Advances in Statistical Modeling and Financial Machine Learning
暫譯: 統計建模與金融機器學習的最新進展

Dar, Amir Ahmad, Khan, Mohammad Shahfaraz, Alam, Naushad

Advances in Statistical Modeling and Financial Machine Learning

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商品描述

The interplay between mathematics, finance, and technology is becoming increasingly intricate and vital in today's rapidly evolving world. This book explores this complex relationship, offering a thorough examination of advanced theories, models, and applications that are shaping the future across these interconnected fields. The chapters have been curated to reflect the diversity of current research and its practical implications, providing readers with a deeper understanding of both foundational concepts and innovative developments.

Divided into three sections, Advances in Statistical Modeling and Financial Machine Learning offers studies in foundations and developments in mathematical and statistical models, mathematical models in finance and emerging technological impacts, and control systems, fuzzy logic, and decision-making in complex environments.

The book begins with an exploration of queuing models, a fundamental area of operations research, which, while theoretical, has real-world applications in various industries, including telecommunications, healthcare, and retail, where managing customer flow and service time is essential for operational success. The book looks into the realm of statistical inference, focusing on stress-strength reliability measures, important in the fields of engineering, manufacturing, and quality control, providing valuable insights into risk assessment. A comparative study of exponentiated distributions is presented, highlighting the importance of selecting the appropriate statistical distribution to model data accurately, a decision that can significantly impact the outcomes of research and analysis.

The volume also looks at the transformative effects of the Fintech revolution, which is redefining how banking and finance operate, creating new opportunities for innovation while also presenting significant challenges. Chapters explore the impact of Fintech on traditional banking models, mathematical models for option pricing, the growing influence of machine learning in education, using data-driven strategies for stock price prediction.

Several novel modeling systems are discussed, such as using exponential weighted moving average control charts, smart decision-making with Pythagorean fuzzy sets in granular uncertainty, generalized uncertainty principles for Wigner-Ville distribution associated with the quaternion linear canonical transform, and fixed points in ordered metric spaces.

Offering a holistic view of the advancements in mathematics, finance, and technology, this volume will inspire new ideas and foster a deeper understanding of the intricate relationships that define these fields. By integrating advanced theoretical concepts with their practical applications, it offers a well-rounded understanding of the challenges and opportunities that characterize these fields today.

商品描述(中文翻譯)

數學、金融與科技之間的相互作用，在今日快速演變的世界中變得日益複雜且至關重要。本書探討這種複雜關係，全面檢視正在形塑這些相互連結領域未來的進階理論、模型與應用。本書各章經過精心編排，反映當前研究的多樣性及其實務意涵，協助讀者深入理解基礎概念與創新發展。

《統計建模與金融機器學習的進展》分為三個部分，內容涵蓋數學與統計模型的基礎及發展、金融中的數學模型與新興科技所帶來的影響，以及複雜環境中的控制系統、模糊邏輯與決策制定。

本書首先探討排隊模型（queuing models）。這是作業研究中的基礎領域，雖然具有理論性，卻廣泛應用於電信、醫療保健與零售等產業。在這些領域中，有效管理顧客流量與服務時間，是維持營運成功的關鍵。本書接著深入探討統計推論，聚焦於應力–強度可靠度衡量（stress-strength reliability measures）；這類方法在工程、製造與品質控制領域中十分重要，能為風險評估提供有價值的洞見。此外，本書也呈現冪次化分布（exponentiated distributions）的比較研究，凸顯選擇適當統計分布以準確建模資料的重要性；這項決策可能對研究與分析結果產生重大影響。

本書也探討 Fintech 革命所帶來的變革性影響。這場革命正在重新定義銀行業與金融業的運作方式，在創造創新機會的同時，也帶來重大的挑戰。相關章節探討 Fintech 對傳統銀行模型的影響、選擇權定價的數學模型、機器學習在教育領域日益增長的影響力，以及運用資料驅動策略預測股價的方法。

書中討論了多種新穎的建模系統，例如使用指數加權移動平均控制圖（exponential weighted moving average control charts）、在粒狀不確定性（granular uncertainty）下運用畢氏模糊集合（Pythagorean fuzzy sets）進行智慧決策、與四元數線性典範變換（quaternion linear canonical transform）相關之 Wigner–Ville 分布的廣義不確定性原理，以及有序度量空間（ordered metric spaces）中的不動點（fixed points）。

