Quantitative Investment Analysis, 4/e (Hardocver)
暫譯: 量化投資分析(第4版,精裝本)
CFA Institute
- 出版商: Wiley
- 出版日期: 2020-09-16
- 定價: $1,560
- 售價: 9.8 折 $1,529
- 語言: 英文
- 頁數: 944
- ISBN: 1119743621
- ISBN-13: 9781119743620
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相關主題
商品描述
本書序言
We are pleased to bring you Quantitative Investment Analysis, Fourth Edition, which focuses on key tools that are needed for today's professional investor. In addition to classic areas such as the time value of money and probability and statistics, the text covers advanced concepts in regression, time series, machine learning, and big data projects. The text teaches critical skills that challenge many professionals, and shows how these techniques can be applied to areas such as factor modeling, risk management, and backtesting and simulation.
The content was developed in partnership by a team of distinguished academics and practitioners, chosen for their acknowledged expertise in the field, and guided by CFA Institute. It is written specifically with the investment practitioner in mind and is replete with examples and practice problems that reinforce the learning outcomes and demonstrate real-world applicability.
The CFA Program Curriculum, from which the content of this book was drawn, is subjected to a rigorous review process to assure that it is:
• Faithful to the findings of our ongoing industry practice analysis
• Valuable to members, employers, and investors
• Globally relevant
• Generalist (as opposed to specialist) in nature
• Replete with sufficient examples and practice opportunities
• Pedagogically sound
The accompanying workbook is a useful reference that provides Learning Outcome Statements that describe exactly what readers will learn and be able to demonstrate after mastering the accompanying material. Additionally, the workbook has summary overviews and practice problems for each chapter.
We are confident that you will find this and other books in the CFA Institute Investment Series helpful in your efforts to grow your investment knowledge, whether you are a relatively new entrant or an experienced veteran striving to keep up to date in the ever-changing market environment. CFA Institute, as a long-term committed participant in the investment profession and a not-for-profit global membership association, is pleased to provide you with this opportunity.
本書特色
Whether you are a novice investor or an experienced practitioner, Quantitative Investment Analysis, Fourth Edition has something for you. Part of the CFA Institute Investment Series, this authoritative guide is relevant the world over and will facilitate your mastery of quantitative methods and their application in today's investment process.
This updated edition provides all the statistical tools and latest information you need to be a confident and knowledgeable investor. This edition expands coverage to Machine Learning algorithms and the role of Big Data in an investment context along with capstone chapters in applying these techniques to factor modeling, risk management and backtesting and simulation in investment strategies. The authors go to great lengths to ensure an even treatment of subject matter, consistency of mathematical notation, and continuity of topic coverage that is critical to the learning process. Well suited for motivated individuals who learn on their own, as well as general reference, this complete resource delivers clear, example -driven coverage of a wide range of quantitative methods. Inside you'll find:
• Learning outcome statements (LOS) specifying the objective of each chapter
• A diverse variety of investment-oriented examples both aligned with the LOS and reflecting the realities of today's investment world
• A wealth of practice problems, charts, tables, and graphs to clarify and reinforce the concepts and tools of quantitative investment management
Sharpen your skills by furthering your hands-on experience with the Quantitative Investment Analysis Workbook, Fourth Edition-an essential guide, containing learning outcomes and summary over view sections, along with challenging problems and solutions.
商品描述(中文翻譯)
本書序言
我們很高興為您帶來《量化投資分析》第四版,該書專注於當今專業投資者所需的關鍵工具。除了經典領域如貨幣的時間價值、概率和統計外,文本還涵蓋了回歸分析、時間序列、機器學習和大數據項目等先進概念。該書教授許多專業人士面臨的關鍵技能,並展示這些技術如何應用於因子建模、風險管理以及回測和模擬等領域。
本書內容由一組傑出的學者和實務專家合作開發,他們在該領域的專業知識得到廣泛認可,並在CFA協會的指導下進行。書中專門針對投資實務者撰寫,並充滿了強化學習成果的範例和練習題,展示其在現實世界中的應用。
本書內容來源於CFA課程大綱,該大綱經過嚴格的審查過程,以確保其:
• 忠實於我們持續的行業實踐分析結果
• 對會員、雇主和投資者有價值
• 在全球範圍內具有相關性
• 本質上是通才(而非專才)
• 充滿足夠的範例和練習機會
• 教學上是合理的
附帶的工作簿是一個有用的參考,提供學習成果聲明,準確描述讀者在掌握附帶材料後將學到的內容和能夠展示的能力。此外,工作簿還為每一章提供了摘要概述和練習題。
我們相信,無論您是相對新手還是努力跟上不斷變化的市場環境的經驗豐富的老手,您都會發現本書及CFA協會投資系列中的其他書籍對於增進您的投資知識非常有幫助。CFA協會作為投資專業的長期參與者和非營利全球會員協會,樂於為您提供這個機會。
本書特色
無論您是新手投資者還是經驗豐富的實務者,《量化投資分析》第四版都能為您提供幫助。作為CFA協會投資系列的一部分,這本權威指南在全球範圍內都具有相關性,將促進您掌握量化方法及其在當今投資過程中的應用。
本更新版提供了您成為自信且知識淵博的投資者所需的所有統計工具和最新資訊。本版擴展了對機器學習算法和大數據在投資背景中角色的涵蓋,並包含了將這些技術應用於因子建模、風險管理以及投資策略中的回測和模擬的總結章節。作者竭盡所能確保主題的均衡處理、數學符號的一致性以及對學習過程至關重要的主題涵蓋的連貫性。本書非常適合那些自學的積極個體,也可作為一般參考,這本完整的資源提供了清晰、以範例為驅動的廣泛量化方法的涵蓋。在書中,您將找到:
• 每章的學習成果聲明(LOS),具體說明每章的目標
• 與學習成果聲明相一致且反映當今投資世界現實的多樣化投資導向範例
• 大量的練習題、圖表、表格和圖形,以澄清和強化量化投資管理的概念和工具
通過進一步的實踐經驗來提升您的技能,使用《量化投資分析工作簿》第四版——這是一本必備指南,包含學習成果和摘要概述部分,以及具有挑戰性的問題和解答。
目錄大綱
Chapter 1 The Time Value of Money
Chapter 2 Organizing, Visualizing, and Describing Data
Chapter 3 Probability Concepts
Chapter 4 Common Probability Distributions
Chapter 5 Sampling and Estimation
Chapter 6 Hypothesis Testing
Chapter 7 Introduction to Linear Regression
Chapter 8 Multiple Regression
Chapter 9 Time-Series Analysis
Chapter 10 Machine Learning
Chapter 11 Big Data Projects
Chapter 12 Using Multifactor Models
Chapter 13 Measuring and Managing Market Risk
Chapter 14 Backtesting and Simulation
目錄大綱(中文翻譯)
Chapter 1 The Time Value of Money
Chapter 2 Organizing, Visualizing, and Describing Data
Chapter 3 Probability Concepts
Chapter 4 Common Probability Distributions
Chapter 5 Sampling and Estimation
Chapter 6 Hypothesis Testing
Chapter 7 Introduction to Linear Regression
Chapter 8 Multiple Regression
Chapter 9 Time-Series Analysis
Chapter 10 Machine Learning
Chapter 11 Big Data Projects
Chapter 12 Using Multifactor Models
Chapter 13 Measuring and Managing Market Risk
Chapter 14 Backtesting and Simulation