ملخص
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.
| اللغة الأصلية | الإنجليزيّة |
|---|---|
| رقم المقال | 103 |
| دورية | Journal of Risk and Financial Management |
| مستوى الصوت | 12 |
| رقم الإصدار | 2 |
| المعرِّفات الرقمية للأشياء | |
| حالة النشر | نُشِر - يونيو 2019 |
| منشور خارجيًا | نعم |
بصمة
أدرس بدقة موضوعات البحث “Next-Day Bitcoin Price Forecast'. فهما يشكلان معًا بصمة فريدة.قم بذكر هذا
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