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The purpose of this paper is to analyze the differences between the actual mortgage prompt and late payments and their respective expected measures from 2004 to 2010 to spot early symptoms of housing crisis.

This paper explores these discrepancies across the entire US market and along various delinquency lengths of 30, 60 and 90 days. This paper constructs a Bayesian forecasting model that relies on prior distributional properties of diverse time horizons.

Abnormal mortgage delinquency rates are identified in real time and can be served as early symptoms for housing crisis.

The statistical scheme proposed in this paper can function as a valuable predictive tool for lending institutions, bank audit companies, regulatory bodies and real estate professional investors who examine changes in economic settings and trends in short sale leads.

The abnormal mortgage delinquencies can serve as indicators of changes in economic fundamentals and early signs of a mounting housing crisis.

This paper presents a unique statistical technique in the context of mortgage delinquencies.