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Title: Aplikasi Model Artificial Neural Network Untuk Stock Forecasting Di Pasar Modal Indonesia
Authors: Herdinata, Christian
Keywords: Artificial Neural Networks (ANN), Buy & Hold Strategy, Technical Trading Rule, Efficient Market Hypothesis
Issue Date: Jan-2010
Publisher: Program Studi Keuangan dan Perbankan, Universitas Merdeka Malang,
Citation: Herdinata, C. (2010). Aplikasi model artificial neural network untuk stock forecasting di pasar modal indonesia. Jurnal keuangan dan perbankan , 14(01), 001-012. Retrieved from
Abstract: This research showed the application of model Artificial Neural Networks (ANN) or Jaringan Syaraf Tiruan (JST) at the field of monetary science, especially for the application of financial forecasting. ANN or JST was a new alternative for the application of financial forecasting.The purpose of this research was to know whether the stock index instantaneously and fully reflect historical information, in Indonesia Stock Exchange (IDX). The research used comparison between return of technical trading rule based Artificial Neural Networks (ANN) model and return of buy & hold strategy. The result showed that the weakness form of efficient market hypothesis was rejected in the Indonesian capital market. Expectation of this research was giving information and securing the market perpetrators that still enabled to get abnormal of return by doing commerce in chnical through forecasting of model Artificial Neural Networks (ANN) or Jaringan Syaraf Tiruan (JST).
ISSN: 1410-8089
Appears in Collections:Lecture Papers National Published Articles

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