國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Algorithmic approaches to financial ...

IGI Global.

Algorithmic approaches to financial technologyforecasting, trading, and optimization /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Algorithmic approaches to financial technologyAmandeep Singh, Sanjay Taneja, Pawan Kumar, editors.
其他題名:	forecasting, trading, and optimization /
其他作者:	Kumar, Pawan,
出版者:	Hershey, Pennsylvania :IGI Global,2024.
面頁冊數:	1 online resource (266 p.)
標題:	FinanceMathematical models.
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1746-4
ISBN:	9798369317471$q(ebook)

Algorithmic approaches to financial technologyforecasting, 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: 9798369317471$q(ebook)Subjects--Topical Terms:

183782
Finance
--Mathematical models.Index Terms--Genre/Form:

214472
Electronic books.

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

Dewey Class. No.: 332.01/51

Algorithmic approaches to financial technologyforecasting, trading, and optimization /
LDR:03246nmm a2200241 a 4500 001 662303
006 m d
007 cr nn muauu
008 241202s2024 pau fob 001 0 eng d
020 $a 9798369317471$q(ebook)
020 $a 9798369317464$q(print)
035 $a (OCoLC)1417813849
035 $a 00329966
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
041 0 $a eng
050 4 $a HG106 $b .A4198 2024e
082 0 4 $a 332.01/51 $2 23
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.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2024.
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 183782
650 0 $a Finance $x Technological innovations. $3 775508
655 4 $a Electronic books. $2 local. $3 214472
700 1 $a Kumar, Pawan, $c (Professor of finance). $3 974153
700 1 $a Taneja, Sanjay. $3 974055
700 1 $a Singh, Amandeep, $d 1982- $3 927228
710 2 $a IGI Global. $3 529832
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1746-4