|
Textbook
Quantitative Investment Analysis, 2nd EditionISBN: 978-0-470-05220-4
Hardcover
600 pages
January 2007, ©2007
 Add to Cart
This price is valid for United States. Change location to view local pricing and availability.  Other Available Formats: E-book
|
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
