Abnormal and normative cost indicators in the painting market

Abstract

The article examines the issue of determi­ning anomalous and normative value indicators on the painting market. This study is relevant, since quite often the calculated forecast value indicators of paintings differ significantly from the prices recorded as a result of their sale on the open market, and the reasons for such anomalous deviations are currently the subject of professional discussions. The purpose of the article is to present the results of studying the distribution of value indicators on the Ukrainian online painting market, demonstrate the possi­bility of identifying individual anomalous price groups for this type of product, and also describe the algorithm for calculating the predicted cost of paintings. The hypothesis is considered that based on the study of the distribution of value indicators of paintings, it is possible to identify an interval of samples whose cost is justified, as well as individual anomalous price groups of this type of product. The research methodology provided for: compiling a representative database of initial information on the cost of paintings, creating a regression mathematical model for predicting the value indicators of paintings, applying extrapolation procedures to predict the expected levels of deviation of forecast and actual value indicators. To achieve the goal, a database of initial information on 160 samples of paintings offered for sale on the Ukrainian online market has been created. The results of studying the distribution of specific value indi­cators of paintings are described. The possi­bility of identifying individual groups of anomalous value indicators of paintings in the created database has been considered. The possibilities of using extrapolation in the task of cost forecasting of paintings have been determined, and explanations have been given for the devia­tions between the observed and predicted value indicators on the market. Depending on the task facing the appraiser, the feasibility of identifying three main characteristics is shown – liquida­tion value, normative and maximum value within the available recorded information. An example of cost forecasting of a painting is given. The proposed algorithm for cost forecas­ting of paintings can be used in the areas of investment activities, forensic examination, risk insurance, collateral, auction business, and collecting.