Masters thesis, University of Vaasa, Faculty of Business Studies, Department of Accounting and Finance .
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: The cryptocurrency markets have experienced a drastic increase in trading volume and prices since the global realization of blockchain technologies’ potential in the mid-2017. The market capitalization of the cryptocurrency markets increased from only $18 billion on January 1st, 2017 to $565 billion on December 31st, 2017. Thus, it is important to understand the market’s current operating state. This research aims to test whether price and volume data from the cryptocurrency markets conform with Benford’s Law and is the first research conducted in this manner. Similar research performed with data from the international financial markets show that price and volume data conform with the Benford’s Law distribution, which is also the expected result of this study. The data is gathered from coinmarketcap.com and includes 30 of the top 100 largest cryptocurrencies determined by market capitalization. Benford’s Law offers distributions for first, second and first-two occurring digits of numbers in naturally formed data sets. If the distribution deviates from Benford’s Law, it can be caused by an unnatural data formation process, low quality of data or insufficient data. This study also offers theoretical aspects affecting the cryptocurrency markets and its data formation. The authenticity of the use of Benford’s Law as a data analyzation tool is emphasized by the fact that it is frequently used in research and as a fraud detection tool in auditing worldwide. Three tests are conducted for both entire price- and volume data sets. As a further assessment, each subsample included is tested individually. The results show that when testing entire data sets, they closely conform with Benford’s Law. Interestingly, when testing the subsamples, only two subsamples of the volume data set conform with Benford’s Law at some level. Each price data subsample fails at least one of the three tests. Furthermore, the results show that the volume data conforms far more closely with Benford’s Law than the price data. The results indicate that the majority of the subsamples experience something else than a natural data formation process. This gives direction for further research and assessments.
Bibtex:
@phdThesis{,
AUTHOR = {Henrik Wist},
TITLE = {Assessing The Conformity Of Cryptocurrency Market Data With Benford’s Law},
SCHOOL = {University of Vaasa},
YEAR = {2019},
TYPE = {Thesis ({Masters})},
URL = {https://osuva.uwasa.fi/bitstream/handle/10024/9631/osuva_8754.pdf?sequence=1},
}
Reference Type: Thesis
Subject Area(s): Accounting, Economics