Deep Learning Forecasting in Cryptocurrency High-Frequency Trading

Author:

Lahmiri Salim,Bekiros SteliosORCID

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Reference9 articles.

1. Fama EF. Random walks in stock market prices. Financial Anal J. 1995;51:75–80.

2. Bustos O, Pomares-Quimbaya A. Stock market movement forecast: a systematic review. Expert Syst Appl. 2020; 56, Article 113464.

3. Lahmiri S, Bekiros S. Cryptocurrency forecasting with deep learning chaotic neural networks. Chaos, Solitons Fractals. 2019;118:35–40.

4. Atsalakis GS, Atsalaki IG, Pasiouras F, Zopounidis C. Bitcoin price forecasting with neuro-fuzzy techniques. Eur J Oper Res. 2019;276:770–80.

5. Aggarwal D, Chandrasekaran S, Annamalai B. A complete empirical ensemble mode decomposition and support vector machine-based approach to predict Bitcoin prices. J Behav Exp Finance. 2020; 27, Article 100335.

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