Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications (機器學習與深度學習的創新金融應用：演算法、產品建模與應用)

Abedin, Mohammad Zoynul, Hajek, Petr

Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications

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商品描述

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study.

The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice.

The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

商品描述(中文翻譯)

本書介紹了機器學習在金融領域的最先進應用，重點在於金融產品建模，旨在提升模型性能並最小化風險與不確定性。它提供了金融與管理決策支持系統的實務與管理意涵，這些系統捕捉了廣泛的金融數據特徵。本書同時作為風險調整金融產品定價系統實施的指南，並為所研究的課題增添了重要的金融素養補充。

本書涵蓋了先進的機器學習技術，如支持向量機（Support Vector Machine）、神經網絡（Neural Networks）、隨機森林（Random Forest）、K-最近鄰（K-Nearest Neighbors）、極限學習機（Extreme Learning Machine）、深度學習方法（Deep Learning Approaches）及其在金融數據集上的應用。它還利用真實世界的金融實例來實踐商業產品建模和數據分析。書中包含了如MATLAB、Python和/或R等軟體代碼，以及涵蓋廣泛金融領域的數據集，以便進行更嚴謹的實踐。

本書主要旨在為研究生和研究人員提供金融數據分析的路線圖。它也適合廣泛的讀者，包括學術界、專業金融分析師和政策制定者，這些人員參與預測、建模、交易、風險管理、經濟學、信用風險和投資組合管理等領域。

作者簡介

Mohammad Zoynul Abedin is a Senior Lecturer in Fintech and Financial Innovation at Teesside University International Business School, Teesside University, UK. He received his B.B.A. and M.B.A. degrees in finance from the University of Chittagong, Bangladesh, and his D.Phil. degree in investment theory from the Dalian University of Technology, China. Dr. Abedin published more than 70 papers, including peer reviewed full length articles, conference papers, and book chapters. His work appears on the Annals of Operations Research, International Journal of Production Research, IEEE Transactions on Industrial Informatics, to mention a few. His current research interests include business data analytics, fintech, and computational finance. He is a fellow of the Financial Management Association (FMA), and British Accounting and Finance Association (BAFA).

Petr Hajek is a Professor at the Science and Research Centre, University of Pardubice, Czech Republic. He holds a Ph.D. degree in system engineering and informatics. Professor Hajek is the author or coauthor of 5 books and more than 70 articles in leading journals such as Information Sciences, Decision Support Systems, and Knowledge-Based Systems. His current research interests include business decision-making, soft computing, text mining, and knowledge-based systems. He is a fellow of the Association for Computing Machinery (ACM), KES International, and Association for Information Systems (AIS).

作者簡介(中文翻譯)

Mohammad Zoynul Abedin 是英國提賽德大學國際商學院的金融科技與金融創新高級講師。他在孟加拉的吉大港大學獲得了財務學的學士及碩士學位，並在中國大連理工大學獲得投資理論的博士學位。Abedin 博士已發表超過70篇論文，包括同行評審的完整文章、會議論文和書籍章節。他的研究成果發表於《Operations Research 年鑑》、《International Journal of Production Research》、《IEEE Transactions on Industrial Informatics》等期刊。他目前的研究興趣包括商業數據分析、金融科技和計算金融。他是金融管理協會（FMA）和英國會計與金融協會（BAFA）的會員。

Petr Hajek 是捷克帕爾杜比采大學科學與研究中心的教授。他擁有系統工程和資訊學的博士學位。Hajek 教授是5本書籍的作者或合著者，並在《Information Sciences》、《Decision Support Systems》和《Knowledge-Based Systems》等領先期刊上發表了超過70篇文章。他目前的研究興趣包括商業決策、軟計算、文本挖掘和知識基礎系統。他是計算機協會（ACM）、KES International 和資訊系統協會（AIS）的會員。

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