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  • Search: subject:"Candlestick technical analysis"
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Year of publication
Subject
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Candlestick technical analysis 6 Stock market predicting 6 Support vector machine 6 Aktienmarkt 4 Algorithm 4 Algorithmus 4 Financial analysis 4 Finanzanalyse 4 Forecasting model 4 Machine learning 4 Meta-heuristic algorithms 4 Mustererkennung 4 Neural networks 4 Neuronale Netze 4 Pattern recognition 4 Prognoseverfahren 4 Stock market 4 Theorie 4 Theory 4 Börsenkurs 3 Share price 3 Artificial intelligence 2 Heuristics 2 Heuristik 2 Künstliche Intelligenz 2 Neural network 2 Particle swarm optimization 2 Aktienindex 1 Forecast 1 Mathematical programming 1 Mathematische Optimierung 1 Prognose 1 Stock index 1
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Online availability
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Free 3 Undetermined 3 CC license 2
Type of publication
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Article 6
Type of publication (narrower categories)
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Article in journal 4 Aufsatz in Zeitschrift 4 Article 1 research-article 1
Language
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English 6
Author
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Hashemi, Leila 6 Jasemi, Milad 6 Mahmoodi, Armin 6 Laliberté, Jeremy 2 Mahmoodi, Amin 2 Mahmoodi, Benyamin 2 Millar, Richard C. 2 Mehraban, Soroush 1 Noshadi, Hamed 1
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Published in...
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Asian journal of economics and banking : AJEB 1 EuroMed Journal of Business 1 EuroMed journal of business 1 Journal of Capital Markets Studies (JCMS) 1 Journal of capital markets studies 1 Opsearch : journal of the Operational Research Society of India 1
Source
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ECONIS (ZBW) 4 EconStor 1 Other ZBW resources 1
Showing 1 - 6 of 6
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Novel comparative methodology of hybrid support vector machine with meta-heuristic algorithms to develop an integrated candlestick technical analysis model
Mahmoodi, Armin; Hashemi, Leila; Mahmoodi, Amin; … - In: Journal of capital markets studies 8 (2024) 1, pp. 67-94
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),...
Persistent link: https://www.econbiz.de/10015047541
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Novel comparative methodology of hybrid support vector machine with meta-heuristic algorithms to develop an integrated candlestick technical analysis model
Mahmoodi, Armin; Hashemi, Leila; Mahmoodi, Amin; … - In: Journal of Capital Markets Studies (JCMS) 8 (2024) 1, pp. 67-94
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),...
Persistent link: https://www.econbiz.de/10015327938
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A novel approach for candlestick technical analysis using a combination of the support vector machine and particle swarm optimization
Mahmoodi, Armin; Hashemi, Leila; Jasemi, Milad; … - In: Asian journal of economics and banking : AJEB 7 (2023) 1, pp. 2-24
Purpose - In this research, the main purpose is to use a suitable structure to predict the trading signals of the stock market with high accuracy. For this purpose, two models for the analysis of technical adaptation were used in this study. Design/methodology/approach - It can be seen that...
Persistent link: https://www.econbiz.de/10014309150
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Develop an integrated candlestick technical analysis model using meta-heuristic algorithms
Mahmoodi, Armin; Hashemi, Leila; Jasemi, Milad - In: EuroMed journal of business 19 (2024) 4, pp. 1231-1270
Persistent link: https://www.econbiz.de/10015327533
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A developed stock price forecasting model using support vector machine combined with metaheuristic algorithms
Mahmoodi, Armin; Hashemi, Leila; Jasemi, Milad; … - In: Opsearch : journal of the Operational Research Society … 60 (2023) 1, pp. 59-86
Persistent link: https://www.econbiz.de/10014280628
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Cover Image
Develop an integrated candlestick technical analysis model using meta-heuristic algorithms
Mahmoodi, Armin; Hashemi, Leila; Jasemi, Milad - In: EuroMed Journal of Business 19 (2023) 4, pp. 1231-1270
Purpose In this study, the central objective is to foresee stock market signals with the use of a proper structure to achieve the highest accuracy possible. For this purpose, three hybrid models have been developed for the stock markets which are a combination of support vector machine (SVM)...
Persistent link: https://www.econbiz.de/10015343564
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