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Developing a model based on fuzzy logic for identifying reversal points in capital markets derived from technical analysis | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 05 خرداد 1405 اصل مقاله (3.14 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2024.35389.5267 | ||
| نویسندگان | ||
| Valiollah Mehri1؛ Mehrdad Ghanbari* 2؛ Babak Jamshidinavid2؛ Alireza Moradi3 | ||
| 1Department of Financial Management, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran | ||
| 2Department of Accounting, Faculty of Humanities, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran | ||
| 3Department of Economics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran | ||
| تاریخ دریافت: 30 مرداد 1403، تاریخ بازنگری: 30 شهریور 1403، تاریخ پذیرش: 15 مهر 1403 | ||
| چکیده | ||
| This research aims to present a model for identifying reversal points in capital markets using technical analysis based on fuzzy logic. From the perspective of its objectives, this is an applied research, meaning it seeks to acquire the necessary knowledge to develop a tool that addresses key needs of shareholders, such as identifying reversal points, which are crucial in decision-making for buying and selling. Additionally, since the study aims to find relationships between variables to identify reversal points and assess the impact of their changes on the overall outcome, it is classified as causal or experimental research in terms of its methodology. From the perspective of data type, this research is based on quantitative data. In terms of timing, this study employs a cross-sectional design followed by a prospective approach. In this research, fuzzy logic and genetic algorithms were used to provide a method for identifying reversal points in financial markets. For this purpose, a Mamdani fuzzy system was employed. After implementing the proposed structure, the optimized membership functions were evaluated to ensure their alignment with the research objective (identifying reversal points). The proposed method, due to its desirable accuracy in identifying reversal points, has increased the returns from trading. If users enter or exit trades based on alerts with a probability higher than 85%, according to the type of reversal point, they will enter or exit trades at the right time in about 94% of cases, which will significantly contribute to improving the profitability of their trades. | ||
| کلیدواژهها | ||
| Return points؛ capital market؛ technical analysis؛ fuzzy logic | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 43 تعداد دریافت فایل اصل مقاله: 73 |
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