The Complexity of Cryptocurrencies Algorithmic Trading

Gil Cohen, Mahmoud Qadan

Research output: Contribution to journalArticlepeer-review


In this research, we provided an answer to a very important trading question, what is the optimal number of technical tools in order to achieve the best trading results for both swing trade that uses daily bars and intraday trade that uses minutes bars? We designed Machine Learning (ML) systems that can trade four major cryptocurrencies: Bitcoin, Ethereum, BNB, and Solana. We found that more indicators do not necessarily mean better trading performance. Swing traders that use daily bars should trade Bitcoin and Solana using Ichimoku Cloud (IC) plus Moving Average Convergence Divergence (MACD), Ethereum with IC plus Chaikin Money Flow (CMF), and BNB with IC alone. With regard to intraday trading, we documented that different cryptocurrencies should be trading using different time frames. These results emphasize that the optimal number of indicators that are used to trade daily bars is one or, at maximum, two. The Multi-Layer (MUL) system that consists of all three examined technical indicators failed to improve the trading results for both days (swing) and intraday trades. The main implication of this study for traders is that more indicators does not necessarily improve trades performances.

Original languageEnglish
Article number2037
Issue number12
StatePublished - 1 Jun 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


  • cryptocurrencies
  • intraday
  • swing
  • technical indicators
  • trading

ASJC Scopus subject areas

  • Mathematics (all)


Dive into the research topics of 'The Complexity of Cryptocurrencies Algorithmic Trading'. Together they form a unique fingerprint.

Cite this