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

  • Matkovskyy, Roman

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.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 42153.

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Date of creation: Aug 2012
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Handle: RePEc:pra:mprapa:42153
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  1. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer, vol. 23(3), pages 187-200, September.
  2. Matkovskyy, Roman, 2012. "The Index of the Financial Safety (IFS) of South Africa and Bayesian Estimates for IFS Vector-Autoregressive Model," MPRA Paper 42173, University Library of Munich, Germany.
  3. Abdul Abiad, 2003. "Early Warning Systems: A Survey and a Regime-Switching Approach," IMF Working Papers 03/32, International Monetary Fund.
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