In this paper, we compare the out-of-sample forecasting ability of three ARIMA family models: ARIMA, ARIMAX, and ARIMAX-GARCH. The models are tested to forecast turning points and trends in the Canadian real estate index using monthly data from April 2002 to March 2011. The results indicate that...

This paper examines whether machine learning (ML) algorithms can outperform a linear model in predicting monthly growth in Canada of both house prices and existing home sales. The aim is to apply two widely used ML techniques (support vector regression and multilayer perceptron) in economic...

This paper examines the predictive power of five linear hedonic pricing models for the residential market with varying complexity in their spatial and temporal structure. In contrast to similar studies, we extend the out-of-sample forecast evaluation to one-day-ahead predictions with a rolling...

Many studies documented that actual asset-price movements exhibit momentum and reversion to fundamentals. We study real estate markets and find that households' subjective house-price expectations capture momentum but not reversion to fundamentals. Moreover, if current house prices are deviated...

Problem: How to help practitioners, academics, and decision makers use experimental research findings to substantially reduce forecast errors for all types of forecasting problems. Methods: Findings from our review of forecasting experiments were used to identify methods and principles that lead...

We employ forty-seven different algorithms to forecast Australian log real house prices and growth rates, and compare their ability to produce accurate out-of-sample predictions. The algorithms, which are specified in both single- and multi-equation frameworks, consist of traditional time-series...

This paper presents a simple rational expectations model of intertemporal asset pricing. It shows that heterogeneous risk aversion of investors is likely to generate declining aggregate relative risk aversion. This leads to predictability of asset returns and high and persistent volatility....

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We...

This paper argues that Blomberg and Hess's (Journal of International Economics 1997) finding that political variables can be used to predict exchange rate movements better than the random walk model must be seen in the context of the decade and half of previous research which failed to beat this...