Analysis and prediction of apartment prices in inner city Stockholm

Abstract: In this thesis, an attempt will be made to nd a model that predicts apartment prices in inner city Stockholm. Lately, apartment prices have steadily increased and it has become rather popular to invest money in apartments due to the high potential of value increase. Of course not all apartments will increase in value, and we hope to nd the factors that determine the value of an apartment that is about to be sold. To nd these factors, we will combine the approaches of regression and time series analysis, creating a linear regression model and a time series model, and then taking the mean of their predictions. Statistics of apartment sales during the time period of August 2012 to February 2014 will be used as data, and when nding the models explicitly, large data handling softwares such as SPSS, Excel and Matlab will be used. The thesis consists of an introduction to the general theory behind the two approaches, followed by our specic case. Lastly, an attempt will be made to draw some general conclusions from our ndings, and the accuracy of our model will be tested by predicting the selling price of a few apartments that have been or are about to be sold and comparing the predictions with the actual price.