Prediktion av bostadsrättspriser i Stockholms innerstad.
A frequently asked question in real estate marketing is at what time of the year it is optimal to invest or sell. The aim of the project was to answer this question and to generate a prediction model over real estate located in the centre of Stockholm that takes seasons into account. With acquired sales statistics in Stockholm between 2010 and 2013 it was possible to perform a linear least square regression, also known as Ordinary Least Square (OLS), with describing qualities and season of sale as parameters. Statistical problems such as Multicollinearity and Heteroskedasticity have been taken into account when deriving the model. The result was a highly accurate prediction model indicating the profitability of investing in real estate during the summer and selling during the autumn.