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FX forecasting using B-WEMA: Variant of Brown's Double Exponential Smoothing

Hansun, Seng (2016) FX forecasting using B-WEMA: Variant of Brown's Double Exponential Smoothing. 2016 International Conference on Informatics and Computing (ICIC).

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Official URL: https://ieeexplore.ieee.org/abstract/document/7905...

Abstract

A new variant of B-DES (Brown's Double Exponential Smoothing), as a type of classical MA (Moving Averages) method commonly used in time series data forecasting, had been introduced and known as B-WEMA. It has proven to have a better accuracy and robustness level compare to the other moving average methods, such as WMA and B-DES. However, B-WEMA implementation on a real financial time series data such as foreign exchange (FX) had never been done. Therefore, in this research we try to implement B-WEMA as a variant of MA method on FX forecasting and compare the results with other moving average methods using the MSE and MAPE forecast error measurements criteria. Results from the experiments conducted show that B-WEMA has a better accuracy level compared to WMA and B-DES methods.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods (Artificial Intelligence, Machine Learning, 3D Graphics, Digital Video, Data Mining, Augmented Reality)
300 Social Sciences > 330 Economics > 332 Financial Economics (Shares, Investment)
500 Science and Mathematic > 510 Mathematics > 519 Probabilities and Applied Mathematics
Divisions: Fakultas Teknik Informatika > Program Studi Informatika
Depositing User: mr admin umn
Date Deposited: 19 Oct 2021 04:55
Last Modified: 19 Oct 2021 04:56
URI: http://kc.umn.ac.id/id/eprint/18860

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