UMN Knowledge Center

Brown's Weighted Exponential Moving Average Implementation in Forex Forecasting

Hansun, Seng and Subanar, Subanar (2017) Brown's Weighted Exponential Moving Average Implementation in Forex Forecasting. TELKOMNIKA Telecommunication, Computing, Electronics and Control, 15 (3). ISSN 1693-6930

Full text not available from this repository.
Official URL:


In 2016, a time series forecasting technique which combined the weighting factor calculation formula found in weighted moving average with Brown's double exponential smoothing procedures had been introduced. The technique is known as Brown's weighted exponential moving average (B-WEMA), as a new variant of double exponential smoothing method which does the exponential filter processes twice. In this research, we will try to implement the new method to forecast some foreign exchange, or known as forex data, including EUR/USD, AUD/USD, GBP/USD, USD/JPY and EUR/JPY data. The time series data forecasting results using B-WEMA then be compared with other conventional and hybrid moving average methods, such as weighted moving average (WMA), exponential moving average (EMA) and Brown's double exponential smoothing (B-DES). The comparison results show that B-WEMA has a better accuracy level than other forecasting methods used in this research.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods (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 04:53
Last Modified: 19 Oct 2021 04:53

Actions (login required)

View Item View Item