3rd European International Conference on Industrial Engineering and Operations Management

Comparison of Double Exponential Smoothing Holt and Fuzzy Time Series Methods in Forecasting Stock Prices (Case Study: PT Bank Central Asia Tbk)

Eman Lesmana, Nursanti Anggiani, Sukono Sukono, Fatimah Fatimah & Abdul Talib Bon
Publisher: IEOM Society International
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Track: Decision Sciences
Abstract

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.

Published in: 3rd European International Conference on Industrial Engineering and Operations Management, Pilsen, Czech Republic

Publisher: IEOM Society International
Date of Conference: July 23-26, 2019

ISBN: 978-1-5323-5949-1
ISSN/E-ISSN: 2169-8767