Visual autocorrelation of prices

Paintings are in essence about visual features of varying significance from which differences in their market prices originate. Studies normally investigate derivative sources of painting price determinants, which is reasonably understandable because the appreciation of an image is quite subjective. This paper provides an operational solution to the quantification of paintings based on a new concept termed as “visual autocorrelation” of prices (VAP). Considering the current empirical framework of spatial and temporal autocorrelation of prices, and using data on the paintings of two abstract expressionist artists, empirical results support the coherence of the VAP concept. Copyright Springer Science+Business Media New York 2013