Finding attractive technical patterns in cryptocurrency markets

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{ha:Memetic_Computing,

• author = "Sungjoo Ha and Byung-Ro Moon",
• title = "Finding attractive technical patterns in cryptocurrency markets",
• journal = "Memetic Computing",
• year = "2018",
• volume = "10",
• number = "3",
• pages = "301--306",
• month = sep,
• keywords = "genetic algorithms, genetic programming, Technical patterns, Cryptocurrency, Algorithmic trading",
• ISSN = "1865-9292",
• URL = "http://rdcu.be/IJDd",
• URL = "https://doi.org/10.1007/s12293-018-0252-y",
• DOI = "doi:10.1007/s12293-018-0252-y",
• size = "6 pages",
• abstract = "The cryptographic currency market is an emerging venue for traders looking to diversify their investments. We investigate the use of genetic programming (GP) for finding attractive technical patterns in a cryptocurrency market. We decompose the problem of automatic trading into two parts, mining useful signals and applying them to trading strategies, and focus our attention on the former. Extensive experiments are performed to analyse the factors that affect the quality of the solutions found by the proposed GP system. With the introduction of domain knowledge through extended function sets and the inclusion of diversity preserving mechanism, we show that the proposed GP system successfully finds attractive technical patterns. Out-of-sample performance of the patterns indicates that the GP consistently finds signals that are profitable and frequent. A trading simulation with the generated patterns suggests that the captured signals are indeed useful for portfolio optimization.",
• notes = "School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Korea",

}

Genetic Programming entries for Sungjoo Ha Byung-Ro Moon

Citations