Hierarchical structure in phonographic market

TL;DR

This paper applies topological and correlation analysis methods to the phonographic market, revealing a meaningful economic taxonomy and hierarchical structure based on artists' record sales and genre relevance.

Contribution

It introduces the use of Minimal Spanning Tree and correlation lifetime analysis to the phonographic market, a novel approach outside traditional stock market applications.

Findings

Hierarchical structure of the phonographic market identified

Correlation-based taxonomy reveals genre relevance

Methodology applicable to other asset markets

Abstract

I find a topological arrangement of assets traded in a phonographic market which has associated a meaningful economic taxonomy. I continue using the Minimal Spanning Tree and the Life-time Of Correlations between assets, but now outside the stock markets. This is the first attempt to use these methods on phonographic market where we have artists instead of stocks. The value of an artist is defined by record sales. The graph is obtained starting from the matrix of correlations coefficient computed between the world's most popular 30 artists by considering the synchronous time evolution of the difference of the logarithm of weekly record sales. This method provides the hierarchical structure of phonographic market and information on which music genre is meaningful according to customers.