The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange
The present research proposes an automatic system based on moving average (MA) and fuzzy logic to recognize technical analysis patterns including head and shoulder patterns, triangle patterns and broadening patterns in the Tehran Stock Exchange. The automatic system was used on 38 indicators of Tehr...
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Islamic Azad University of Arak
2019-07-01
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doaj-dd5af10ae843477cb44c05fc8c4c4f502020-11-25T01:19:08ZengIslamic Azad University of ArakAdvances in Mathematical Finance and Applications2538-55692645-46102019-07-014310712510.22034/amfa.2019.585179.1185666547The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock ExchangeAbdolmajid Abdolbaghi Ataabadi0Sayyed Mohammad Reza Davoodi1Mohammad Salimi Bani2Department of Management, Industrial Engineering, Amp and Management Sciences, Shahrood University of TechnologyDepartment of Management ,Dehaghan Branch, Islamic Azad University, Dehaghan, Iran.Department of Financial Engineering, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran.The present research proposes an automatic system based on moving average (MA) and fuzzy logic to recognize technical analysis patterns including head and shoulder patterns, triangle patterns and broadening patterns in the Tehran Stock Exchange. The automatic system was used on 38 indicators of Tehran Stock Exchange within the period 2014-2017 in order to evaluate the effectiveness of technical patterns. Having compared the conditional distribution of daily returns under the condition of the discovered patterns and the unconditional distribution of returns at various levels of confidence driven from fuzzy logic with the mean returns of all normalized market indicators, we observed that in the desired period, after recognizing the pattern, all patterns investigated at the confidence level 0.95 with a fuzzy point 0.5 contained useful information, practically leading to abnormal returns.http://amfa.iau-arak.ac.ir/article_666547_66fbf06cde194d2677596e7ba580e1f2.pdftechnical patternspattern recognitionmoving averagefuzzy logic |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Abdolmajid Abdolbaghi Ataabadi Sayyed Mohammad Reza Davoodi Mohammad Salimi Bani |
spellingShingle |
Abdolmajid Abdolbaghi Ataabadi Sayyed Mohammad Reza Davoodi Mohammad Salimi Bani The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange Advances in Mathematical Finance and Applications technical patterns pattern recognition moving average fuzzy logic |
author_facet |
Abdolmajid Abdolbaghi Ataabadi Sayyed Mohammad Reza Davoodi Mohammad Salimi Bani |
author_sort |
Abdolmajid Abdolbaghi Ataabadi |
title |
The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange |
title_short |
The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange |
title_full |
The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange |
title_fullStr |
The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange |
title_full_unstemmed |
The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange |
title_sort |
effectiveness of the automatic system of fuzzy logic-based technical patterns recognition: evidence from tehran stock exchange |
publisher |
Islamic Azad University of Arak |
series |
Advances in Mathematical Finance and Applications |
issn |
2538-5569 2645-4610 |
publishDate |
2019-07-01 |
description |
The present research proposes an automatic system based on moving average (MA) and fuzzy logic to recognize technical analysis patterns including head and shoulder patterns, triangle patterns and broadening patterns in the Tehran Stock Exchange. The automatic system was used on 38 indicators of Tehran Stock Exchange within the period 2014-2017 in order to evaluate the effectiveness of technical patterns. Having compared the conditional distribution of daily returns under the condition of the discovered patterns and the unconditional distribution of returns at various levels of confidence driven from fuzzy logic with the mean returns of all normalized market indicators, we observed that in the desired period, after recognizing the pattern, all patterns investigated at the confidence level 0.95 with a fuzzy point 0.5 contained useful information, practically leading to abnormal returns. |
topic |
technical patterns pattern recognition moving average fuzzy logic |
url |
http://amfa.iau-arak.ac.ir/article_666547_66fbf06cde194d2677596e7ba580e1f2.pdf |
work_keys_str_mv |
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