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Algorithmic approaches to financial technology = forecasting, trading, and optimization /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Algorithmic approaches to financial technology/ Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors.
Reminder of title:	forecasting, trading, and optimization /
other author:	Kumar, Pawan,
Published:	Hershey, Pennsylvania :IGI Global, : 2024.,
Description:	1 online resource (266 p.)
Subject:	Finance - Mathematical models. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1746-4
ISBN:	9798369317471

Algorithmic approaches to financial technology = forecasting, trading, and optimization /
Algorithmic approaches to financial technologyforecasting, trading, and optimization /[electronic resource] :Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors. - Hershey, Pennsylvania :IGI Global,2024. - 1 online resource (266 p.)

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.

"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 thefinancial 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 bookserves 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."--

ISBN: 9798369317471Subjects--Topical Terms:

557653
Finance
--Mathematical models.Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: HG106 / .A4198 2024e

Dewey Class. No.: 332.01/51

Algorithmic approaches to financial technology = forecasting, trading, and optimization /
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245 0 0 $a Algorithmic approaches to financial technology $h [electronic resource] : $b forecasting, trading, and optimization / $c Amandeep Singh, Sanjay Taneja, Pawan Kumar, editors.
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300 $a 1 online resource (266 p.)
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.
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 thefinancial 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 bookserves 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.
650 0 $a Finance $x Mathematical models. $3 557653
650 0 $a Finance $x Technological innovations. $3 1135526
655 4 $a Electronic books. $2 local $3 554714
700 1 $a Kumar, Pawan, $c (Professor of finance). $3 1458742
700 1 $a Taneja, Sanjay. $3 1458637
700 1 $a Singh, Amandeep, $d 1982- $3 1403762
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856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1746-4