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Machine learning and modeling techniques in financial data science

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine learning and modeling techniques in financial data science/ Haojun Chen, editor.
other author:	Chen, Haojun,
Published:	Hershey, Pennsylvania :IGI Global, : 2025.,
Description:	1 online resource (xxiv, 547 p.) :ill. :
Subject:	Finance - Mathematical models. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8186-1
ISBN:	9798369381885

Machine learning and modeling techniques in financial data science
Machine learning and modeling techniques in financial data science[electronic resource] /Haojun Chen, editor. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (xxiv, 547 p.) :ill.

Includes bibliographic references and index.

Preface -- Section 1. ESG, Sustainability, and Fairness in AI for Financial Services -- Chapter 1. Fairness and Bias in Machine Learning Models for Credit Decisions -- Chapter 2. From Fintech to Green Fintech: How to Decarbonize theAI in the Financial Domain -- Chapter 3. Regulatory Challenges and Compliance in Decentralized Finance (DeFi): Comparative Study Between India and USA -- Section 2. Advances in AI and Machine Learning for Algorithmic and High-Frequency Trading -- Chapter 4. Revolutionizing High-Frequency Trading: The Impacts of Financial Technology and Data Science Innovations -- Chapter 5. Robo-Traders and PPO: Advancing Grid Trading With Deep Reinforcement Learning -- Chapter 6. Exploring Leading Practices in Algorithmic Trading: Insights From Survey and Case Studies on Machine Learning Techniques and Market Dynamics -- Chapter 7. Innovative Applications and Advanced Practices in Financial Data Science and Machine Learning for High-Frequency Trading -- Section 3. Data Analytics and AI in Financial Processes -- Chapter 8. A Review of Current Applications of AI and Machine Learning Methods for Financial Statement Analysis -- Chapter 9. Enhancing Audit Effectiveness Through Strategic Data Analytics -- Chapter 10. Artificial Intelligence-Based Capital Structure Management: A Comparative Analysis of Sectoral Dynamics of Leverage -- Chapter 11. AI-Driven Credit Assessment in Banks and Non-Banking Finance Companies (NBFCs) in India: A Comprehensive Analysis -- Section 4. Applications in Financial Market Forecasting and Strategy Optimization -- Chapter 12. From Chart to Chart: Analyzing Lyric Content in Music Streaming Charts for Predicting Stock Prices Using LSTM -- Chapter 13. Machine Learning for Price Prediction and Risk-Adjusted Portfolio Optimization in Cryptocurrencies -- Chapter 14. Evaluating the Effectiveness of Optimized LSTM and XGBoost Classifiers in High-Frequency Futures Market Prediction -- Chapter 15. Exploring Dynamic Volatility Transmission in Canadian and Global Financial Markets -- Section 5. Natural Language Processing for Finance -- Chapter 16. Natural Language Processing in Finance: Techniques, Applications, and Future Directions -- Section 6. Advancements and Future Research -- Chapter 17. Exploring Quantum Challenges and Opportunities of Quantum Machine Learning Adoption in Finance -- Chapter 18. Machine Learning for Financial Data Forecasting: Deep Learning-Powered Scientometric Analysis -- Compilation of References -- About the Contributors -- Index.

"This book aims to provide an updated review and showcase recent theoretical advances and breakthroughs in professional practices within financial data science, exploring the strategic roles of machine learning and modeling techniques across various domains in finance"--

Mode of access: World Wide Web.

