Nonlinear difference equation forecasting engine for FOREX markets.
In this study, we aim to find stable models that can be used to model the exchange rate time series using non-linear difference equations. Because the FOREX market is a dynamical system, we can expect the exchange rate to switch from model to model. Therefore, we can develop a forecasting engine that...
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sg-ntu-dr.10356-495052023-02-28T23:53:40Z Nonlinear difference equation forecasting engine for FOREX markets. Tan, James Peng Lung. Cheong Siew Ann School of Physical and Mathematical Sciences DRNTU::Business::Finance::Foreign exchange DRNTU::Science::Mathematics::Applied mathematics::Complex systems In this study, we aim to find stable models that can be used to model the exchange rate time series using non-linear difference equations. Because the FOREX market is a dynamical system, we can expect the exchange rate to switch from model to model. Therefore, we can develop a forecasting engine that can switch between the best fitting models to obtain reliable forecasts of the exchange rate. To do this, we first overfitted the model to capture as many relevant parameters as possible and then through sensitivity analysis, filtered out the least relevant parameters. Then we tracked the relevant parameters through time to determine their stable values for use in a forecasting engine. However, the parameters were found to vary too wildly and did not remain stable at all. We then found that a change in interest rate produced a deviation from the normal behavior of the model. Forecasts using a simpler non-linear difference equation with the more sensitive parameters were then carried out. Doctor of Philosophy (SPMS) 2012-05-21T04:20:52Z 2012-05-21T04:20:52Z 2012 2012 Thesis http://hdl.handle.net/10356/49505 en 63 p. application/pdf |
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DRNTU::Business::Finance::Foreign exchange DRNTU::Science::Mathematics::Applied mathematics::Complex systems Tan, James Peng Lung. Nonlinear difference equation forecasting engine for FOREX markets. |
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In this study, we aim to find stable models that can be used to model the exchange rate time series using non-linear difference equations. Because the FOREX market is a dynamical system, we can expect the exchange rate to switch from model to model. Therefore, we can develop a forecasting engine that can switch between the best fitting models to obtain reliable forecasts of the exchange rate. To do this, we first overfitted the model to capture as many relevant parameters as possible and then through sensitivity analysis, filtered out the least relevant parameters. Then we tracked the relevant parameters through time to determine their stable values for use in a forecasting engine. However, the parameters were found to vary too wildly and did not remain stable at all. We then found that a change in interest rate produced a deviation from the normal behavior of the model. Forecasts using a simpler non-linear difference equation with the more sensitive parameters were then carried out. |
author2 |
Cheong Siew Ann |
author_facet |
Cheong Siew Ann Tan, James Peng Lung. |
format |
Theses and Dissertations |
author |
Tan, James Peng Lung. |
author_sort |
Tan, James Peng Lung. |
title |
Nonlinear difference equation forecasting engine for FOREX markets. |
title_short |
Nonlinear difference equation forecasting engine for FOREX markets. |
title_full |
Nonlinear difference equation forecasting engine for FOREX markets. |
title_fullStr |
Nonlinear difference equation forecasting engine for FOREX markets. |
title_full_unstemmed |
Nonlinear difference equation forecasting engine for FOREX markets. |
title_sort |
nonlinear difference equation forecasting engine for forex markets. |
publishDate |
2012 |
url |
http://hdl.handle.net/10356/49505 |
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1759857080677695488 |