Time Series Movements in Art Prices

Abstract

The aim of our paper is to understand the price behavior of artworks, mainly graphics sold in one selected Czech auction house. The publicly available information obtained from internet auction systems provide price time series of monitored painters works. We focused on the prediction of the price development using linear regression methods. Approach presented in our paper provided finding an artist whose painting prices are rising statistically significantly. We worked with a dataset of total of 398 paintings by 10 Czech painters. Authors with at least 11 auctioned paintings will be used for statistical analysis. We did not focus on art auctions with the most expensive paintings, but on paintings and graphics that are affordable for the general population. The graphics dominated the data collected. The goal of our study is to estimate the annual change in works of art in the Czech Republic and compare with respect to inflation in the period from 2014 to 2020. In the final discussion, an assessment of the further price development of works of art is also discussed.