Application of Machine Learning Algorithms for Bitcoin Automated Trading
Kamil Piotr Żbikowski
AbstractThe 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.
|Publication size in sheets||0.5|
|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|
|project||Development 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
|Score|| = 15.0, 27-03-2017, BookChapterSeriesAndMatConfByIndicator|
= 15.0, 27-03-2017, BookChapterSeriesAndMatConfByIndicator
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.