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What does financial volatility tell us about macroeconomic fluctuations?

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  • Marcelle Chauvet
  • Zeynep Senyuz
  • Emre Yoldas

Abstract

This paper provides an extensive analysis of the predictive ability of financial volatility measures for economic activity. We construct monthly measures of stock and bond market volatility from daily returns and model volatility as composed of a long-run component that is common across all series, and a set of idiosyncratic short-run components. Based on powerful in-sample predictive ability tests, we find that the stock volatility measures and the common factor significantly improve short-term forecasts of conventional financial indicators. A real-time out of sample assessment yields a similar conclusion under the assumption of noisy revisions in macroeconomic data. In a non-linear extension of the dynamic factor model for volatility series, we identify three regimes that describe the joint volatility dynamics: low, intermediate and high-volatility. We also find that the non-linear model performs remarkably well in tracking the Great Recession of 2007-2009 in real-time.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2013-61.

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Date of creation: 2013
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Handle: RePEc:fip:fedgfe:2013-61

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Cited by:
  1. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2010. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," CREATES Research Papers 2010-58, School of Economics and Management, University of Aarhus.
  2. Ferrara, L. & Marsilli, C. & Ortega, J-P., 2013. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Working papers 454, Banque de France.

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