Abstract
This paper examines persistence in price movements and predictability of the US housing market both on a local level across 20 cities in the US and on a nationwide level. We use a time series approach instead of often applied multivariate approaches to exclude potential biases across local markets and provide trading strategies to compare predictability across markets and to test whether or not the detected persistence can be exploited by investors to earn excess returns. The results from the monthly and quarterly transaction-based S&P/Case-Shiller house price indices from 1987 to 2009 provide empirical evidence on strong persistence. This is confirmed by both parametric and non-parametric tests for nominal and real house prices based on expected inflation. Furthermore, the empirical findings suggest that investors might be able to obtain excess returns from both autocorrelation-based and moving average-based trading strategies compared to a buy-and-hold strategy, although the results depend on the transaction costs individual investors face.
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