This article provides the in-sample estimation and evaluates the out-of-sample conditional mean and volatility forecast performance of the conventional Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) and...

This paper follows the recent literature on real estate price prediction and proposes to take advantage of machine learning techniques to better explain which variables are more important in describing the real estate market evolution. We apply the random forest algorithm on London real estate...

Housing markets display several correlations to multiple economic sectors of an economy. Their enormous impact on economies’ health, wealth, and stability is uncontroversial. Interestingly, the forms of financing residential property vary widely between the different countries in terms of...

This chapter reviews the evidence of predictability in US residential and commercial real estate markets. First, we highlight the main methodologies used in the construction of real estate indices, their underlying assumptions and their impact on the stochastic properties of the resultant...

I create a time series of weekly ratios of Google searches, in the US, on buying and selling in the Real Estate Category of Google Trends. I call this ratio the Google US Housing Market BUSE Index or simply the BUSE index. It expresses the number of "buy"-searches for each "sell"-search which,...

We analyze the impacts of alternative submarket definitions when predicting house prices in a mass appraisal context, using both ordinary least squares (OLS) and geostatistical techniques. For this purpose, we use over 13,000 housing transactions for Louisville, Kentucky. We use districts...

On the 22nd of February 2011, much of the residential housing stock in the city of Christchurch, New Zealand, was damaged by an unusually destructive earthquake. Almost all of the houses were insured. We ask whether insurance was able to mitigate the damage adequately, or whether the damage from...

The 2006 sudden and immense downturn in U.S. House Prices sparked the 2007 global financial crisis and revived the interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting methodology that combines the Ensemble Empirical Mode...

We introduce a novel quantitative methodology to detect real estate bubbles and forecast their critical end time, which we apply to the housing markets of China's major cities. Building on the Log-Periodic Power Law Singular (LPPLS) model of self-reinforcing feedback loops, we use the quantile...

This paper documents that the housing cycle, measured by the residential investment share, is a strong in-sample and out-of-sample predictor for the dollar up to twelve quarters. Housing construction is negatively associated with risk premia in equity and bonds, but positively with foreign...