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Stock market returns and economic activity: evidence from wavelet analysis

  • Marco Gallegati

    (Department of Economics, Università Politecnica delle Marche)

In this paper we investigate the relationship between stock market returns and economic activity by using signal decomposition techniques based on wavelet analysis. In particular, we apply the maximum overlap discrete wavelet transform (MODWT) to the DJIA stock price index and the industrial production index for US over the period 1961:1- 2005:3 and using the definitions of wavelet variance, wavelet correlation and cross-correlations analyze the association as well as the lead/lag relationship between stock prices and industrial production at the different time scales. Our results show that stock market returns tends to lead the level of economic activity but only at the highest scales (lowest frequencies), corresponding to periods of 16 months and longer, and that the periods by which stock returns lead output increase as the wavelet time scale increases.

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Paper provided by EconWPA in its series Macroeconomics with number 0512016.

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Length: 12 pages
Date of creation: 27 Dec 2005
Date of revision:
Handle: RePEc:wpa:wuwpma:0512016
Note: Type of Document - pdf; pages: 12
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  1. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Working Papers 02-3, Bank of Canada.
  2. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Scaling properties of foreign exchange volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 249-266.
  3. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
  4. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
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