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Predicting South African Equity Premium using Domestic and Global Economic Policy Uncertainty Indices: Evidence from a Bayesian Graphical Model

Author

Listed:
  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Turkey and Department of Economics, University of Pretoria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Mampho P. Modise

    (Department of Economics, University of Pretoria)

  • John W. Muteba Mwamba

    (Department of Economics and Econometrics, University of Johannesburg)

Abstract

This paper analyses whether we can predict South African excess stock returns based on a measure of economic policy uncertainty (EPU) of South Africa and twenty other developed and emerging markets. In this regard, we use a Bayesian graphical model estimated over the sample period of 1998:01-2012:12. The model is also estimated in a rolling-window fashion over the monthly sample period of 2003:01-2012:03, using an initial sample period of 1998:01-2002:12. The Bayesian shrinkage approach allows us to simultaneously model the 21 EPUs, over and above 22 other standard financial and macroeconomic predictors. In addition, the Bayesian graphical model also provides both instantaneous and lagged relationships between the predictors and the equity premium. Our full sample results show that, in terms of instantaneous relationship, none of the EPUs play any role, and for the lagged relationship, only the EPU of Hong Kong and the Netherlands can be considered as important with posterior inclusion probabilities in excess of 0.50. Rolling estimates show that instantaneous relationships are quite constant and do not indicate any significant links from EPUs to the equity premium. On the other hand, rolling estimates are highly time-varying, and there is significant lagged impact from most of the EPUs in various sub-periods.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Mampho P. Modise & John W. Muteba Mwamba, 2015. "Predicting South African Equity Premium using Domestic and Global Economic Policy Uncertainty Indices: Evidence from a Bayesian Graphical Model," Working Papers 201596, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201596
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    Citations

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    Cited by:

    1. Apergis, Nicholas & Gupta, Rangan, 2017. "Can (unusual) weather conditions in New York predict South African stock returns?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 377-386.
    2. Christou, Christina & Gupta, Rangan, 2020. "Forecasting equity premium in a panel of OECD countries: The role of economic policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 243-248.
    3. Elie Bouri & Rangan Gupta & Seyedmehdi Hosseini & Chi Keung Marco Lau, 2017. "Does Global Fear Predict Fear in BRICS Stock Markets? Evidence from a Bayesian Graphical VAR Model," Working Papers 201704, University of Pretoria, Department of Economics.
    4. Nicholas Apergis & Rangan Gupta, 2016. "Can Weather Conditions in New York Predict South African Stock Returns?," Working Papers 201634, University of Pretoria, Department of Economics.

    More about this item

    Keywords

    Economic Policy Uncertainty; Stock Prices; Prediction; Bayesian Graphical Models; Vector Autoregression; South Africa;
    All these keywords.

    JEL classification:

    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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