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Title: Nonlinear difference equation forecasting engine for FOREX markets.
Authors: Tan, James Peng Lung.
Keywords: DRNTU::Business::Finance::Foreign exchange
DRNTU::Science::Mathematics::Applied mathematics::Complex systems
Issue Date: 2012
Abstract: 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.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Theses

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