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Identification and critical time forecasting of real estate bubbles in the USA

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  • Diego Ardila
  • Dorsa Sanadgol
  • Peter Cauwels
  • Didier Sornette

Abstract

We present a hybrid model for diagnosis and critical time forecasting of real estate bubbles. The model combines two elements: (1) the Log Periodic Power Law Singular model to describe endogenous price dynamics originated from positive feedback loops among economic agents; and (2) a diffusion index that creates a parsimonious representation of multiple macroeconomic variables. We explicitly compare the in-sample and out-sample behaviour of our model on the housing price indices of 380 US metropolitan areas. Empirical results suggest that the model is able to forecast the end of the bubbles and to identify the variables that are highly relevant during the bubble regime.

Suggested Citation

  • Diego Ardila & Dorsa Sanadgol & Peter Cauwels & Didier Sornette, 2017. "Identification and critical time forecasting of real estate bubbles in the USA," Quantitative Finance, Taylor & Francis Journals, vol. 17(4), pages 613-631, April.
    • Handle: RePEc:taf:quantf:v:17:y:2017:i:4:p:613-631
    DOI: 10.1080/14697688.2016.1207796
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