Algorithmic approaches to financial technology:
"Today, algorithms steer and inform more than 75% of modern trades. These mathematical constructs play an intricate role in automating processes, predicting market trends, optimizing portfolios, and fortifying decision-making in the financial domain. In an era where algorithms underpin the very...
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| Other Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2024.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "Today, algorithms steer and inform more than 75% of modern trades. These mathematical constructs play an intricate role in automating processes, predicting market trends, optimizing portfolios, and fortifying decision-making in the financial domain. In an era where algorithms underpin the very foundation of financial services, it is imperative to hold a deep understanding of the intricate web of computational finance.Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization takes a comprehensive approach, spotlighting the fusion of artificial intelligence(AI) and algorithms in financial operations. The chapters explore the expansive landscape of algorithmic applications, from scrutinizing market trends to managing risks. The emphasis extends to AI-driven personnel selection, implementing trusted financial services, crafting recommendation systems for financial platforms, and critical fraud detection. This book serves as a vital resource for researchers, students, and practitioners. Its core strength lies in discussing AI-based algorithms as a catalyst for evolving market trends. It provides algorithmic solutions for stock markets, portfolio optimization, and robust financial fraud detection mechanisms."-- |
| Physical Description: | 21 PDFs (266 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9798369317471 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
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| 245 | 0 | 0 | |a Algorithmic approaches to financial technology |c Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2024. | |
| 300 | |a 21 PDFs (266 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Chapter 1. Investigation of the time pattern of bit green crypto: an arma modeling approach to unrave volatility -- Chapter 2. Algorithmic FinTech pioneering the financial landscape of tomorrow -- Chapter 3. Disruptive technologies in computational finance -- Chapter 4. Challenges and opportunities of machine learning in the financial sector -- Chapter 5. Sustainability-driven finance: reshaping the financial world -- Chapter 6. Masters of the market: unleashing algorithmic wizardry in finance -- Chapter 7. The impact of corruption on economic growth in Tunisia: an application of ARDL approach -- Chapter 8. A study on rural BPL households' perception towards financial inclusion schemes -- Chapter 9. Contribution of disruptive technologies in computational finance -- Chapter 10. Organizational citizenship behavior and employee retention -- Chapter 11. User experience and interaction in information applications: advanced human-machine interfaces -- Chapter 12. Assessing the impact of quality and internal control on academic institutions' performance: a case of study of HIBAG. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "Today, algorithms steer and inform more than 75% of modern trades. These mathematical constructs play an intricate role in automating processes, predicting market trends, optimizing portfolios, and fortifying decision-making in the financial domain. In an era where algorithms underpin the very foundation of financial services, it is imperative to hold a deep understanding of the intricate web of computational finance.Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization takes a comprehensive approach, spotlighting the fusion of artificial intelligence(AI) and algorithms in financial operations. The chapters explore the expansive landscape of algorithmic applications, from scrutinizing market trends to managing risks. The emphasis extends to AI-driven personnel selection, implementing trusted financial services, crafting recommendation systems for financial platforms, and critical fraud detection. This book serves as a vital resource for researchers, students, and practitioners. Its core strength lies in discussing AI-based algorithms as a catalyst for evolving market trends. It provides algorithmic solutions for stock markets, portfolio optimization, and robust financial fraud detection mechanisms."-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 01/17/2024). | ||
| 650 | 0 | |a Finance |x Mathematical models. | |
| 650 | 0 | |a Finance |x Technological innovations. | |
| 653 | |a Algorithmic Finance. | ||
| 653 | |a Artificial Intelligence. | ||
| 653 | |a Automated Trading. | ||
| 653 | |a Computational Finance. | ||
| 653 | |a Cryptoanalysis in Finance. | ||
| 653 | |a Decision-Making. | ||
| 653 | |a Financial Fraud Detection. | ||
| 653 | |a Financial Services Automation. | ||
| 653 | |a Financial Technology. | ||
| 653 | |a High-Frequency Trading. | ||
| 653 | |a Machine Learning in Finance. | ||
| 653 | |a Market Trends Analysis. | ||
| 653 | |a Portfolio Optimization. | ||
| 653 | |a Predictive Analysis. | ||
| 653 | |a Risk Assessment. | ||
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Kumar, Pawan, |c (Professor of finance) |e editor. | |
| 700 | 1 | |a Singh, Amandeep |d 1982- |e editor. | |
| 700 | 1 | |a Taneja, Sanjay |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
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| 912 | |a ZDB-98-IGB | ||
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| author2 | Kumar, Pawan, (Professor of finance) Singh, Amandeep 1982- Taneja, Sanjay |
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| contents | Chapter 1. Investigation of the time pattern of bit green crypto: an arma modeling approach to unrave volatility -- Chapter 2. Algorithmic FinTech pioneering the financial landscape of tomorrow -- Chapter 3. Disruptive technologies in computational finance -- Chapter 4. Challenges and opportunities of machine learning in the financial sector -- Chapter 5. Sustainability-driven finance: reshaping the financial world -- Chapter 6. Masters of the market: unleashing algorithmic wizardry in finance -- Chapter 7. The impact of corruption on economic growth in Tunisia: an application of ARDL approach -- Chapter 8. A study on rural BPL households' perception towards financial inclusion schemes -- Chapter 9. Contribution of disruptive technologies in computational finance -- Chapter 10. Organizational citizenship behavior and employee retention -- Chapter 11. User experience and interaction in information applications: advanced human-machine interfaces -- Chapter 12. Assessing the impact of quality and internal control on academic institutions' performance: a case of study of HIBAG. |
