Use of Statistical Models for Simulating Transactions on the Real Estate Market

Abstract

Abstract The regularities and relations between real estate prices and the factors that shape them may be presented in the form of statistical models, thanks to which the diagnosis and prediction of prices is possible. A formal description of empirical observation presented in the form of regressive models also offers a possibility for creating certain phenomena in a virtual dimension. Market phenomena cannot be fully described with the use of determinist models, which clarify only a part of price variation. The predicted price is, in this situation, a special case of implementing a random function. Assuming that other implementations are also possible, regressive models may constitute a basis for simulation, which results in the procurement of a future image of the market. Simulation may refer both to real estate prices and transaction prices. The basis for price simulation may be familiarity with the structure of the analyzed market data. Assuming that this structure has a static character, simulation of real estate prices is performed on the basis of familiarity with the probability distribution and a generator of random numbers. The basis for price simulation is familiarity with model parameters and probability distribution of the random factor. The study presents the core and theoretical description of a transaction simulation on the real estate market, as well as the results of an experiment regarding transaction prices of office real estate located within the area of the city of Olsztyn. The result of the study is a collection of virtual real properties with known features and simulated prices, constituting a reflection of market processes which may take place in the near future. Comparison between the simulated characteristic and actual transactions in turn allows the correctness of the description of reality by the model to be verified.