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Volatility relationship between stock performance and real output

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Author Info

  • Eun Ahn
  • Jin Man Lee

Abstract

This paper investigates the interaction between stock index returns and the real output growth for five countries. This study focuses on the second moment relationship using various forms of the bivariate generalized autoregressive conditional heteroscedastic models (BGARCH). This study shows that interactivity between stock returns and growth rates are robust at the second order. The results imply that high volatility in the stock market is likely to be followed by increased volatility in the output sector and periods of high volatility in real output is likely to be followed by increased volatility in the stock market.

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File URL: http://www.tandfonline.com/doi/abs/10.1080/09603100500424775
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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

Volume (Year): 16 (2006)
Issue (Month): 11 ()
Pages: 777-784

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Handle: RePEc:taf:apfiec:v:16:y:2006:i:11:p:777-784

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References

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  1. Hassapis, Christis & Kalyvitis, Sarantis, 2002. "Investigating the links between growth and real stock price changes with empirical evidence from the G-7 economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(3), pages 543-575.
  2. Summers, Lawrence H, 1986. " Does the Stock Market Rationally Reflect Fundamental Values?," Journal of Finance, American Finance Association, vol. 41(3), pages 591-601, July.
  3. Fabio Fornari & Antonio Mele, 1997. "Asymmetries and non-linearities in economic activity," Applied Financial Economics, Taylor & Francis Journals, vol. 7(2), pages 203-206.
  4. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
  5. Connolly, Robert A., 1989. "An Examination of the Robustness of the Weekend Effect," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(02), pages 133-169, June.
  6. Adrian R. Pagan & G. William Schwert, 1990. "Alternative Models For Conditional Stock Volatility," NBER Working Papers 2955, National Bureau of Economic Research, Inc.
  7. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-31, February.
  8. Nicole Davis & Ali Kutan, 2003. "Inflation and output as predictors of stock returns and volatility: international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 13(9), pages 693-700.
  9. Eva Liljeblom & Marianne Stenius, 1997. "Macroeconomic volatility and stock market volatility: empirical evidence on Finnish data," Applied Financial Economics, Taylor & Francis Journals, vol. 7(4), pages 419-426.
  10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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Cited by:
  1. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2013. "Forecasting US growth during the Great Recession: Is the financial volatility the missing ingredient?," EconomiX Working Papers 2013-19, University of Paris West - Nanterre la Défense, EconomiX.
  2. Charles K.D. Adjasi, 2009. "Macroeconomic uncertainty and conditional stock-price volatility in frontier African markets: Evidence from Ghana," Journal of Risk Finance, Emerald Group Publishing, vol. 10(4), pages 333-349, August.
  3. Ferrara, Laurent & Marsilli, Clément & Ortega, Juan-Pablo, 2014. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Economic Modelling, Elsevier, vol. 36(C), pages 44-50.
  4. Karunanayake, Indika & Valadkhani, Abbas & O’Brien, Martin, 2012. "GDP Growth and the Interdependency of Volatility Spillovers," MPRA Paper 50398, University Library of Munich, Germany.

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