Day Bitcoin Price Forecast. J. Risk Financial Manag. 2019, 12, 103.

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