STATISTICAL ANALYSIS OF THE DYNAMICS OF THE COST OF APARTMENTS IN THE SECONDARY RESIDENTIAL REAL ESTATE MARKET OF MOSCOW

Abstract

The relevance of the topic. The need to track changes in the value of residential real estate and determine the best moment to purchase secondary real estate in Moscow is of particular importance in modern conditions. Goal. Creation of a model to describe the influence of factors on the variation in the value of real estate in the secondary housing market in Moscow. Methodology. Machine learning approaches were used to create the model, and the classical accuracy metric was used to evaluate its performance — the square root of the root-mean-square error between the test sample not participating in the training of the model and the prediction of the model. Results and conclusions. It is advisable to purchase real estate in June, since a sharp increase begins in July after a decline in the previous month. Prices are steadily rising every year, so real estate in Moscow is a good option for investment. Scope of application. The scope of regulation of the housing market at the national and local levels. Research in the field of modeling time series and complex economic systems. Directions for further research: work to improve the accuracy of the model through a functional design approach and the use of additional variables describing the filling of apartments for sale. Also adding adjustments to the model for the local location of the property in Moscow