This paper develops a financial stress measure for the United States, the Cleveland Financial Stress Index (CFSI). The index is based on publicly available data describing a six-market partition of the financial system comprising credit, funding, real estate, securitization, foreign exchange, and equity markets. This paper improves upon existing stress measures by objectively selecting between several index weighting methodologies across a variety of monitoring frequencies through comparison against a volatility-based benchmark series. The resulting measure facilitates the decomposition of stress to identify disruptions in specific markets and provides insight into historical stress regimes.

Timely identifi cation of coincident systemic conditions and forward-looking capacity to anticipate adverse developments are critical for macroprudential policy. Despite clear recognition of these factors in literature, an evaluation methodology and empirical tests for the information value of coincident measures are lacking. This paper provides a twofold contribution to the literature: (i) a general-purpose evaluation framework for assessing information value for measures of systemic conditions, and (ii) an empirical assessment of the information value for several alternative measures of US systemic conditions. We fi nd substantial differences among the measures, of which the Cleveland Financial Stress Index shows best-in-class identifi cation performance. In terms of forecasting performance, Kamakura's Troubled Company Index, Cleveland Financial Stress Index, and Goldman Sachs Financial Conditions Index show moderately stable usefulness metrics over time.

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The Artronix 1,100 head scanner is a promising unit which allows reconstitution of the images in coronal and sagittal planes from the axial slice. The clinical usefulness of coronal and sagittal images thus obtained is illustrated and discussed.

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