 Blockchain metrics and indicators in cryptocurrency tradingJuan C. King, Roberto Dale and José M. Amigó Chaos, Solitons & Fractals, 2024, vol. 178, issue C Abstract: The objective of this paper is the construction of new indicators that can be useful to operate in the cryptocurrency market. These indicators are based on public data obtained from the blockchain network, specifically from the nodes that make up Bitcoin mining. Therefore, our analysis is unique to that network. The results obtained with numerical simulations of algorithmic trading and prediction via statistical models and Machine Learning demonstrate the importance of variables such as the hash rate, the difficulty of mining or the cost per transaction when it comes to trade Bitcoin assets or predict the direction of price. Variables obtained from the blockchain network will be called here blockchain metrics. The corresponding indicators (inspired by the “Hash Ribbon”) perform well in locating buy signals. From our results, we conclude that such blockchain indicators allow obtaining information with a statistical advantage in the highly volatile cryptocurrency market. Keywords: Time series; Blockchain; Bitcoin; Cryptocurrency; Hash ribbon; Hash rate; Algorithmic trading; Prediction; Machine learning; Adaptive markets; Fundamental analysis; Technical analysis; Mathematical indicators (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012079 DOI: 10.1016/j.chaos.2023.114305 Access Statistics for this article Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros More articles in Chaos, Solitons & Fractals from Elsevier |
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