Abdolmajid Abdolbaghi Ataabadi - Department of Management, Industrial Engineering, Amp and Management Sciences, Shahrood University of Technology
Sayyed Mohammad Reza Davoodi - Department of Management ,Dehaghan Branch, Islamic Azad University, Dehaghan, Iran.
Mohammad Salimi Bani - 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 ۳۸ indicators of Tehran Stock Exchange within the period ۲۰۱۴-۲۰۱۷ 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 ۰.۹۵ with a fuzzy point ۰.۵ contained useful information, practically leading to abnormal returns.

Technical patterns, pattern recognition, moving average, fuzzy logic