Whether you are a novice investor or an experienced practitioner, Quantitative Investment Analysis, 4th 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 in the Quantitative Investment Analysis Workbook, 4th Edition–an essential guide containing learning outcomes and summary overview sections, along with challenging problems and solutions.
Table of Content
Preface
Acknowledgements
About the CFA Institute Investment Series
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
Appendices
Glossary
About the Authors
About the CFA Program
Index
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