Development of a methodology for property valuation using the retrospective method of correlation-regression dependence

Abstract

The conducted research is based on information databases of real estate objects, where an important problem is that while there is a large amount of data, on the one hand, they are used for market research and mass valuation of real estate, but on the other hand, due to the lack of sufficient information or tools, do not allow to reflect the market situation fully. The paper shows the analysis of the use of data collection and processing of real estate data in different countries, research results and opportunities in the use and implementation of real estate data depending on the pricing factors. This paper considers economic and mathematical methods of evaluating the data set in the assessment of real estate objects, including the use of artificial intelligence. The reasonable confirmation of the hypothesis that the use of retrospective information of the most similar and comparable objects of analogues on price-forming factors for the assessed real estate object allows to determine the current market value using the retrospective method of correlation-regression dependence is carried out. The substantiation is given on the example of calculation of the market value of an arbitrarily selected real estate object. The conducted research partially displays the change in the value of the property object from the time factor based on the processing of the data set. As one of the price-forming factors are real indices of change in prices of real estate objects on the basis of several data sources. The conclusion summarizes the results of the study and the advantages of the method for the valuation of real estate objects, including the determination of cadastral value by the mass valuation method.

Keywords

• real estate classification
• information systems
• digital platforms
• open data
• data aggregators
• cadastral valuation