Matkovskyy, Roman (2012): Forecasting the Index of Financial Safety (IFS) of South Africa using neural networks.

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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 VectorAutoregressive Models. The results show that the NARX model applied to IFS of South Africa and trained by the LevenbergMarquardt algorithm may ensure a forecast of adequate quality with less computation expanses, compared to BVAR models with different priors.
Item Type:  MPRA Paper 

Original Title:  Forecasting the Index of Financial Safety (IFS) of South Africa using neural networks 
English Title:  Forecasting the Index of Financial Safety (IFS) of South Africa using neural networks 
Language:  English 
Keywords:  Index of Financial Safety (IFS); neural networks; nonlinear dynamic network (NDN); nonlinear autoregressive model with exogenous input (NARX); forecast 
Subjects:  C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C45  Neural Networks and Related Topics E  Macroeconomics and Monetary Economics > E4  Money and Interest Rates > E44  Financial Markets and the Macroeconomy G  Financial Economics > G0  General > G01  Financial Crises 
Item ID:  42153 
Depositing User:  Roman Matkovskyy 
Date Deposited:  23 Oct 2012 19:22 
Last Modified:  28 Sep 2019 04:53 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/42153 