FORECASTING THE RAND-DOLLAR AND RAND-POUND EXCHANGE RATES USING DYNAMIC MODEL AVERAGING

Riane de Bruyn (), Rangan Gupta and Renee van Eyden ()
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Riane de Bruyn: Department of Economics, University of Pretoria

No 201307, Working Papers from University of Pretoria, Department of Economics

Abstract: Traditionally, the literature on forecasting exchange rates with many potential predictors have primarily only accounted for parameter uncertainty using Bayesian Model Averaging (BMA). Though BMA-based models of exchange rates tend to outperform the random walk model, we show that when accounting for model uncertainty over and above parameter uncertainty through the use of Dynamic model Averaging (DMA), the gains relative to the random walk model are even bigger. That is, DMA models outperform not only the random walk model, but also the BMA model of exchange rates. We obtain these results based on fifteen potential predictors used to forecast two South African Rand-based exchange rates. In the process, we also unveil variables, which tends to vary over time, that are good predictors of the Rand-Dollar and Rand-Pound exchange rates at different forecasting horizons.

Keywords: Bayesian; state space models; exchange rates; macroeconomic fundamentals; forecasting (search for similar items in EconPapers)
JEL-codes: C11 C53 F37 F47 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2013-01
New Economics Papers: this item is included in nep-afr, nep-for and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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