東華大學圖書館 |

Data analytics and AI for quantitative risk assessment and financial computation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data analytics and AI for quantitative risk assessment and financial computation/ Mohammad Gouse Galety, Jimbo Henri Claver, A.V. Sriharsha, Narasimha Rao Vajjhala, Arul Kumar Natarajan, editors.
其他題名:	Data analytics and artificial intelligence for quantitative risk assessment and financial computation
其他作者:	Natarajan, Arul Kumar.
出版者:	Hershey, Pennsylvania :IGI Global, : 2025.,
面頁冊數:	1 online resource (xxix, 610 p.) :ill.
內容註:	Preface -- Chapter 1. Foundations of AI and Machine Learning in Real Estate Valuation: An Analysis Using the California Housing Prices Dataset With Python Implementations -- Chapter 2. AI Innovations in Market Risk Analysis and VaR Modelling -- Chapter 3. Predictive Modeling in Finance: Harnessing Machine Learning Algorithms for Enhanced Decision Making -- Chapter 4. Financial Modelling 2.0: The Machine Learning Transformation -- Chapter 5. Predicting Exchange Rates Volatility Using Hybrid ARIMA-GARCH Model: A Comparative Analysis -- Chapter 6. Datalyse: Integrating Statistics and Computation for Streamlined Financial Data Analysis, Linear Model Building, and Time Series Analysis -- Chapter 7. Comparingthe Exact and Approximate Solutions of Financial-Type Stochastic Differential Equations -- Chapter 8. Ito's Calculus for Stock Price Prediction for the Johannesburg Stock Exchange Market -- Chapter 9. Diving Into the Performance of Supervised Learning Models for Forecasting the Indian Stock Market: A Case Study -- Chapter 10. Novel Applications of Data Analytics in Financial Markets: A Review and Exploration of Predictive Power -- Chapter 11. Random Matrix Approach for Analysis of the Johannesburg Stock Exchange -- Chapter 12. Selection and Analysis of Optimized Portfolio Sectors of Johannesburg Stock Markets -- Chapter 13. A Network-Based Approach to the Implications of the COVID-19 Pandemic on the Latin American Minimum Variance Portfolio -- Chapter 14. Statistical Optimization of Option Pricing Factors: Application of Taguchi's DOE -- Chapter 15. Charting the Ethical Landscape: A Holistic Examination of AI Ethics and Bias in the Financial Sector -- Chapter 16. The Ascending AI Era: Rerouting the Bubble Discourse -- Chapter 17. The Future of Risk Management in Healthcare: The Role of Artificial Intelligence -- Chapter 18. The Future of HR Analytics Using Machine Learning to Predict and Improve Employee Performance: Optimizing Workforce Strategy Through Advanced Data Analysis -- Chapter 19. The Transformative Journey of Sustainable Finance in Global Markets -- Chapter 20. The Art of Digital Engagement: Mastering Social Media Marketing -- Compilation of References -- About the Contributors -- Index.
標題:	Risk assessment. -
電子資源:	https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-6215-0
ISBN:	9798369362174

Data analytics and AI for quantitative risk assessment and financial computation
Data analytics and AI for quantitative risk assessment and financial computation[electronic resource] /Data analytics and artificial intelligence for quantitative risk assessment and financial computationMohammad Gouse Galety, Jimbo Henri Claver, A.V. Sriharsha, Narasimha Rao Vajjhala, Arul Kumar Natarajan, editors. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (xxix, 610 p.) :ill. - Advances in computational intelligence and robotics (ACIR) book series. - Advances in computational intelligence and robotics (ACIR) book series..

Includes bibliographical references and index.

Preface -- Chapter 1. Foundations of AI and Machine Learning in Real Estate Valuation: An Analysis Using the California Housing Prices Dataset With Python Implementations -- Chapter 2. AI Innovations in Market Risk Analysis and VaR Modelling -- Chapter 3. Predictive Modeling in Finance: Harnessing Machine Learning Algorithms for Enhanced Decision Making -- Chapter 4. Financial Modelling 2.0: The Machine Learning Transformation -- Chapter 5. Predicting Exchange Rates Volatility Using Hybrid ARIMA-GARCH Model: A Comparative Analysis -- Chapter 6. Datalyse: Integrating Statistics and Computation for Streamlined Financial Data Analysis, Linear Model Building, and Time Series Analysis -- Chapter 7. Comparingthe Exact and Approximate Solutions of Financial-Type Stochastic Differential Equations -- Chapter 8. Ito's Calculus for Stock Price Prediction for the Johannesburg Stock Exchange Market -- Chapter 9. Diving Into the Performance of Supervised Learning Models for Forecasting the Indian Stock Market: A Case Study -- Chapter 10. Novel Applications of Data Analytics in Financial Markets: A Review and Exploration of Predictive Power -- Chapter 11. Random Matrix Approach for Analysis of the Johannesburg Stock Exchange -- Chapter 12. Selection and Analysis of Optimized Portfolio Sectors of Johannesburg Stock Markets -- Chapter 13. A Network-Based Approach to the Implications of the COVID-19 Pandemic on the Latin American Minimum Variance Portfolio -- Chapter 14. Statistical Optimization of Option Pricing Factors: Application of Taguchi's DOE -- Chapter 15. Charting the Ethical Landscape: A Holistic Examination of AI Ethics and Bias in the Financial Sector -- Chapter 16. The Ascending AI Era: Rerouting the Bubble Discourse -- Chapter 17. The Future of Risk Management in Healthcare: The Role of Artificial Intelligence -- Chapter 18. The Future of HR Analytics Using Machine Learning to Predict and Improve Employee Performance: Optimizing Workforce Strategy Through Advanced Data Analysis -- Chapter 19. The Transformative Journey of Sustainable Finance in Global Markets -- Chapter 20. The Art of Digital Engagement: Mastering Social Media Marketing -- Compilation of References -- About the Contributors -- Index.

