Downloads: 161 | Views: 177
Research Paper | Statistics | Nigeria | Volume 8 Issue 10, October 2019
Estimating and Forecasting Bitcoin Daily Returns Using ARIMA-GARCH Models
Emaeyak Xavier Udom
Abstract: This paper provides an evaluation of the forecasting performance of hybrid ARIMA-GARCH model in forecasting Bitcoin daily price returns. We combined ARIMA and GARCH model with Normal, Studentís t and Skewed studentís t distributions. To make the series stationary, Bitcoin daily price data was transformed to Bitcoin daily returns. By using Box-Jenkins method, the appropriate ARIMA model was obtained and for capturing volatilities of the returns series GARCH (1, 1) models with Normal, Studentís t and Skewed studentís t distributions was used. To evaluate the performance of the models, the study employs two measures, RMSE and MAE. The results reveal that ARIMA (2, 0, 1) -GARCH (1, 1) with Normal distribution outperform the other three in terms of out-of-sample forecast with minimum RMSE and MAE. The findings can aid investors, market practitioners, financial institutions, policymakers, and scholars.
Keywords: ARIMA, GARCH, Bitcoin returns, Hybrid ARIMA-GARCH
Edition: Volume 8 Issue 10, October 2019,
Pages: 376 - 382
Similar Articles with Keyword 'ARIMA'
Research Paper, Statistics, Nigeria, Volume 10 Issue 11, November 2021Pages: 507 - 510
Modelling Auto - Crash Cases in Osun State, Nigeria
Salami Taofeek A | Adeyemi Adekunle M | Yusuf Jamal .A
Research Paper, Statistics, Nigeria, Volume 10 Issue 8, August 2021Pages: 734 - 744
Application of Autoregressive Integrated Moving Average Intervention Model for Corruption Index in Nigeria
Sadiq Nafisatu | Nweze N. O.  | Ibrahim Ahmed  | Mohammed Rilwan