Trading cryptocurrencies using algorithmic average true range systems
Gil Cohen
School of Management of Western Galilee Academic College, Israel
: J Comput Eng Inf Technol
Abstract
This research makes the first attempt to design, optimize and use average true range (ATR)-based trading systems for five popular cryptocurrencies. We used particle swarm optimization procedures to optimize systems with multiple objectives that are based on the ATR concept. Our aim was to determine the best configurations for each system that would maximize net profits, the profit factor, and the percentage of profitable trades. We demonstrate that the ATR based systems can predict the price trends of the examined cryptocurrencies. Our results also indicate that optimized Keltner Channel-based systems improve the ability of the stand-alone optimized ATR systems to forecast trends, net profits, and the profit factor. Finally, both systems perform better for long trades than for short trades. Of membrane receptor glycoproteins by non-myeloid and non-lymphoid cellular types on the influence of viruses or viral antigens, of malignant cells/ antigens, etc., was proposed.
Biography
Gil Cohen is the head of the Management department at Western Galilee Academic College. Gil is a finance expert who published more than 60 papers and 2 books on different finance issues. Professor Cohen also serves as an advisor to global firms on financial issues such as dividend policy and acquisitions.
