STOCHASTIC PRICING MODEL FOR THE REAL ESTATE MARKET: FORMATION OF LOG-NORMAL GENERAL POPULATION

Abstract

We construct a stochastic model of real estate pricing. The method of the pricing construction is based on a sequential comparison of the supply prices. We proof that under standard assumptions imposed upon the comparison coefficients there exists an unique non-degenerated limit in distribution and this limit has the lognormal law of distribution. The accordance of empirical distributions of prices to thetheoretically obtained log-normal distribution we verify by numerous statistical data of real estate prices from Saint-Petersburg (Russia). For establishing this accordance we essentially apply the efficient and sensitive test of fit of Kolmogorov-Smirnov. Basing on “The Russian Federal Estimation Standard N2”, we conclude that the most probable price, i.e. mode of distribution, is correctly and uniquely defined under the log-normal approximation. Since the mean value of log-normal distribution exceeds the mode - most probable value, it follows that the prices valued by the mathematical expectation are systematically overstated.

Keywords

• рыночная стои мость недвижимости
• стохастичес кая модель ценообразования
• геомет рическое броуновское движение
• мода логарифмически нормального закона распределения
• применение критерия согласия колмогорова-смирнова
• real estate market value
• stochastic model of pricing
• geometric brownian motion
• mode of the logarithmi cally normal law distribution
• applications of the kolmogorov-smirnov test of fit