Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading
Stock traders' forecasting strategies are mainly dependent on Technical Analysis (TA) indicators. However, some traders would follow their intuition and emotional aspects when trading instead of following the mathematically solid forecasting techniques of TA(s). The objective of this paper is t...
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| Format: | Article |
| Language: | English |
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Ayandegan Institute of Higher Education,
2022-03-01
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| Series: | Journal of Fuzzy Extension and Applications |
| Subjects: | |
| Online Access: | https://www.journal-fea.com/article_142511_837ec54c67c1f4f4ed4522371022c772.pdf |
| _version_ | 1797744275532808192 |
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| author | Issam Kouatli |
| author_facet | Issam Kouatli |
| author_sort | Issam Kouatli |
| collection | DOAJ |
| description | Stock traders' forecasting strategies are mainly dependent on Technical Analysis (TA) indicators. However, some traders would follow their intuition and emotional aspects when trading instead of following the mathematically solid forecasting techniques of TA(s). The objective of this paper is to help traders to rationalize their choices by generating the maximum and minimum tolerances of possible prices (termed in this paper as "fuzzy spectrum") and hence reducing their "emotional" trading decisions. This would be an important aspect towards avoiding an undesired outcome. Fuzzy logic has been used in this paper to identify such tolerances based on the most popular TA(s). Fuzzification of these TA(s) was used via a modular approach of fuzzy logic and by adopting "fuzzimetric sets" described in this paper to achieve the "fuzzy spectrum" of forecasted price tolerances when buying and selling decisions. Experimental results show the success of developing the "fuzzy spectrum" based on the "fuzzy" tolerances discovered from the TA(s) outputs. As a result, this paper contributes towards a better "rationalized" decision making when it comes to buying and selling stocks in this kind of industry. |
| first_indexed | 2024-03-12T15:07:25Z |
| format | Article |
| id | doaj.art-8be16520b154439a9eea9df7aa82d998 |
| institution | Directory Open Access Journal |
| issn | 2783-1442 2717-3453 |
| language | English |
| last_indexed | 2024-03-12T15:07:25Z |
| publishDate | 2022-03-01 |
| publisher | Ayandegan Institute of Higher Education, |
| record_format | Article |
| series | Journal of Fuzzy Extension and Applications |
| spelling | doaj.art-8be16520b154439a9eea9df7aa82d9982023-08-12T10:01:19ZengAyandegan Institute of Higher Education,Journal of Fuzzy Extension and Applications2783-14422717-34532022-03-0131456310.22105/jfea.2021.315178.1171142511Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional tradingIssam Kouatli0Department of Information Technology and Operations Management, Lebanese American University (LAU), Lebanon.Stock traders' forecasting strategies are mainly dependent on Technical Analysis (TA) indicators. However, some traders would follow their intuition and emotional aspects when trading instead of following the mathematically solid forecasting techniques of TA(s). The objective of this paper is to help traders to rationalize their choices by generating the maximum and minimum tolerances of possible prices (termed in this paper as "fuzzy spectrum") and hence reducing their "emotional" trading decisions. This would be an important aspect towards avoiding an undesired outcome. Fuzzy logic has been used in this paper to identify such tolerances based on the most popular TA(s). Fuzzification of these TA(s) was used via a modular approach of fuzzy logic and by adopting "fuzzimetric sets" described in this paper to achieve the "fuzzy spectrum" of forecasted price tolerances when buying and selling decisions. Experimental results show the success of developing the "fuzzy spectrum" based on the "fuzzy" tolerances discovered from the TA(s) outputs. As a result, this paper contributes towards a better "rationalized" decision making when it comes to buying and selling stocks in this kind of industry.https://www.journal-fea.com/article_142511_837ec54c67c1f4f4ed4522371022c772.pdfcognitive modellingfuzzy systemtechnical analysistrading systemsstock trading optimizationfuzzimetric sets |
| spellingShingle | Issam Kouatli Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading Journal of Fuzzy Extension and Applications cognitive modelling fuzzy system technical analysis trading systems stock trading optimization fuzzimetric sets |
| title | Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading |
| title_full | Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading |
| title_fullStr | Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading |
| title_full_unstemmed | Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading |
| title_short | Modeling fuzzimetric cognition of technical analysis decisions: reducing emotional trading |
| title_sort | modeling fuzzimetric cognition of technical analysis decisions reducing emotional trading |
| topic | cognitive modelling fuzzy system technical analysis trading systems stock trading optimization fuzzimetric sets |
| url | https://www.journal-fea.com/article_142511_837ec54c67c1f4f4ed4522371022c772.pdf |
| work_keys_str_mv | AT issamkouatli modelingfuzzimetriccognitionoftechnicalanalysisdecisionsreducingemotionaltrading |