本書全面呈現數學、金融與科技領域的發展，將啟發新的思維，並促進讀者深入理解定義這些領域的複雜關係。透過整合進階理論概念與實務應用，本書提供對當今形塑這些領域之挑戰與機會的完整理解。

作者簡介

Amir Ahmad Dar, PhD, is currently serving as an Assistant Professor in the Department of Statistics at Lovely Professional University in India. Dr. Dar has an impressive academic portfolio, having published over 20 research papers and 10 book chapters. He has presented his work at eight national and international conferences. His research interests include actuarial statistics, experimental design, financial derivatives, and financial mathematics. He completed his BSc in Actuarial and Financial Mathematics at the Islamic University of Science and Technology in Awantipora, India. He pursued his MSc and PhD in Actuarial Science at B S Abdur Rahman University in Chennai, India.

Mohammad Shahfaraz Khan, PhD is the Assistant Professor (Finance and Accounting) in the Department of Business Administration in the College of Economics and Business Administration at the University of Technology and Applied Sciences (UTAS) (formerly College of Applied Sciences, Salalah), Salalah, Sultanate of Oman. He earned his PhD from Aligarh Muslim University (AMU), India, and also did his bachelor's (Commerce) and master's in Finance & Control (MFC) at the same university. He is a gold medalist for his postgraduation (MFC) work and qualified national eligibility test for lecturership. He has published several papers in the field of finance and accounting, and his areas of interest in research is foreign direct investment (FDI), stock market, investment management, fintech, banking and finance, Islamic banking, and behavioral finance.

Naushad Alam, PhD, is currently working in the Department of Finance and Economics at Dhofar University, Oman. He earned his Master of Finance and Control and PhD in Finance from Aligarh Muslim University, India. He has more than 10 years of teaching and research experience and has published research paper in journals with impact factors. He formerly worked at the GL Bajaj Institute of Management Research, India, and at Saudi Electronic University, Saudi Arabia.

Olayan Albalawi, PhD, is an Assistant Professor in the Department of Statistics in the Faculty of Science at the University of Tabuk, Saudi Arabia. He holds a PhD in Applied Statistics from the University of New South Wales, Australia, as well as a Masters of Statistics from the University of New Mexico, USA. Additionally, he obtained a master's degree in Mathematical Science from the University of Queensland of Technology. He serves as a reviewer for the King Saud of Science Journal.

作者簡介(中文翻譯)

Amir Ahmad Dar 博士目前任職於印度 Lovely Professional University 統計學系，擔任助理教授。Dar 博士學術成果豐碩，已發表超過 20 篇研究論文及 10 篇書籍章節，並曾在 8 場國內及國際會議中發表研究成果。他的研究興趣包括精算統計、實驗設計、金融衍生工具及金融數學。他於印度 Awantipora 的 Islamic University of Science and Technology 取得精算與金融數學學士學位，並於印度 Chennai 的 B S Abdur Rahman University 攻讀精算學碩士及博士學位。

Mohammad Shahfaraz Khan 博士是阿曼蘇丹國 Salalah 的 University of Technology and Applied Sciences（UTAS，前身為 College of Applied Sciences, Salalah）經濟與企業管理學院企業管理系的助理教授（財務與會計）。他於印度 Aligarh Muslim University（AMU）取得博士學位，並在同一所大學完成商學學士學位及財務與控制碩士學位（MFC）。他在研究所階段的 MFC 學業中獲得金牌，並通過國家講師資格考試。他已在財務與會計領域發表多篇論文，研究興趣包括外國直接投資（FDI）、股票市場、投資管理、金融科技、銀行與金融、伊斯蘭銀行及行為財務。

Naushad Alam 博士目前任職於阿曼 Dhofar University 財務與經濟系。他於印度 Aligarh Muslim University 取得財務與控制碩士學位及財務博士學位。他擁有超過 10 年的教學與研究經驗，並已在具影響因子期刊上發表研究論文。他曾任職於印度的 GL Bajaj Institute of Management Research，以及沙烏地阿拉伯的 Saudi Electronic University。

Olayan Albalawi 博士是沙烏地阿拉伯 University of Tabuk 科學學院統計學系的助理教授。他擁有澳洲 University of New South Wales 的應用統計博士學位，以及美國 University of New Mexico 的統計學碩士學位。此外，他也取得 University of Queensland of Technology 的數學科學碩士學位。他擔任 King Saud of Science Journal 的審稿人。

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