"In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape."--

Mode of access: World Wide Web.

ISBN: 9798369362174Subjects--Topical Terms:

543512
Risk assessment.
Subjects--Index Terms:

AI Ethics and Bias in Financial Models.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HD61 / .D38 2025eb

Dewey Class. No.: 658.155

Data analytics and AI for quantitative risk assessment and financial computation
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246 3 $a Data analytics and artificial intelligence for quantitative risk assessment and financial computation
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2025.
300 $a 1 online resource (xxix, 610 p.) : $b ill.
490 1 $a Advances in computational intelligence and robotics (ACIR) book series
504 $a Includes bibliographical references and index.
505 0 $a Preface -- Chapter 1. Foundations of AI and Machine Learning in Real Estate Valuation: An Analysis Using the California Housing Prices Dataset With Python Implementations -- Chapter 2. AI Innovations in Market Risk Analysis and VaR Modelling -- Chapter 3. Predictive Modeling in Finance: Harnessing Machine Learning Algorithms for Enhanced Decision Making -- Chapter 4. Financial Modelling 2.0: The Machine Learning Transformation -- Chapter 5. Predicting Exchange Rates Volatility Using Hybrid ARIMA-GARCH Model: A Comparative Analysis -- Chapter 6. Datalyse: Integrating Statistics and Computation for Streamlined Financial Data Analysis, Linear Model Building, and Time Series Analysis -- Chapter 7. Comparingthe Exact and Approximate Solutions of Financial-Type Stochastic Differential Equations -- Chapter 8. Ito's Calculus for Stock Price Prediction for the Johannesburg Stock Exchange Market -- Chapter 9. Diving Into the Performance of Supervised Learning Models for Forecasting the Indian Stock Market: A Case Study -- Chapter 10. Novel Applications of Data Analytics in Financial Markets: A Review and Exploration of Predictive Power -- Chapter 11. Random Matrix Approach for Analysis of the Johannesburg Stock Exchange -- Chapter 12. Selection and Analysis of Optimized Portfolio Sectors of Johannesburg Stock Markets -- Chapter 13. A Network-Based Approach to the Implications of the COVID-19 Pandemic on the Latin American Minimum Variance Portfolio -- Chapter 14. Statistical Optimization of Option Pricing Factors: Application of Taguchi's DOE -- Chapter 15. Charting the Ethical Landscape: A Holistic Examination of AI Ethics and Bias in the Financial Sector -- Chapter 16. The Ascending AI Era: Rerouting the Bubble Discourse -- Chapter 17. The Future of Risk Management in Healthcare: The Role of Artificial Intelligence -- Chapter 18. The Future of HR Analytics Using Machine Learning to Predict and Improve Employee Performance: Optimizing Workforce Strategy Through Advanced Data Analysis -- Chapter 19. The Transformative Journey of Sustainable Finance in Global Markets -- Chapter 20. The Art of Digital Engagement: Mastering Social Media Marketing -- Compilation of References -- About the Contributors -- Index.
520 3 $a "In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape."-- $c Provided by publisher.
538 $a Mode of access: World Wide Web.
650 0 $a Risk assessment. $3 543512
650 0 $a Financial engineering. $3 550926
650 0 $a Evolutionary computation. $3 582189
650 0 $a Quantitative research. $3 919734
650 0 $a Artificial intelligence. $3 516317
653 $a AI Ethics and Bias in Financial Models.
653 $a Algorithmic Trading and High-Frequency Trading (HFT)
653 $a Artificial Intelligence and Beyond.
653 $a Big Data Technologies in Finance.
653 $a Blockchain and Cryptocurrencies Risk Assessment.
653 $a Credit Risk Modeling and Assessment.
653 $a Derivative Pricing.
653 $a Fundamentals of Data Analytics and AI.
653 $a Liquidity Risk Measurement and Management.
653 $a Machine Learning Algorithms for Financial Modeling.
653 $a Market Risk Analysis and Value at Risk (VaR) Models.
653 $a Natural Language Processing (NLP) in Financial Analysis.
653 $a Operational Risk Management.
653 $a Portfolio Optimization and Asset Allocation.
653 $a Probability Theory and Statistical Analysis for Risk Assessment.
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Natarajan, Arul Kumar. $3 3793215
700 1 $a Vajjhala, Narasimha Rao. $3 2093201
700 1 $a Claver, Jimbo Henri. $3 3793303
700 1 $a Galety, Mohammad Gouse, $d 1976- $3 3793230
700 1 $a Sriharsha, A. V. $3 3793304
710 2 $a IGI Global. $3 1361470
776 0 8 $i Print version: $z 9798369362150
830 0 $a Advances in computational intelligence and robotics (ACIR) book series. $3 3311060
856 4 0 $u https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-6215-0