Predicting the direction of Indonesian stock price movement using support vector machines and fuzzy Kernel C-Means

Z. Rustam, D. F. Vibranti, D. Widya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

The nature of stock price fluctuations becomes a challenge for the investors to gain return in investing stocks. To overcome this problem, investors need some accurate predictions in order to anticipate future stock price movement. However, predicting the direction of stock price movement is a complex task due to many uncertain factors affecting the stock price itself. Therefore, this paper studied the application of Support Vector Machines and Fuzzy Kernel C-Means in predicting the direction of stock price movement of Indonesian stock market, particularly on banking subsector. Using the stock historical data, eight technical indicators have been computed to obtain two different approaches for the input model. One of them use the computed indicators while the other process the computed indicators into trends. The results suggest that, in general view, Support Vector Machines with technical indicators represented as trend being the input model outperforms the other prediction models. However, in particular condition, the best model of the entire observation with 92 % accuracy is given by FKCM with computed indicators as the input by using σ = 100 and 90 % training data.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
EditorsRatna Yuniati, Terry Mart, Ivandini T. Anggraningrum, Djoko Triyono, Kiki A. Sugeng
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735417410
DOIs
Publication statusPublished - 22 Oct 2018
Event3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017 - Bali, Indonesia
Duration: 26 Jul 201727 Jul 2017

Publication series

NameAIP Conference Proceedings
Volume2023
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
Country/TerritoryIndonesia
CityBali
Period26/07/1727/07/17

Keywords

  • Fuzzy Kernel C-Means
  • Support Vector Machines
  • prediction
  • stock price movement
  • technical indicators

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