Real Estate Forecasting – An evaluation of forecasts

Sammanfattning: This degree project aims to explore the subject of forecasting, which is an ongoing and much alive debate within economics and finance. Within the forecasting field the available research is vast and even if restricted to real estate, which is the main focus of this paper, the available material is comprehensive. A large fraction of published research concerning the subject of real estate forecasting consists of post mortem studies, with econometric models trying to replicate historical trends with the help of available micro and macro data. This branch within the field of forecasting seems to advance and progress with help of refined econometric models. This paper, on the other hand, rather examines the fundamentals behind forecasting and why forecasting can be a difficult task in general. This is shown with an examination of the accuracy of 160 unique forecasts within the field of real estate. To evaluate the accuracy and predictability from different perspectives we state three main null hypotheses: 1. Correct forecasts and the direction of the predictions are independent variables. 2. Correct forecasts and the examined consultants are independent variables. 3. Correct forecasts and the examined cities are independent variables. 4 The observed frequencies for Hypothesis 1 indicate that upward predictions seem to be easier to predict than downward predictions. This is however not supported by the statistical tests. The observed frequencies for Hypothesis 2 clearly indicate that one consultant is a superior forecaster than compared to the other consultants. The statistical tests confirm this. The observed frequencies for Hypothesis 3 indicate no signs of dependence for the variables. The statistical tests confirm this.