ISBN: 9798369381885Subjects--Topical Terms:

557653
Finance
--Mathematical models.Subjects--Index Terms:

Algorithmic Trading.Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: HG106 / .M325 2025eb

Dewey Class. No.: 332.01/5195

Machine learning and modeling techniques in financial data science
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245 0 0 $a Machine learning and modeling techniques in financial data science $h [electronic resource] / $c Haojun Chen, editor.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2025.
300 $a 1 online resource (xxiv, 547 p.) : $b ill.
504 $a Includes bibliographic references and index.
505 0 $a Preface -- Section 1. ESG, Sustainability, and Fairness in AI for Financial Services -- Chapter 1. Fairness and Bias in Machine Learning Models for Credit Decisions -- Chapter 2. From Fintech to Green Fintech: How to Decarbonize theAI in the Financial Domain -- Chapter 3. Regulatory Challenges and Compliance in Decentralized Finance (DeFi): Comparative Study Between India and USA -- Section 2. Advances in AI and Machine Learning for Algorithmic and High-Frequency Trading -- Chapter 4. Revolutionizing High-Frequency Trading: The Impacts of Financial Technology and Data Science Innovations -- Chapter 5. Robo-Traders and PPO: Advancing Grid Trading With Deep Reinforcement Learning -- Chapter 6. Exploring Leading Practices in Algorithmic Trading: Insights From Survey and Case Studies on Machine Learning Techniques and Market Dynamics -- Chapter 7. Innovative Applications and Advanced Practices in Financial Data Science and Machine Learning for High-Frequency Trading -- Section 3. Data Analytics and AI in Financial Processes -- Chapter 8. A Review of Current Applications of AI and Machine Learning Methods for Financial Statement Analysis -- Chapter 9. Enhancing Audit Effectiveness Through Strategic Data Analytics -- Chapter 10. Artificial Intelligence-Based Capital Structure Management: A Comparative Analysis of Sectoral Dynamics of Leverage -- Chapter 11. AI-Driven Credit Assessment in Banks and Non-Banking Finance Companies (NBFCs) in India: A Comprehensive Analysis -- Section 4. Applications in Financial Market Forecasting and Strategy Optimization -- Chapter 12. From Chart to Chart: Analyzing Lyric Content in Music Streaming Charts for Predicting Stock Prices Using LSTM -- Chapter 13. Machine Learning for Price Prediction and Risk-Adjusted Portfolio Optimization in Cryptocurrencies -- Chapter 14. Evaluating the Effectiveness of Optimized LSTM and XGBoost Classifiers in High-Frequency Futures Market Prediction -- Chapter 15. Exploring Dynamic Volatility Transmission in Canadian and Global Financial Markets -- Section 5. Natural Language Processing for Finance -- Chapter 16. Natural Language Processing in Finance: Techniques, Applications, and Future Directions -- Section 6. Advancements and Future Research -- Chapter 17. Exploring Quantum Challenges and Opportunities of Quantum Machine Learning Adoption in Finance -- Chapter 18. Machine Learning for Financial Data Forecasting: Deep Learning-Powered Scientometric Analysis -- Compilation of References -- About the Contributors -- Index.
520 3 $a "This book aims to provide an updated review and showcase recent theoretical advances and breakthroughs in professional practices within financial data science, exploring the strategic roles of machine learning and modeling techniques across various domains in finance"-- $c Provided by publisher.
538 $a Mode of access: World Wide Web.
650 0 $a Finance $x Mathematical models. $3 557653
650 0 $a Machine learning. $3 561253
653 $a Algorithmic Trading.
653 $a Artificial Intelligence (AI)
653 $a Capital Structure Management.
653 $a Credit Assessment.
653 $a Credit Decisions.
653 $a Decentralized Finance (DeFi)
653 $a Deep Learning.
653 $a Deep Reinforcement Learning.
653 $a Financial Data Science.
653 $a Financial Technology (FinTech)
653 $a Global Financial Markets.
653 $a Grid Trading.
653 $a High-Frequency Trading.
653 $a Machine Learning.
653 $a Modeling Techniques.
653 $a Natural Language Processing (NLP)
653 $a Non-Banking Finance Companies (NBFCs)
655 4 $a Electronic books. $2 local $3 554714
700 1 $a Chen, Haojun, $d 1980- $3 1498683
710 2 $a IGI Global. $3 805187
776 0 8 $i Print version: $z 9798369381861
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8186-1