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

Mehmet Balcilar, Rangan Gupta, Mampho Modise () and John Weirstrass Muteba Mwamba
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Mampho Modise: Department of Economics, University of Pretoria

No 201596, Working Papers from University of Pretoria, Department of Economics

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.

Keywords: Economic Policy Uncertainty; Stock Prices; Prediction; Bayesian Graphical Models; Vector Autoregression; South Africa (search for similar items in EconPapers)
JEL-codes: C32 C53 E60 G12 G17 (search for similar items in EconPapers)
Pages: 20pages
Date: 2015-12
New Economics Papers: this item is included in nep-for and nep-mac
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