Application of Machine Learning Algorithms for Bitcoin Automated Trading

Kamil Piotr Żbikowski

Abstract

The aim of this paper is to compare and analyze different approaches to the problem of automated trading on the Bitcoin market. We compare simple technical analysis method with more complex machine learning models. Experimental results showed that the performance of tested algorithms is promising and that Bitcoin market is still in its youth, and further market opportunities can be found. To the best of our knowledge, this is the first work that tries to investigate applying machine learning methods for the purpose of creating trading strategies on the Bitcoin market.
Author Kamil Piotr Żbikowski II
Kamil Piotr Żbikowski,,
- The Institute of Computer Science
Pages161-168
Publication size in sheets0.5
Book Ryżko Dominik Paweł, Gawrysiak Piotr, Kryszkiewicz Marzena, Rybiński Henryk (eds.): Machine Intelligence and Big Data in Industry, Studies in Big Data, vol. 19, 2016, Springer International Publishing Switzerland, ISBN 978-3-319-30314-7, [978-3-319-30315-4], 236 p., DOI:10.1007/978-3-319-30315-4 document.gif
DOIDOI:10.1007/978-3-319-30315-4_14
URL http://link.springer.com/chapter/10.1007/978-3-319-30315-4_14
projectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 18-05-2015, end date 30-11-2016, II/2015/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
File
01230152.pdf (file archived - login or check accessibility on faculty) 01230152.pdf 333.22 KB
Score (nominal)15
ScoreMinisterial score = 15.0, 27-03-2017, BookChapterSeriesAndMatConfByIndicator
Ministerial score (2013-2016) = 15.0, 27-03-2017, BookChapterSeriesAndMatConfByIndicator
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