In stocks market, investors need a forecasting method which has high accuracy for predicting stock prices. In this study, the conventional forecasting method of Double Exponential Smoothing Holt will be compared with the modern forecasting method, namely the Fuzzy Time Series method. The Fuzzy Time Series forecasting method used in this study is the Cheng model, which used linguistic interval partition and adaptive forecast equation. Through this forecast analysis and calculation on PT Bank Central Asia Tbk’s stock price, Fuzzy Time Series forecast method has higher accuracy than Double Exponential Smoothing Holt, so Fuzzy Time Series is the best method for predicting PT Bank Central Asia Tbk’s stock prices.
Comparison of Double Exponential Smoothing Holt and Fuzzy Time Series Methods in Forecasting Stock Prices (Case Study: PT Bank Central Asia Tbk)
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