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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Iranian Journal of Finance
- نوع مقاله: Journal Article
- کلمات کلیدی: PSO,Fuzzy inference system,Corrective property,Oscillators
- چکیده:
- چکیده انگلیسی: Technical analysis is constituted as an approach in the market analysis which is based on the study of pricing behavior and shares size in the past and price determination and its procedure in the future. Algorithmic transactions are growing rapidly in order to automate business strategies, given the arrival of computer-based technologies and the rapid processing of bulky information. Trading systems combine input information and ultimately identify the time of purchase and sale by forming one signal. In this paper, the training system is a kind of fuzzy inference system that combines fuzzified RSI and SO signals from technical analysis. The system’s trade rules database (selling, buying, and holding) would be calculated based on an optimization process using PSO. This optimization process should be repeated at certain intervals to keep the system up to date. This process is called the corrective property of systems. The findings on the overall index in the period 2001/3/21-2019/3/20 indicate that the system having optimized training on training data has an average daily return of /0027, risk-taking of /0065 and the daily sharp ratio of /42. Concerning the index of return and sharp ratio, the findings reveal that the system outperforms the signals and the market performance.
- انتشار مقاله: 17-10-1398
- نویسندگان: CharaghAli Bakhtiyariasl,Sayyed Mohammad Reza Davoodi,Abdolmajid Abdolbaghi Ataabadi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Technical patterns,pattern recognition,moving average,fuzzy logic
- چکیده:
- چکیده انگلیسی: 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.
- انتشار مقاله: 24-11-1397
- نویسندگان: Abdolmajid Abdolbaghi Ataabadi,Sayyed Mohammad Reza Davoodi,Mohammad Salimi Bani
- مشاهده