Determination of price of an artwork is a fundamental problem in cultural economics. In this work we investigate what impact visual characteristics of a painting have on its price. We construct a number of visual features in CIELAB color space measuring complexity of the painting, its points of interest using Discrete symmetry transform, segmentation-based features using Felzenszwalb segmentation and Regions adjacency graph merging, local color features from segmented image, features based on Itten and Kandinsky theories, and utilize mixed-effects model with authors bias as fixed effect to study impact of these features on the painting price. We analyze the influence of the color on the example of the most complex art style - abstractionism, created by Kandinsky, for which the color is the primary basis. We use Itten’s theory - the most recognized color theory in art history, from which the largest number of subtheories was born. For this day it is taken as the base for teaching artists. We utilize novel dataset of 3,885 paintings collected from Christie’s and Sotheby’s and find that color harmony has a little explanatory power, color complexity metrics are impact price negatively and color diversity explains price well.