Christian Herdinata_abstract_1412010

APLIKASI MODEL ARTIFICIAL NEURAL NETWORKS UNTUK STOCK FORECASTING DI PASAR MODAL INDONESIA

Christian Herdinata
Fakultas Ekonomi Jurusan International Business Management
Universitas Ciputra Surabaya
Jl. Waterpark, Boulevard Citra Land 60216, Surabaya

Korespondensi dengan Penulis:
Christian Herdinata: Telp. + 62 31 745 1699, Faks. +62 31 745 1698
E-mail: christian.herdinata@ciputra.ac.id

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).

Key words:  Artificial Neural Networks (ANN), Buy & Hold Strategy, Technical Trading Rule, Efficient Market Hypothesis

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