Literature DB >> 33434209

Behavioral structure of users in cryptocurrency market.

Ayana T Aspembitova1,2, Ling Feng2,3, Lock Yue Chew1,4,5.   

Abstract

Human behavior as they engaged in financial activities is intimately connected to the observed market dynamics. Despite many existing theories and studies on the fundamental motivations of the behavior of humans in financial systems, there is still limited empirical deduction of the behavioral compositions of the financial agents from a detailed market analysis. Blockchain technology has provided an avenue for the latter investigation with its voluminous data and its transparency of financial transactions. It has enabled us to perform empirical inference on the behavioral patterns of users in the market, which we explore in the bitcoin and ethereum cryptocurrency markets. In our study, we first determine various properties of the bitcoin and ethereum users by a temporal complex network analysis. After which, we develop methodology by combining k-means clustering and Support Vector Machines to derive behavioral types of users in the two cryptocurrency markets. Interestingly, we found four distinct strategies that are common in both markets: optimists, pessimists, positive traders and negative traders. The composition of user behavior is remarkably different between the bitcoin and ethereum market during periods of local price fluctuations and large systemic events. We observe that bitcoin (ethereum) users tend to take a short-term (long-term) view of the market during the local events. For the large systemic events, ethereum (bitcoin) users are found to consistently display a greater sense of pessimism (optimism) towards the future of the market.

Entities:  

Year:  2021        PMID: 33434209      PMCID: PMC7802929          DOI: 10.1371/journal.pone.0242600

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  9 in total

1.  Economic fluctuations and anomalous diffusion

Authors: 
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  2000-09

2.  Statistical properties of share volume traded in financial markets

Authors: 
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  2000-10

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Authors:  Vasiliki Plerou; H Eugene Stanley
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2007-10-12

4.  Linking agent-based models and stochastic models of financial markets.

Authors:  Ling Feng; Baowen Li; Boris Podobnik; Tobias Preis; H Eugene Stanley
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-14       Impact factor: 11.205

5.  Stock return distributions: tests of scaling and universality from three distinct stock markets.

Authors:  Vasiliki Plerou; H Eugene Stanley
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-03-19

6.  Do the rich get richer? An empirical analysis of the Bitcoin transaction network.

Authors:  Dániel Kondor; Márton Pósfai; István Csabai; Gábor Vattay
Journal:  PLoS One       Date:  2014-02-05       Impact factor: 3.240

7.  Fitness preferential attachment as a driving mechanism in bitcoin transaction network.

Authors:  Ayana Aspembitova; Ling Feng; Valentin Melnikov; Lock Yue Chew
Journal:  PLoS One       Date:  2019-08-23       Impact factor: 3.240

Review 8.  Where Is Current Research on Blockchain Technology?-A Systematic Review.

Authors:  Jesse Yli-Huumo; Deokyoon Ko; Sujin Choi; Sooyong Park; Kari Smolander
Journal:  PLoS One       Date:  2016-10-03       Impact factor: 3.240

9.  Clustering algorithms: A comparative approach.

Authors:  Mayra Z Rodriguez; Cesar H Comin; Dalcimar Casanova; Odemir M Bruno; Diego R Amancio; Luciano da F Costa; Francisco A Rodrigues
Journal:  PLoS One       Date:  2019-01-15       Impact factor: 3.240

  9 in total

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