Predicting Instability

Weshah Razzak

MPRA Paper from University Library of Munich, Germany

Abstract: Unanticipated shocks could lead to instability, which is reflected in statistically significant changes in distributions of random variables. Changes in the conditional moments of stationary variables are predictable. We provide a framework based on a statistic for the Sample Generalized Variance, which is useful for interrogating real time data and to predicting statistically significant sudden and large shifts in the conditional variance of a vector of correlated macroeconomic and financial variables. It is a test for a market-wide instability. Central banks can incorporate the framework in the policymaking process.

Keywords: Generalized Variance; Conditional Variance (search for similar items in EconPapers)
JEL-codes: C16 E32 E44 (search for similar items in EconPapers)
Date: 2012-11-07
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Related works:
Working Paper: Predicting Instability (2010)
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