  In this research paper, I have performed time series analysis and forecasted
the monthly value of housing starts for the year 2019 using several econometric
methods - ARIMA(X), VARX, (G)ARCH and machine learning algorithms - artificial
neural networks, ridge regression, K-Nearest Neighbors, and support vector
regression, and created an ensemble model. The ensemble model stacks the
predictions from various individual models, and gives a weighted average of all
predictions. The analyses suggest that the ensemble model has performed the
best among all the models as the prediction errors are the lowest, while the
econometric models have higher error rates.
