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Macroeconomic Surprises and Stock Returns in South Africa

  • Rangan Gupta

    ()

    (Department of Economics, University of Pretoria)

  • Monique Reid

    ()

    (Department of Economics, Stellenbosch University)

The objective of this paper is to explore the sensitivity of industry-specific stock returns to monetary policy and macroeconomic news. The paper looks at a range of industry-specific South African stock market indices and evaluates the sensitivity of these indices to a various unanticipated macroeconomic shocks. We begin with an event study, which examines the immediate impact of macroeconomic shocks on the stock market indices, and then use a Bayesian Vector Autoregressive (BVAR) analysis, which provides insight into the dynamic effects of the shocks on the stock market indices, by allowing us to treat the shocks as exogenous through appropriate setting of priors defining the mean and variance of the parameters in the VAR. The results from the event study indicate that with the exception of the gold mining index, where the CPI surprise plays a significant role, monetary surprise is the only variable that consistently negatively affects the stock returns significantly, both at the aggregate and sectoral levels. The BVAR model based on monthly data however, indicates that, in addition to the monetary policy surprises, the CPI and PPI surprises also affect aggregate stock returns significantly. However, the effects of the CPI and PPI surprises are quite small in magnitude and are mainly experienced at shorter horizons immediately after the shock.

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Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 201212.

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Length: 27 pages
Date of creation: Apr 2012
Date of revision:
Handle: RePEc:pre:wpaper:201212
Contact details of provider: Postal: PRETORIA, 0002
Phone: (+2712) 420 2413
Fax: (+2712) 362-5207
Web page: http://www.up.ac.za/economics

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  1. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
  2. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
  3. Clive Coetzee, 2002. "Monetary Conditions and Stock Returns: A South African Case Study," Finance 0205002, EconWPA.
  4. Rangan Gupta & Alain Kabundi, 2008. "A Dynamic Factor Model for Forecasting Macroeconomic Variables in South Africa," Working Papers 200815, University of Pretoria, Department of Economics.
  5. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
  6. Monique Reid, 2009. "The Sensitivity of South African Inflation Expectations to Surprises," Working Papers 131, Economic Research Southern Africa.
  7. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  8. Gupta, Rangan & Kabundi, Alain, 2011. "Forecasting Macroeconomic Variables Using Large Datasets: Dynamic Factor Model versus Large-Scale BVARs," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 46(1), pages 23-40.
  9. Z. Chinzara, 2010. "Macroeconomic uncertainty and emerging market stock market volatility: The case for South Africa," Working Papers 187, Economic Research Southern Africa.
  10. Refet S. Gürkaynak & Brian Sack & Eric Swanson, 2005. "The Sensitivity of Long-Term Interest Rates to Economic News: Evidence and Implications for Macroeconomic Models," American Economic Review, American Economic Association, vol. 95(1), pages 425-436, March.
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