Investigating Market Behavior Correlations between Classified Tokens using the International Token Classification Framework

This paper explores the novel International Token Classification framework, creates a large sample set of tokens classified according to the framework, clusters the tokens into groups, and performs statistical analysis regarding the selected token’s correlation. It investigates how the current token landscape looks by classifying 200 tokens. These tokens are clustered in three different groups, payment token, DeFi ecosystem token, and network utility tokens. We first investigate whether tokens tend to move in the same direction with the tokens from their group, and secondly, we use a created average portfolio return to compare the single token return with the different groups. According to the results, we mainly found utility and payment tokens from the IT and Finance industries. Out of the three groups, tokens clustered in the payment token group showed the highest correlations within the group and with their own group portfolio average. Overall, we conclude that the classification indeed has an impact on the relationship of token pairs. However, the results show that many more factors influence the market behavior of tokens, which should also be considered. Keywords: Blockchain; token; correlation; classification; Bitcoin.This paper explores the novel International Token Classification framework, creates a large sample set of tokens classified according to the framework, clusters the tokens into groups, and performs statistical analysis regarding the selected token’s correlation. It investigates how the current token landscape looks by classifying 200 tokens. These tokens are clustered in three different groups, payment token, DeFi ecosystem token, and network utility tokens. We first investigate whether tokens tend to move in the same direction with the tokens from their group, and secondly, we use a created average portfolio return to compare the single token return with the different groups. According to the results, we mainly found utility and payment tokens from the IT and Finance industries. Out of the three groups, tokens clustered in the payment token group showed the highest correlations within the group and with their own group portfolio average. Overall, we conclude that the classification indeed has an impact on the relationship of token pairs. However, the results show that many more factors influence the market behavior of tokens, which should also be considered. Keywords: Blockchain; token; correlation; classification; Bitcoin