Subject. This article deals with the issues of financial modeling and forecasting of consumer demand in the primary residential real estate market. Objectives. The article aims to form a financial model for forecasting consumer demand in the primary residential real estate market in the context of the regions of the Russian Federation. Methods. For the study, I used an integrated approach to financial modeling of consumer demand, based on retrospective, systems, functional and structural, and correlation and regression analyses. Results. Based on the analysis of macroeconomic factors influencing demand indicators in the primary residential real estate market in Moscow, the Moscow Oblast, St. Petersburg and the Leningrad Oblast, the article presents a financial model for forecasting the number and volume of concluded transactions (equity participation agreements) using a correlation and regression model. Relevance. The formed financial model helps assess the levels of sensitivity of the forecast to certain macroeconomic factors in the primary residential real estate market in the context of the regions of the Russian Federation. It can be used in factor analysis of the changes in individual industry indicators, and can also be used in regulatory, investment, construction, and banking activities.
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