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South African Stock Returns Predictability using Domestic and Global Economic Policy Uncertainty: Evidence from a Nonparametric Causality-in-Quantiles Approach

Author

Listed:
  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Famagusta, via Mersin 10, Northern Cyprus, Turkey and Department of Economics, University of Pretoria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Clement Kyei

    (Department of Economics, University of Pretoria)

Abstract

This paper analyses whether we can predict South African stock returns based on a measure of economic policy uncertainty (EPU) of South Africa and twenty other developed and emerging markets. While, linear Granger causality tests fail to find evidence of predictability, barring couple of cases, strong evidence of causality is detected from all the EPUs using a nonparametric causality-in-quantiles test. In addition, predictability is found to hold over the entire conditional distribution of stock returns, with the same being strongest around the median, i.e., when the stock market is in a normal mode. Given the existence of nonlinearity and regime changes in our data set, we consider the results from the nonparametric test as more robust relative to the standard causality test.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2015. "South African Stock Returns Predictability using Domestic and Global Economic Policy Uncertainty: Evidence from a Nonparametric Causality-in-Quantiles Approach," Working Papers 201570, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201570
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    Citations

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    Cited by:

    1. Balcilar, Mehmet & Roubaud, David & Uzuner, Gizem & Wohar, Mark E., 2021. "Housing sector and economic policy uncertainty: A GMM panel VAR approach," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 114-126.
    2. Balcilar, Mehmet & Usman, Ojonugwa & Gungor, Hasan & Roubaud, David & Wohar, Mark E., 2021. "Role of global, regional, and advanced market economic policy uncertainty on bond spreads in emerging markets," Economic Modelling, Elsevier, vol. 102(C).
    3. Fasanya, Ismail O. & Adekoya, Oluwasegun B. & Adetokunbo, Abiodun M., 2021. "On the connection between oil and global foreign exchange markets: The role of economic policy uncertainty," Resources Policy, Elsevier, vol. 72(C).
    4. Abid, Ilyes & Dhaoui, Abderrazak & Kaabia, Olfa & Tarchella, Salma, 2023. "Geopolitical risk on energy, agriculture, livestock, precious and industrial metals: New insights from a Markov Switching model," Resources Policy, Elsevier, vol. 85(PA).
    5. Serdar Ongan & Ismet Gocer, 2017. "Testing The Causalities Between Economic Policy Uncertainty And The Us Stock Indices: Applications Of Linear And Nonlinear Approaches," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(04), pages 1-20, December.
    6. Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
    7. Fasanya, Ismail O. & Oliyide, Johnson A. & Adekoya, Oluwasegun B. & Agbatogun, Taofeek, 2021. "How does economic policy uncertainty connect with the dynamic spillovers between precious metals and bitcoin markets?," Resources Policy, Elsevier, vol. 72(C).
    8. Nguyen, Dat Thanh & Phan, Dinh Hoang Bach & Anglingkusumo, Reza & Sasongko, Aryo, 2021. "US government shutdowns and Indonesian stock market," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    9. Fasanya, Ismail O. & Oyewole, Oluwatomisin & Dauda, Mariam, 2023. "Uncertainty due to infectious diseases and bitcoin-gold nexus: Evidence from a non-parametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 82(C).
    10. 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; Linear Causality; Nonparametric Quantile Causality; 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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