A comparative study on WEMA and H-WEMA forecasting methods in time series analysis (case study: JKSE composite index data)

Moving average as one of popular technical indicator used to predict data in time series analysis has grown significantly. There are many researchers who have develop moving average methods resulting in its' many derivatives methods. Two of them are Weighted Exponential Moving Average (WEMA) and Holt's Weighted Exponential Moving Average (H-WEMA) methods. This research aims to conduct a comparative study on WEMA and H-WEMA methods which are said to excel the other conventional moving average methods. Therefore, we will implement both methods to predict Jakarta Stock Exchange (JKSE) composite index data and then calculate the accuracy and robustness level using Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) criteria. The results from the experiments taken show that H-WEMA has a better accuracy and robustness levels compared to other moving average methods.