Beauty is in the bid of the beholder: An empirical basis for style

We develop a method for classification of works of art based on their price dynamics. The method is in the same spirit as factor models commonly used within financial economics. Factor models assume that price dynamics of assets are related to underlying fundamental characteristics. We assume that such characteristics exist for works of art, and that they are associated with what we intuitively think of as style. We use a clustering algorithm to group artists that represent similar styles. This algorithm is specifically well-suited for situations where statistical distributions are far from normal - a description we believe fits well with markets for art. We test the method empirically on a ten-year sample of price data for paintings by 58 artists. Even with this limited data set, we clearly identify five groups and show that these are related to a standard classification of style.