Analysis of the cryptocurrency market applying different prototype-based clustering techniques



Downloads per month over past year

Lorenzo Álvarez, Luis and Arroyo Gallardo, Javier (2022) Analysis of the cryptocurrency market applying different prototype-based clustering techniques. Financial Innovation . ISSN 2199-4730

[thumbnail of s40854-021-00310-9.pdf]
Creative Commons Attribution.


Official URL:


Since the appearance of Bitcoin, cryptocurrencies have experienced enormous growth not only in terms of capitalization but also in number. As a result, the cryptocurrency market can be an attractive arena for investors as it offers many possibilities, but a difficult one to understand as well. In this work, we aim to summarize and segment the whole cryptocurrency market in 2018 with the help of data analysis tools. We will use three different partitional clustering algorithms each of them using a different representation for cryptocurrencies, namely: yearly mean and standard deviation of the returns, distribution of returns, and time series of returns. Since each representation will provide a different and complementary perspective of the market, we will also explore the combination of the three clustering results to obtain a fine-grained analysis of the main trends of the market. Finally, we will analyze the association of the clustering results with other descriptive features of the cryptocurrencies, including the age, technological attributes, and financial ratios derived from them. This will help to enhance the profiling of the clusters with additional insights. As a result, this work offers a description of the market and a methodology that can be reproduced by investors that want to understand the main trends on the market.

Item Type:Article
Uncontrolled Keywords:Fintech; Data Sciences; Cryptocurrency; Electronic market; Clustering
Subjects:Sciences > Computer science > Artificial intelligence
Sciences > Statistics > Multivariate analysis
Social sciences > Economics > Finance
JEL:G17 Financial Forecasting and Simulation
ID Code:63821
Deposited On:02 Feb 2021 09:28
Last Modified:07 Feb 2022 11:49

Origin of downloads

Repository Staff Only: item control page