Forecasting the Index of Financial Safety (IFS) of South Africa using neural networks

Roman Matkovskyy

MPRA Paper from University Library of Munich, Germany

Abstract: This paper investigates neural network tools, especially the nonlinear autoregressive model with exogenous input (NARX), to forecast the future conditions of the Index of Financial Safety (IFS) of South Africa. Based on the time series that was used to construct the IFS for South Africa (Matkovskyy, 2012), the NARX model was built to forecast the future values of this index and the results are benchmarked against that of Bayesian Vector-Autoregressive Models. The results show that the NARX model applied to IFS of South Africa and trained by the Levenberg-Marquardt algorithm may ensure a forecast of adequate quality with less computation expanses, compared to BVAR models with different priors.

Keywords: Index of Financial Safety (IFS); neural networks; nonlinear dynamic network (NDN); nonlinear autoregressive model with exogenous input (NARX); forecast (search for similar items in EconPapers)
JEL-codes: C45 E44 G01 (search for similar items in EconPapers)
Date: 2012-08
New Economics Papers: this item is included in nep-afr, nep-cmp, nep-for and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:42153

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