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020 _a9783031577086
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024 7 _a10.1007/978-3-031-57708-6
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050 4 _aQ342
072 7 _aUYQ
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072 7 _aCOM004000
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072 7 _aUYQ
_2thema
245 1 0 _aComputing Intelligence in Capital Market
_h[electronic resource] /
_cedited by Asef Yelghi, Aref Yelghi, Mehmet Apan, Shirmohammad Tavangari.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aV, 65 p. 19 illus., 13 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v1154
505 0 _a -- 1. Estimating and Evaluation of International Capital Movements in The Perspective of Corporate Economic Geography. -- 2. Wave Net-TSRS Model for Timeseries Prediction in Finance. -- 3. Integrating Decision Analytics and Advanced Modeling in Financial and Economic Systems through Artificial Intelligence. -- 4. Co-movements between Bitcoin and Gold: Multivariate BEKK-GARCH Models. -- 5. An Approach for backtesting and algorithmic trading with liquidity and Hill Climbing algorithm. -- 6. Unleashing Economic Potential: Exploring the Synergy of Artificial Intelligence and Intelligent Automation.
520 _aThe book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections are implementation and analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented.
650 0 _aComputational intelligence.
_964052
650 0 _aArtificial intelligence.
_958441
650 0 _aFinance.
_958339
650 0 _abranding
_xmarketing
_958950
650 1 4 _aComputational Intelligence.
_964052
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aFinancial Economics.
_969737
650 2 4 _aBranding.
_964224
700 1 _aYelghi, Asef.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_976025
700 1 _aYelghi, Aref.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_976026
700 1 _aApan, Mehmet.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_976027
700 1 _aTavangari, Shirmohammad.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_976028
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031577079
776 0 8 _iPrinted edition:
_z9783031577093
776 0 8 _iPrinted edition:
_z9783031577109
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v1154
_968854
856 4 0 _uhttps://doi.org/10.1007/978-3-031-57708-6
912 _aZDB-2-INR
912 _aZDB-2-SXIT
999 _c59504
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