Method of virtual increase in the sample when predicting rare sales in conditions of information asymmetry

The work is aimed at solving the actual problem of forecasting rare sales in a changing competitive environment and the intentions of buyers. The proposed approach is based on the method of virtual sample increase in order to build more accurate probabilistic statements about socio-economic indicators on the example of the car market. The model of selection of the optimal offer price depending on the number of competitive offers on the basis of simulation by the Monte Carlo method is considered. The tools of modeling changes in the competitive environment, as well as the intentions of buyers, generating information asymmetry in the market. The constructed model allows us to study the pricing mechanism, to optimize the cost of the proposed product, as well as to forecast the demand and sales volumes with a different number of competitive offers and intentions of buyers. With the help of the presented methods of simulation studied the dependence of sales volumes on the value of the goods, as well as the intentions of buyers and the number of competitive offers, the results of modeling, on the basis of which are built probabilistic statements regarding profit and loss, as well as sales volumes of cars of different models and brands.