Machine Learning-Based Bitcoin Time Series Analysis and Price Prediction Makine grenmesine Dayali Bitcoin Zaman Serisi Analizi ve Fiyati Tahmini

KÖYLÜ F., ÜLKER M.

2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023, Sivas, Türkiye, 11 - 13 Ekim 2023 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/asyu58738.2023.10296664
  • Basıldığı Şehir: Sivas
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: bitcoin, machine learning, random forest, regression, time series analysis, xgboost
  • Erciyes Üniversitesi Adresli: Evet

Özet

The accurate prediction of an uncertain future is crucial for society. Particularly when it comes to finance, where it holds vital importance for companies. Time series analysis is conducted to forecast the potential value of financial assets in the near future. Due to the impracticality of manually analyzing hundreds of indicators, machine learning methods are frequently employed. This study showcases the optimal value of the lag hyperparameter used in Random Forest and Extreme Gradient Boosting methods. The daily Bitcoin OHLCV data of a time series was enriched with indicators, and it was observed that the lag hyperparameter yielded the best results when considering the preceding 23 time series units.