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 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.
Item Type: | MPRA Paper |
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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.uni-muenchen.de/id/eprint/42153 |