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1 – 10 of 16
Content available
Article
Publication date: 2 August 2011

David Orrell

210

Abstract

Details

International Journal of Social Economics, vol. 38 no. 9
Type: Research Article
ISSN: 0306-8293

Content available
Book part
Publication date: 30 September 2019

Jacob Dahl Rendtorff

Abstract

Details

Philosophy of Management and Sustainability: Rethinking Business Ethics and Social Responsibility in Sustainable Development
Type: Book
ISBN: 978-1-78973-453-9

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Book part
Publication date: 12 September 2017

Abstract

Details

The Economics of Airport Operations
Type: Book
ISBN: 978-1-78714-497-2

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Article
Publication date: 20 June 2008

279

Abstract

Details

Strategic Direction, vol. 24 no. 8
Type: Research Article
ISSN: 0258-0543

Content available
Article
Publication date: 11 September 2009

Nicholas Tsounis and Aspasia Vlahvei

328

Abstract

Details

Journal of International Trade Law and Policy, vol. 8 no. 3
Type: Research Article
ISSN: 1477-0024

Content available
Article
Publication date: 6 June 2008

320

Abstract

Details

Journal of Chinese Economic and Foreign Trade Studies, vol. 1 no. 2
Type: Research Article
ISSN: 1754-4408

Content available
Article
Publication date: 8 February 2008

David Cromb

2731

Abstract

Details

Leadership & Organization Development Journal, vol. 29 no. 1
Type: Research Article
ISSN: 0143-7739

Keywords

Open Access
Article
Publication date: 8 December 2023

Armin Mahmoodi, Leila Hashemi, Amin Mahmoodi, Benyamin Mahmoodi and Milad Jasemi

The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese…

Abstract

Purpose

The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).

Design/methodology/approach

In addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.

Findings

Results have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

Research limitations/implications

In this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.

Originality/value

In this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

Details

Journal of Capital Markets Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-4774

Keywords

Content available
Article
Publication date: 1 March 2003

Michael Mainelli

103

Abstract

Details

Balance Sheet, vol. 11 no. 1
Type: Research Article
ISSN: 0965-7967

Content available
Article
Publication date: 25 January 2008

Guijun Lin and Richard Li-Hua

2175

Abstract

Details

Journal of Chinese Economic and Foreign Trade Studies, vol. 1 no. 1
Type: Research Article
ISSN: 1754-4408

1 – 10 of 16