Comparison of Fuzzy Time Series and ARIMA Model for Predicting Stock Prices

The stock market has always been a contentious topic in society, and it is place where economic standards are established. incredibly unpredictable turbulent. This means that the shares may fluctuate for reasons sometimes difficult to understand. Due this uncertainty, many investors believe as risky investment. Therefore, having an accurate picture of future environment crucial minimising losses. Forecasting technique predicting based on outcome previous data. There wide range forecasting algorithms, however, study only focuses these two techniques: Auto Regressive Moving Average (ARIMA) model Fuzzy Time Series (FTS) Model. goal evaluate compare effectiveness ARIMA FTS sample data prices Top Glove Corporation Berhad since company largest glove supplier world plays significant role Covid-19 global pandemic crisis. error measures were taken into consideration consist Root Mean Square Error (RMSE), (MSE), Absolute Percentage (MAPE). These measurements computed numerically graphically using statistical programme called EViews. shows performs better than terms accuracy provides lowest values MAPE, MSE, RMSE, which 10.58757, 0.926354, 0.962473, respectively.