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Macroeconomic Surprises and Stock Returns in South Africa

Author

Listed:
  • Rangan Gupta

    () (Department of Economics, University of Pretoria)

  • Monique Reid

    () (Department of Economics, University of Stellenbosch)

Abstract

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.

Suggested Citation

  • Rangan Gupta & Monique Reid, 2012. "Macroeconomic Surprises and Stock Returns in South Africa," Working Papers 05/2012, Stellenbosch University, Department of Economics.
  • Handle: RePEc:sza:wpaper:wpapers157
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    References listed on IDEAS

    as
    1. 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.
    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. 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.
    4. 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.
    5. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    6. Z. Chinzara, 2010. "Macroeconomic uncertainty and emerging market stock market volatility: The case for South Africa," Working Papers 187, Economic Research Southern Africa.
    7. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    8. Monique Reid, 2009. "The Sensitivity Of South African Inflation Expectations To Surprises," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 414-429, September.
    9. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    10. Bonga-Bonga, Lumengo & Kabundi, Alain, 2015. "Monetary Policy Instrument and Inflation in South Africa: Structural Vector Error Correction Model Approach," MPRA Paper 63731, University Library of Munich, Germany.
    11. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    12. Clive Coetzee, 2002. "Monetary Conditions and Stock Returns: A South African Case Study," Finance 0205002, EconWPA.
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    Citations

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    Cited by:

    1. Beatrice D. Simo - Kengne & Mehmet Balcilar & Rangan Gupta & Monique Reid & Goodness C. Aye, 2012. "Is the relationship between monetary policy and house prices asymmetric in South Africa? Evidence from a Markov-Switching Vector Autoregressive mode," Working Papers 15-26, Eastern Mediterranean University, Department of Economics.
    2. Nasha Maveé & Roberto Perrelli & Axel Schimmelpfennig, 2016. "Surprise, Surprise; What Drives the Rand / U.S. Dollar Exchange Rate Volatility?," IMF Working Papers 16/205, International Monetary Fund.
    3. Sonali Das & Rangan Gupta & Patrick Kanda & Monique Reid & Christian Tipoy & Mulatu Zerihun, 2014. "Real interest rate persistence in South Africa: evidence and implications," Economic Change and Restructuring, Springer, vol. 47(1), pages 41-62, February.
    4. Pooja Joshi & A K Giri, 2015. "Dynamic Relations between Macroeconomic Variables and Indian Stock Price: An Application of ARDL Bounds Testing Approach," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 5(10), pages 1119-1133, October.
    5. Esin Cakan & Rangan Gupta, 2016. "Does U.S. Macroeconomic News Make the South African Stock Market Riskier?," Working Papers 201646, University of Pretoria, Department of Economics.

    More about this item

    Keywords

    Bayesian Vector Autoregressive Model; Event Study; Macroeconomic Surprises; Stock Returns.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G1 - Financial Economics - - General Financial Markets

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