This simulation shows the relation ship between the number of houses for sale (Supply), the amount of people searching for home (Demand) and how these factors affect the prices within the real estate market, with the purpose of forecasting when the best time to buy and sell property is. It is assumed in this model that the number of houses are a constant, as we are looking at existing housing infrastructure rather than an emerging market or apartment buildings.
This model spans over 20 years, showing the long-term flow of the real estate market within this time frame. Price is a linear function of the number of houses for sale (positive) and also a liner function of the number of people searching for homes (negative).
Demand Elasticity Of price, Price Elasticity of Demand, Price elasticity of Supply, Supply Elasticity of Price and Interest rates can all be adjusted through the use of the sliders to create different scenarios with supply, demand and interest rates. The sales variable passes information into both the buying and sold variables upon completion of a relevant transaction.
While demand is low, the price is typically low too, however the supply of houses is high. While the demand is high the price is driven up and the supply of houses is lower than the demand.
