Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS method
In the dynamic realm of financial markets, developing effective strategies for stock exchange transactions is paramount. This research addresses this critical need by introducing a pioneering indicator for daily stock trading, leveraging a robust fuzzy inference system (FIS). The indicator ingenious...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Results in Control and Optimization |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666720723001674 |
| _version_ | 1797259644874260480 |
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| author | R. Venugopal C. Veeramani S.A. Edalatpanah |
| author_facet | R. Venugopal C. Veeramani S.A. Edalatpanah |
| author_sort | R. Venugopal |
| collection | DOAJ |
| description | In the dynamic realm of financial markets, developing effective strategies for stock exchange transactions is paramount. This research addresses this critical need by introducing a pioneering indicator for daily stock trading, leveraging a robust fuzzy inference system (FIS). The indicator ingeniously integrates key technical indicators including Moving Average Convergence and Divergence (MACD), Relative Strength Index (RSI), Stochastic Oscillator (SO), and On-Balance-Volume (OBV). The FIS is meticulously constructed based on expert opinions and gleaned fuzzy rules. The fuzzified values then serve as inputs to the FIS, which in turn generates signals indicating optimal actions: buy, hold, or sell stocks. To validate the importance of the FIS, a carefully curated selection of stocks from the NASDAQ stock exchange is employed for experimentation. To prove the efficiency of the FIS, the technical indicators and the fuzzy risk-adjusted returns are considered as alternatives and criteria, respectively. A novel Z-number-based technique for order preference by similarity to the ideal solution (TOPSIS) method is used to rank the technical indicators and the FIS. The comparative results unequivocally demonstrate that the developed FIS surpasses existing indicators, yielding superior returns. |
| first_indexed | 2024-03-08T19:41:37Z |
| format | Article |
| id | doaj.art-882376d9ff6a433ea16f7cf024aeba62 |
| institution | Directory Open Access Journal |
| issn | 2666-7207 |
| language | English |
| last_indexed | 2024-04-24T23:12:43Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Control and Optimization |
| spelling | doaj.art-882376d9ff6a433ea16f7cf024aeba622024-03-17T07:58:58ZengElsevierResults in Control and Optimization2666-72072024-03-0114100365Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS methodR. Venugopal0C. Veeramani1S.A. Edalatpanah2Department of Applied Science(Mathematics), PSG College of Technology, Coimbatore 641 004, Tamil Nadu, IndiaDepartment of Applied Science(Mathematics), PSG College of Technology, Coimbatore 641 004, Tamil Nadu, India; Corresponding author.Department of Applied Mathematics, Ayandegan Institute of Higher Education, Tonekabon, IranIn the dynamic realm of financial markets, developing effective strategies for stock exchange transactions is paramount. This research addresses this critical need by introducing a pioneering indicator for daily stock trading, leveraging a robust fuzzy inference system (FIS). The indicator ingeniously integrates key technical indicators including Moving Average Convergence and Divergence (MACD), Relative Strength Index (RSI), Stochastic Oscillator (SO), and On-Balance-Volume (OBV). The FIS is meticulously constructed based on expert opinions and gleaned fuzzy rules. The fuzzified values then serve as inputs to the FIS, which in turn generates signals indicating optimal actions: buy, hold, or sell stocks. To validate the importance of the FIS, a carefully curated selection of stocks from the NASDAQ stock exchange is employed for experimentation. To prove the efficiency of the FIS, the technical indicators and the fuzzy risk-adjusted returns are considered as alternatives and criteria, respectively. A novel Z-number-based technique for order preference by similarity to the ideal solution (TOPSIS) method is used to rank the technical indicators and the FIS. The comparative results unequivocally demonstrate that the developed FIS surpasses existing indicators, yielding superior returns.http://www.sciencedirect.com/science/article/pii/S2666720723001674Fuzzy inference systemFuzzy multi criteria decision makingRanking performanceTechnical indicatorZ-number |
| spellingShingle | R. Venugopal C. Veeramani S.A. Edalatpanah Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS method Results in Control and Optimization Fuzzy inference system Fuzzy multi criteria decision making Ranking performance Technical indicator Z-number |
| title | Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS method |
| title_full | Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS method |
| title_fullStr | Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS method |
| title_full_unstemmed | Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS method |
| title_short | Enhancing daily stock trading with a novel fuzzy indicator: Performance analysis using Z-number based fuzzy TOPSIS method |
| title_sort | enhancing daily stock trading with a novel fuzzy indicator performance analysis using z number based fuzzy topsis method |
| topic | Fuzzy inference system Fuzzy multi criteria decision making Ranking performance Technical indicator Z-number |
| url | http://www.sciencedirect.com/science/article/pii/S2666720723001674 |
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