Multiple strategies for trading short-term stock index futures based on visual trend bands

Many day traders focus on forecasts of stock index futures. These securities are suitable for frequent and time-sensitive trading as well as for short-term investments. However, most day traders’ strategies are based on their experiences or news headlines. Combined with a pool trading policy, this m...

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Vydané v:Multimedia tools and applications Ročník 80; číslo 28-29; s. 35481 - 35494
Hlavní autori: Chou, Hsien-Ming, Hung, Chihli
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.11.2021
Springer Nature B.V
Predmet:
1166: Advances of machine learning in data analytics and visual information processing
Algorithms
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Employment
Futures
Investment strategy
Machine learning
Multimedia Information Systems
Optimization
Special Purpose and Application-Based Systems
Day traders
Short-term investment
Stock index futures
Machine learning
Visual trend bands
ISSN:1380-7501, 1573-7721
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Abstract Many day traders focus on forecasts of stock index futures. These securities are suitable for frequent and time-sensitive trading as well as for short-term investments. However, most day traders’ strategies are based on their experiences or news headlines. Combined with a pool trading policy, this may lead to unsatisfactory average monthly profit, particularly when compared to the opportunity cost of the traders’ full-time employment in other non-trading jobs. This paper represents multiple investment strategies for day traders based on visual trend bands on short-term stock index futures. This study uses sequential minimal optimization and other machine learning algorithms to evaluate the performance of visual trend bands and derive strategies for better predictions. This study also applies empirical methods on short-term stock index futures datasets to explore the impact of visual trend bands on short-term stock index trading. The accuracy of our proposed visual trend bands reaches 82%, which is not only an objectively high forecasting accuracy rate but also substantially higher than other visual trend bands. The proposed visual trend bands can support day traders in realizing higher profits in their day trades and short-term investments.
AbstractList Many day traders focus on forecasts of stock index futures. These securities are suitable for frequent and time-sensitive trading as well as for short-term investments. However, most day traders’ strategies are based on their experiences or news headlines. Combined with a pool trading policy, this may lead to unsatisfactory average monthly profit, particularly when compared to the opportunity cost of the traders’ full-time employment in other non-trading jobs. This paper represents multiple investment strategies for day traders based on visual trend bands on short-term stock index futures. This study uses sequential minimal optimization and other machine learning algorithms to evaluate the performance of visual trend bands and derive strategies for better predictions. This study also applies empirical methods on short-term stock index futures datasets to explore the impact of visual trend bands on short-term stock index trading. The accuracy of our proposed visual trend bands reaches 82%, which is not only an objectively high forecasting accuracy rate but also substantially higher than other visual trend bands. The proposed visual trend bands can support day traders in realizing higher profits in their day trades and short-term investments.
Author Hung, Chihli
Chou, Hsien-Ming
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  organization: Department of Information Management, Chung Yuan Christian University
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  givenname: Chihli
  surname: Hung
  fullname: Hung, Chihli
  organization: Department of Information Management, Chung Yuan Christian University
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Copyright The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021
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Keywords Day traders
Short-term investment
Stock index futures
Machine learning
Visual trend bands
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SubjectTerms 1166: Advances of machine learning in data analytics and visual information processing
Algorithms
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Employment
Futures
Investment strategy
Machine learning
Multimedia Information Systems
Optimization
Special Purpose and Application-Based Systems
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Title Multiple strategies for trading short-term stock index futures based on visual trend bands
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