Call for Chapters: Machine Learning and Modeling Techniques in Financial Data Science

Editors

Haojun Chen, Guangzhou Huali College, International School, China

Call for Chapters

Proposals Submission Deadline: September 1, 2024
Full Chapters Due: October 13, 2024
Submission Date: October 13, 2024

Introduction

In the realm of modern finance, the application of machine learning and modeling techniques has become pivotal for gaining insights, making informed decisions, and optimizing outcomes. This book aims to explore the cutting-edge methodologies and empirical research findings in the field of financial data science. It seeks to bridge theoretical frameworks with practical applications, catering to professionals keen on advancing their expertise in utilizing these techniques effectively.

Objective

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. Featuring articles by esteemed scholars and experts, it offers a comprehensive collection that brings together a wealth of knowledge and experience. Readers will gain a thorough understanding of the current landscape and future directions in financial data science. This compilation serves as an essential resource for researchers, practitioners, and students looking to delve into cutting-edge methodologies and their practical applications in today's financial markets.

Target Audience

The intended audience for this book includes professionals and researchers working in finance, economics, business analytics, and related fields. We also aim to reach executives, data scientists, and technologists involved in financial decision-making processes. Additionally, this book will serve as a valuable resource for educators and students pursuing studies in finance and data science. Please note: Each chapter should focus on a specific, narrow topic and provide in-depth, advanced, and front-running insights. General introductions to existing principles and applications are not suitable for this publication. However, critical reviews of existing literature in the field related to the topics of the book are welcomed and not considered general introductions. We encourage submissions that delve deeply into specialized areas, offer innovative research, and present cutting-edge methodologies.

Recommended Topics

We welcome topics in theory, innovative applications, and advanced practices in financial data science and machine learning related to the following areas: Asset Pricing, Financial Modeling, High-frequency Trading, Natural Language Processing in Finance, Deep Learning, Sentiment Analysis, Algorithmic Trading, Investment Strategies, Explainable AI in Financial Decisions, Blockchain and Cryptocurrency, Big Data, Ethical Considerations, Regulatory Challenges and Compliance, Fraud Detection, Financial Pattern Discoveries, Market Microstructure, Financial Anomalies and Market Predictability, Theories in Financial Data Science, Financial Statistics and Econometrics, Data Techniques, Quantitative Methods in Finance, Financial Risk management

Submission Procedure

Researchers and practitioners are invited to submit on or before September 1, 2024, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by September 5, 2024 about the status of their proposals and sent chapter guidelines.Full chapters are expected to be submitted by October 13, 2024, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Machine Learning and Modeling Techniques in Financial Data Science. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.



Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2025.



Important Dates

September 1, 2024: Proposal Submission Deadline
September 5, 2024: Notification of Acceptance
October 13, 2024: Full Chapter Submission
November 17, 2024: Review Results Returned
December 15, 2024: Final Acceptance Notification
December 22, 2024: Final Chapter Submission



Inquiries

Dr. Edwin Chen
Guangzhou Huali College, International School
ed@topfintech.org



Classifications


Business and Management; Computer Science and Information Technology; Library and Information Science; Social Sciences and Humanities; Physical Sciences and Engineering
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