- Built loss function to evaluate various potential situations. - Removed exponential trend in the data and analyzed autocorrelation and partial autocorrelation. - Performed Augmented Dickey-Fuller test on three key variables to check for stationarity. - Tested for exogenity between variables using Granger Causality Wald test. - Created Univariate and multivariate forecasts using Vector Autoregression and Autoregressive-moving-average models. - Selected the best forecasting model as the one with the minimum loss. - Used Diebold-Mariano test to determine the statistical superiority of said forecast.

Predicting tomorrow’s house prices with today’s data