Brown’s Weighted Exponential Moving Average Implementation in Forex Forecasting
Abstract: 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.
Keywords: Brown’s double
exponential smoothing, B-WEMA, exponential moving average, foreign exchange,
time series forecasting, weighted moving average
Author: Seng Hansun, Subanar
Journal Code: jptkomputergg170180
