COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETS
Artificial neural networks (ANNs) allow users to improve forecasts through pattern recognition. The purpose of this paper is to validate ANNs as a detection tool in four financial markets. This study investigates whether market inefficiencies exist using ANN as a model. It also investigates whether...
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doaj-43a2ce2344cc4900b660b66af9a5cb232020-11-25T00:58:10ZengUniversiti Sains Malaysia Asian Academy of Management Journal1394-26031985-82802002-01-01721725COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETSJoachim TanEdward Sek WongArtificial neural networks (ANNs) allow users to improve forecasts through pattern recognition. The purpose of this paper is to validate ANNs as a detection tool in four financial markets. This study investigates whether market inefficiencies exist using ANN as a model. It also investigates whether additional publicly available information can provide investors with a trading advantage. In finance, any forecasting advantage obtained through the use of publicly available information albeit internal or/and external market factors suggest inefficiencies in the financial markets. In this paper, we explore the efficiency of the United States, Japan, Hong Kong and Australia. In Australia, using the ASX 200 index, we demonstrate how the inclusion of external information to our ANN improves our forecasting. Our results show accounting for external market signals significantly improves forecasts of the ASX200 index by an additional 10 percent. This suggests the inclusion of publicly available information from other markets, can improve predictions and returns for investors.http://www.usm.my/aamj/7.2.2002/AAMJ%207-2-2.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Joachim Tan Edward Sek Wong |
spellingShingle |
Joachim Tan Edward Sek Wong COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETS Asian Academy of Management Journal |
author_facet |
Joachim Tan Edward Sek Wong |
author_sort |
Joachim Tan |
title |
COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETS |
title_short |
COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETS |
title_full |
COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETS |
title_fullStr |
COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETS |
title_full_unstemmed |
COGNITIVE LEARNING OF INTELLIGENCE SYSTEMS USING NEURAL NETWORKS: EVIDENCE FROM THE AUSTRALIAN CAPITAL MARKETS |
title_sort |
cognitive learning of intelligence systems using neural networks: evidence from the australian capital markets |
publisher |
Universiti Sains Malaysia |
series |
Asian Academy of Management Journal |
issn |
1394-2603 1985-8280 |
publishDate |
2002-01-01 |
description |
Artificial neural networks (ANNs) allow users to improve forecasts through pattern recognition. The purpose of this paper is to validate ANNs as a detection tool in four financial markets. This study investigates whether market inefficiencies exist using ANN as a model. It also investigates whether additional publicly available information can provide investors with a trading advantage. In finance, any forecasting advantage obtained through the use of publicly available information albeit internal or/and external market factors suggest inefficiencies in the financial markets. In this paper, we explore the efficiency of the United States, Japan, Hong Kong and Australia. In Australia, using the ASX 200 index, we demonstrate how the inclusion of external information to our ANN improves our forecasting. Our results show accounting for external market signals significantly improves forecasts of the ASX200 index by an additional 10 percent. This suggests the inclusion of publicly available information from other markets, can improve predictions and returns for investors. |
url |
http://www.usm.my/aamj/7.2.2002/AAMJ%207-2-2.pdf |
work_keys_str_mv |
AT joachimtan cognitivelearningofintelligencesystemsusingneuralnetworksevidencefromtheaustraliancapitalmarkets AT edwardsekwong cognitivelearningofintelligencesystemsusingneuralnetworksevidencefromtheaustraliancapitalmarkets |
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