Data Analytics for Finance Using Python (金融數據分析:使用Python)

Untwal, Nitin Jaglal, Kose, Utku

  • 出版商: CRC
  • 出版日期: 2024-12-30
  • 售價: $4,820
  • 貴賓價: 9.5$4,579
  • 語言: 英文
  • 頁數: 121
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1032618213
  • ISBN-13: 9781032618210
  • 相關分類: Python程式語言Data Science
  • 尚未上市,無法訂購

相關主題

商品描述

Unlock the power of data analytics in finance with this comprehensive guide. Data Analytics for Finance Using Python is your key to unlocking the secrets of the financial markets.

In this book, you'll discover how to harness the latest data analytics techniques, including machine learning and inferential statistics, to make informed investment decisions and drive business success. With a focus on practical application, this book takes you on a journey from the basics of data preprocessing and visualization to advanced modeling techniques for stock price prediction.

Through real-world case studies and examples, you'll learn how to:

  • Uncover hidden patterns and trends in financial data
  • Build predictive models that drive investment decisions
  • Optimize portfolio performance using data-driven insights
  • Stay ahead of the competition with cutting-edge data analytics techniques

Whether you're a finance professional seeking to enhance your data analytics skills or a researcher looking to advance the field of finance through data-driven insights, this book is an essential resource. Dive into the world of data analytics in finance and discover the power to make informed decisions, drive business success, and stay ahead of the curve.

This book will be helpful for students, researchers, and users of machine learning and financial tools in the disciplines of commerce, management, and economics.

商品描述(中文翻譯)

解鎖金融數據分析的力量,這本全面的指南將是你的關鍵。《使用 Python 的金融數據分析》將揭示金融市場的秘密。

在這本書中,你將發現如何利用最新的數據分析技術,包括機器學習和推論統計,來做出明智的投資決策並推動商業成功。這本書專注於實際應用,帶你從數據預處理和可視化的基礎知識,進入股票價格預測的高級建模技術。

透過真實案例研究和範例,你將學會如何:
- 發現金融數據中的隱藏模式和趨勢
- 建立驅動投資決策的預測模型
- 利用數據驅動的見解優化投資組合表現
- 以尖端的數據分析技術保持競爭優勢

無論你是希望提升數據分析技能的金融專業人士,還是希望透過數據驅動的見解推進金融領域的研究者,這本書都是一個必備資源。深入探索金融數據分析的世界,發現做出明智決策、推動商業成功和保持領先的力量。

這本書將對商業、管理和經濟學科的學生、研究者以及機器學習和金融工具的使用者有所幫助。

作者簡介

Nitin Jaglal Untwal, PhD, is a distinguished scholar and educator in the field of finance, with a remarkable academic background and research expertise. Holding a doctorate in finance and master's degrees in related fields like commerce, management, and econometrics, he has established himself as a prominent authority in financial data analytics, technology management, and econometrics modeling. With over 11 years of experience in teaching and research, Dr. Untwal has published numerous papers in esteemed databases like Scopus and Web of Science, solidifying his reputation as a leading researcher in his field. Recognized as a postgraduate faculty member by the S.P. University of Pune since 2008, he has also achieved success in prestigious eligibility tests, including UGC-SET in Management and State Eligibility Test Commerce. Additionally, he has completed a Faculty Development Program from the Indian Institute of Management, Kozhikode (IIM-K). Dr. Untwal's wealth of knowledge and experience make him an invaluable contributor to this book.

Utku Kose, PhD, a distinguished scholar in computer science and engineering, joins Dr. Untwal in this literary endeavor. With over 200 publications to his name, Dr. Kose has demonstrated his expertise in artificial intelligence, machine ethics, biomedical applications, and more. His impressive academic background and extensive research experience make him a significant contributor to this book.

作者簡介(中文翻譯)

Nitin Jaglal Untwal博士是一位在金融領域享有盛譽的學者和教育工作者,擁有卓越的學術背景和研究專長。他擁有金融學博士學位以及商業、管理和計量經濟學等相關領域的碩士學位,已在金融數據分析、技術管理和計量經濟模型方面建立了自己的權威地位。擁有超過11年的教學和研究經驗,Untwal博士在Scopus和Web of Science等知名數據庫上發表了多篇論文,鞏固了他在該領域的領先研究者聲譽。自2008年以來,他被普納S.P.大學認可為研究生教員,並在包括管理學的UGC-SET和商業的州資格考試等多項著名資格考試中取得成功。此外,他還完成了印度管理學院科澤科德分校(IIM-K)的教員發展計劃。Untwal博士的豐富知識和經驗使他成為本書的重要貢獻者。

Utku Kose博士是一位在計算機科學和工程領域的傑出學者,與Untwal博士共同參與這項文學工作。Kose博士擁有超過200篇的出版物,展現了他在人工智慧、機器倫理、生物醫學應用等領域的專業知識。他令人印象深刻的學術背景和廣泛的研究經驗使他成為本書的重要貢獻者。