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Quantitative Investment Analysis / Edition 2

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Overview

As part of the CFA Institute Investment Series, the Second Edition of Quantitative Investment Analysis has been designed for a wide range of individuals, from graduate-level students focused on finance to practicing investment professionals. This globally relevant guide will help you understand quantitative methods and apply them to today's investment process.

In this latest edition, the distinguished team of Richard DeFusco, Dennis McLeavey, Jerald Pinto, and David Runkle update information associated with this discipline; improve the presentation and coverage of several major areas, including regression, time series, and multifactor models; and introduce an even greater variety of investment-oriented examples—which reflect the changes currently taking place in the investment community. Throughout the text, special attention is paid to ensuring the even treatment of subject matter, consistency of mathematical notation, and continuity of topic coverage that is so critical to the learning process.

Valuable for self-study and general reference, this book provides clear, example-driven coverage of a wide range of quantitative methods. Topics discussed include:

  • The time value of money
  • Discounted cash flow applications
  • Common probability distributions
  • Sampling and estimation
  • Hypothesis testing
  • Correlation and regression
  • Multiple regression and issues in regression analysis
  • Time-series analysis
  • Portfolio concepts

And to further enhance your understanding of the tools and techniques presented here, don't forget to pick up the Quantitative Investment Analysis Workbook, Second Edition—an essential guide containing learning outcomes and summary overview sections along with challenging problems and solutions.

With each author bringing his own unique experiences and perspectives to the table, the Second Edition of Quantitative Investment Analysis distills the knowledge, skills, and abilities you need to succeed in today's fast-paced financial environment. Filled with in-depth insights and practical advice, Quantitative Investment Analysis, Second Edition offers a comprehensive treatment of quantitative methods that combines best practices with solid theory.

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Product Details

  • ISBN-13: 9780470052204
  • Publisher: Wiley
  • Publication date: 1/16/2007
  • Series: CFA Institute Investment Series , #2
  • Edition description: Revised Edition
  • Edition number: 2
  • Pages: 600
  • Sales rank: 295,446
  • Product dimensions: 7.30 (w) x 9.96 (h) x 1.44 (d)

Meet the Author

RICHARD A. DEFUSCO, CFA, is an Associate Professor of Finance at the University of Nebraska-Lincoln (UNL). He earned his CFA charter in 1999. DeFusco is a member of the Omaha-Lincoln Society of Financial Analysts, and completed his bachelor's degree in management science at the University of Rhode Island and doctoral degree in finance at the University of Tennessee-Knoxville.

DENNIS W. MCLEAVEY, CFA, is Head of Professional Development Products at CFA Institute. During his twenty-five year academic career, he has taught at The University of Western Ontario, the University of Connecticut, the University of Rhode Island (where he founded a student-managed fund), and Babson College. McLeavey completed a doctorate in production management and industrial engineering at Indiana University in 1972, and earned his CFA charter in 1990.

JERALD E. PINTO, CFA, is Director in the CFA and CIPM Programs Division at CFA Institute. Before coming to CFA Institute in 2002, he consulted to corporations, foundations, and partnerships in investment planning, portfolio analysis, and quantitative analysis. He has also worked in the investment and banking industries in New York City and taught finance at New York University's Stern School of Business. He holds an MBA from Baruch College, a PhD in finance from the Stern School, and earned his CFA charter in 1992.

DAVID E. RUNKLE, CFA, is Vice President and Research Manager at U.S. Bancorp Piper Jaffray. He has been an adjunct professor of finance in the Carlson School of Management at the University of Minnesota since 1989. Runkle received a BA in economics from Carleton College and a PhD in economics from MIT.

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Table of Contents

Foreword xiii

Acknowledgments xvii

Introduction xix

CHAPTER 1 The Time Value of Money 1

1 Introduction 1

2 Interest Rates: Interpretation 1

3 The Future Value of a Single Cash Flow 3

4 The Future Value of a Series of Cash Flows 13

5 The Present Value of a Single Cash Flow 15

6 The Present Value of a Series of Cash Flows 19

7 Solving for Rates, Number of Periods, or Size of Annuity Payments 27

CHAPTER 2 Discounted Cash Flow Applications 39

1 Introduction 39

2 Net Present Value and Internal Rate of Return 39

3 Portfolio Return Measurement 47

34 Money Market Yields 54

CHAPTER 3 Statistical Concepts andMarket Returns 61

1 Introduction 61

2 Some Fundamental Concepts 61

3 Summarizing Data Using Frequency Distributions 65

4 The Graphic Presentation of Data 72

5 Measures of Central Tendency 76

6 Other Measures of Location: Quantiles 94

7 Measures of Dispersion 100

8 Symmetry and Skewness in Return Distributions 118

9 Kurtosis in Return Distributions 123

10 Using Geometric and Arithmetic Means 127

CHAPTER 4 Probability Concepts 129

1 Introduction 129

2 Probability, Expected Value, and Variance 129

3 Portfolio Expected Return and Variance of Return 152

4 Topics in Probability 161

CHAPTER 5 Common Probability Distributions 171

1 Introduction 171

2 Discrete Random Variables 171

3 Continuous Random Variables 185

4 Monte Carlo Simulation 206

CHAPTER 6 Sampling and Estimation 215

1 Introduction 215

2 Sampling 215

3 Distribution of the Sample Mean 221

4 Point and Interval Estimates of the Population Mean 225

5 More on Sampling 235

CHAPTER 7 Hypothesis Testing 243

1 Introduction 243

2 Hypothesis Testing 244

3 Hypothesis Tests Concerning the Mean 253

4 Hypothesis Tests Concerning Variance 269

5 Other Issues: Nonparametric Inference 275

CHAPTER 8 Correlation and Regression 281

1 Introduction 281

2 Correlation Analysis 281

3 Linear Regression 300

CHAPTER 9 Multiple Regression and Issues in Regression Analysis 325

1 Introduction 325

2 Multiple Linear Regression 325

3 Using Dummy Variables in Regressions 341

4 Violations of Regression Assumptions 345

5 Model Specification and Errors in Specification 359

6 Models with Qualitative Dependent Variables 372

CHAPTER 10 Time-Series Analysis 375

1 Introduction 375

2 Challenges of Working with Time Series 375

3 Trend Models 377

4 Autoregressive (AR) Time-Series Models 386

5 Random Walks and Unit Roots 399

6 Moving-Average Time-Series Models 407

7 Seasonality in Time-Series Models 412

8 Autoregressive Moving-Average Models 416

9 Autoregressive Conditional Heteroskedasticity Models 417

10 Regressions with More than One Time Series 420

11 Other Issues in Time Series 424

12 Suggested Steps in Time-Series Forecasting 425

CHAPTER 11 Portfolio Concepts 429

1 Introduction 429

2 Mean–Variance Analysis 429

3 Practical Issues in Mean–Variance Analysis 464

4 Multifactor Models 473

Appendices 511

References 521

Glossary 527

About the CFA Program 541

About the Authors 543

Index 545

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