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Evolutionary dynamics of the cryptocurrency market
Abeer ElBahrawy1, Laura Alessandretti1, Anne Kandler2
1Department of Mathematics-City, University of London-Northampton Square, London EC1V 0HB, UK.
Royal Society Open Science
|January 2, 2018
Summary
The cryptocurrency market shows stable statistical properties despite rapid growth and continuous emergence/disappearance of digital assets. An ecological model explains market behavior, linking evolution and cryptocurrency dynamics.
Area of Science:
- Financial Markets
- Complex Systems
- Computational Economics
Background:
- The cryptocurrency market rapidly expanded, exceeding $100 billion in June 2017.
- Existing research primarily focused on individual cryptocurrencies, neglecting a holistic market analysis.
Purpose of the Study:
- To analyze the historical behavior of the entire cryptocurrency market.
- To identify stable statistical properties amidst market volatility and growth.
- To explore the applicability of ecological models to cryptocurrency market dynamics.
Main Methods:
- Analysis of 1469 cryptocurrencies introduced between April 2013 and May 2017.
- Statistical analysis of market capitalization, active cryptocurrency counts, market share distribution, and turnover.
- Application of the neutral model of evolution from ecology.
Main Results:
- Cryptocurrency market capitalization exhibited super-exponential growth.
- Key statistical properties such as the number of active cryptocurrencies, market share distribution, and turnover remained stable over years.
- The neutral model of evolution successfully reproduced several empirical observations without assuming selective advantages.
Conclusions:
- The cryptocurrency market exhibits stable underlying statistical properties despite its rapid expansion and dynamic nature.
- Ecological modeling, specifically the neutral model, provides a viable framework for understanding cryptocurrency market dynamics.
- This study establishes a formal link between ecological modeling and cryptocurrency market analysis, suggesting avenues for future research.
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