| ctrlnum | (CaBNVSL)slc00005465 (OCoLC)1417813849 |
| dewey-full | 332.01/51 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
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| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00329966 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:37Z |
| institution | BVB |
| isbn | 9798369317471 |
| language | English |
| oclc_num | 1417813849 |
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| physical | 21 PDFs (266 Seiten) Also available in print. |
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| publishDate | 2024 |
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| spelling | Algorithmic approaches to financial technology Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2024. 21 PDFs (266 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Chapter 1. Investigation of the time pattern of bit green crypto: an arma modeling approach to unrave volatility -- Chapter 2. Algorithmic FinTech pioneering the financial landscape of tomorrow -- Chapter 3. Disruptive technologies in computational finance -- Chapter 4. Challenges and opportunities of machine learning in the financial sector -- Chapter 5. Sustainability-driven finance: reshaping the financial world -- Chapter 6. Masters of the market: unleashing algorithmic wizardry in finance -- Chapter 7. The impact of corruption on economic growth in Tunisia: an application of ARDL approach -- Chapter 8. A study on rural BPL households' perception towards financial inclusion schemes -- Chapter 9. Contribution of disruptive technologies in computational finance -- Chapter 10. Organizational citizenship behavior and employee retention -- Chapter 11. User experience and interaction in information applications: advanced human-machine interfaces -- Chapter 12. Assessing the impact of quality and internal control on academic institutions' performance: a case of study of HIBAG. Restricted to subscribers or individual electronic text purchasers. "Today, algorithms steer and inform more than 75% of modern trades. These mathematical constructs play an intricate role in automating processes, predicting market trends, optimizing portfolios, and fortifying decision-making in the financial domain. In an era where algorithms underpin the very foundation of financial services, it is imperative to hold a deep understanding of the intricate web of computational finance.Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization takes a comprehensive approach, spotlighting the fusion of artificial intelligence(AI) and algorithms in financial operations. The chapters explore the expansive landscape of algorithmic applications, from scrutinizing market trends to managing risks. The emphasis extends to AI-driven personnel selection, implementing trusted financial services, crafting recommendation systems for financial platforms, and critical fraud detection. This book serves as a vital resource for researchers, students, and practitioners. Its core strength lies in discussing AI-based algorithms as a catalyst for evolving market trends. It provides algorithmic solutions for stock markets, portfolio optimization, and robust financial fraud detection mechanisms."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 01/17/2024). Finance Mathematical models. Finance Technological innovations. Algorithmic Finance. Artificial Intelligence. Automated Trading. Computational Finance. Cryptoanalysis in Finance. Decision-Making. Financial Fraud Detection. Financial Services Automation. Financial Technology. High-Frequency Trading. Machine Learning in Finance. Market Trends Analysis. Portfolio Optimization. Predictive Analysis. Risk Assessment. Electronic books. Kumar, Pawan, (Professor of finance) editor. Singh, Amandeep 1982- editor. Taneja, Sanjay editor. IGI Global, publisher. Print version: 9798369317464 |
| spellingShingle | Algorithmic approaches to financial technology Chapter 1. Investigation of the time pattern of bit green crypto: an arma modeling approach to unrave volatility -- Chapter 2. Algorithmic FinTech pioneering the financial landscape of tomorrow -- Chapter 3. Disruptive technologies in computational finance -- Chapter 4. Challenges and opportunities of machine learning in the financial sector -- Chapter 5. Sustainability-driven finance: reshaping the financial world -- Chapter 6. Masters of the market: unleashing algorithmic wizardry in finance -- Chapter 7. The impact of corruption on economic growth in Tunisia: an application of ARDL approach -- Chapter 8. A study on rural BPL households' perception towards financial inclusion schemes -- Chapter 9. Contribution of disruptive technologies in computational finance -- Chapter 10. Organizational citizenship behavior and employee retention -- Chapter 11. User experience and interaction in information applications: advanced human-machine interfaces -- Chapter 12. Assessing the impact of quality and internal control on academic institutions' performance: a case of study of HIBAG. Finance Mathematical models. Finance Technological innovations. |
| title | Algorithmic approaches to financial technology |
| title_auth | Algorithmic approaches to financial technology |
| title_exact_search | Algorithmic approaches to financial technology |
| title_full | Algorithmic approaches to financial technology Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors. |
| title_fullStr | Algorithmic approaches to financial technology Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors. |
| title_full_unstemmed | Algorithmic approaches to financial technology Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors. |
| title_short | Algorithmic approaches to financial technology |
| title_sort | algorithmic approaches to financial technology |
| topic | Finance Mathematical models. Finance Technological innovations. |
| topic_facet | Finance Mathematical models. Finance Technological innovations. Electronic books. |
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