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Quantitative investment analysis

Author: DeFusco, Richard A. ; McLeavey, Dennis W. ; Pinto, Jerald E. ; Runkle, David E. Series: CFA Institute investment series Publisher: Wiley 2007Edition: 2nd ed.Language: EnglishDescription: 566 p. : Graphs ; 26 cm.ISBN: 9780470052204Type of document: BookBibliography/Index: Includes bibliographical references and index and glossary
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Item type Current location Collection Call number Status Date due Barcode Item holds
Book Asia Campus
Main Collection
Print HG4529 .D44 2007
(Browse shelf)
900239066
Available 900239066
Book Europe Campus
Main Collection
Print HG4529 .D44 2007
(Browse shelf)
001267365
Available 001267365
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Includes bibliographical references and index and glossary

Digitized

Quantitative Investment Analysis Contents Foreword Acknowledgments Introduction CHAPTER 1 The Time Value of Money 1 Introduction 2 Interest Rates: Interpretation 3 The Future Value of a Single Cash Flow 3.1 The Frequency of Compounding 3.2 Continuous Compounding 3.3 Stated and Effective Rates 4 The Future Value of a Series of Cash Flows 4.1 Equal Cash Flows--Ordinary Annuity 4.2 Unequal Cash Flows 5 The Present Value of a Single Cash Flow 5.1 Finding the Present Value of a Single Cash Flow 5.2 The Frequency of Compounding 6 The Present Value of a Series of Cash Flows 6.1 The Present Value of a Series of Equal Cash Flows 6.2 The Present Value of an Infinite Series of Equal Cash Flows--Perpetuity 6.3 Present Values Indexed at Times Other Than t = 0 6.4 The Present Value of a Series of Unequal Cash Flows 7 Solving for Rates, Number of Periods, or Size of Annuity Payments 7.1 Solving for Interest Rates and Growth Rates 7.2 Solving for the Number of Periods 7.3 Solving for the Size of Annuity Payments 7.4 Review of Present and Future Value Equivalence 7.5 The Cash Flow Additivity Principle xiii xvii xix 1 1 1 3 8 10 12 13 13 15 15 15 17 19 19 23 24 26 27 27 30 30 35 36 CHAPTER 2 Discounted Cash Flow Applications 1 Introduction 2 Net Present Value and Internal Rate of Return 2.1 Net Present Value and the Net Present Value Rule 2.2 The Internal Rate of Return and the Internal Rate of Return Rule 2.3 Problems with the IRR Rule 3 Portfolio Return Measurement 3.1 Money-Weighted Rate of Return 3.2 Time-Weighted Rate of Return 4 Money Market Yields 39 39 39 40 42 45 47 47 49 54 CHAPTER 3 Statistical Concepts and Market Returns 1 Introduction 2 Some Fundamental Concepts 2.1 The Nature of Statistics 2.2 Populations and Samples 2.3 Measurement Scales 3 Summarizing Data Using Frequency Distributions 4 The Graphic Presentation of Data 4.1 The Histogram 4.2 The Frequency Polygon and the Cumulative Frequency Distribution 5 Measures of Central Tendency 5.1 The Arithmetic Mean 5.2 The Median 5.3 The Mode 5.4 Other Concepts of Mean 6 Other Measures of Location: Quantiles 6.1 Quartiles, Quintiles, Deciles, and Percentiles 6.2 Quantiles in Investment Practice 7 Measures of Dispersion 7.1 The Range 7.2 The Mean Absolute Deviation 7.3 Population Variance and Population Standard Deviation 7.4 Sample Variance and Sample Standard Deviation 7.5 Semivariance, Semideviation, and Related Concepts 7.6 Chebyshev's Inequality 7.7 Coefficient of Variation 7.8 The Sharpe Ratio 8 Symmetry and Skewness in Return Distributions 9 Kurtosis in Return Distributions 10 Using Geometric and Arithmetic Means 61 61 61 62 62 63 65 72 73 74 76 77 81 84 85 94 94 98 100 100 101 103 106 110 111 113 115 118 123 127 CHAPTER 4 Probability Concepts 1 Introduction 2 Probability, Expected Value, and Variance 3 Portfolio Expected Return and Variance of Return 4 Topics in Probability 4.1 Bayes' Formula 4.2 Principles of Counting 129 129 129 152 161 161 166 CHAPTER 5 Common Probability Distributions 1 Introduction 2 Discrete Random Variables 2.1 The Discrete Uniform Distribution 2.2 The Binomial Distribution 3 Continuous Random Variables 3.1 Continuous Uniform Distribution 3.2 The Normal Distribution 3.3 Applications of the Normal Distribution 3.4 The Lognormal Distribution 4 Monte Carlo Simulation 171 171 171 173 175 185 186 189 197 200 206 CHAPTER 6 Sampling and Estimation 1 Introduction 2 Sampling 2.1 Simple Random Sampling 2.2 Stratified Random Sampling 2.3 Time-Series and Cross-Sectional Data 3 Distribution of the Sample Mean 3.1 The Central Limit Theorem 4 Point and Interval Estimates of the Population Mean 4.1 Point Estimators 4.2 Confidence Intervals for the Population Mean 4.3 Selection of Sample Size 5 More on Sampling 5.1 Data-Mining Bias 5.2 Sample Selection Bias 5.3 Look-Ahead Bias 5.4 Time-Period Bias 215 215 215 216 217 219 221 222 225 225 227 233 235 236 238 240 240 CHAPTER 7 Hypothesis Testing 1 Introduction 2 Hypothesis Testing 243 243 244 3 Hypothesis Tests Concerning the Mean 3.1 Tests Concerning a Single Mean 3.2 Tests Concerning Differences between Means 3.3 Tests Concerning Mean Differences 4 Hypothesis Tests Concerning Variance 4.1 Tests Concerning a Single Variance 4.2 Tests Concerning the Equality (Inequality) of Two Variances 5 Other Issues: Nonparametric Inference 5.1 Tests Concerning Correlation: The Spearman Rank Correlation Coefficient 5.2 Nonparametric Inference: Summary 253 254 261 265 269 269 271 275 276 279 CHAPTER 8 Correlation and Regression 281 1 Introduction 281 2 Correlation Analysis 281 2.1 Scatter Plots 281 2.2 Correlation Analysis 282 2.3 Calculating and Interpreting the Correlation Coefficient 283 2.4 Limitations of Correlation Analysis 287 2.5 Uses of Correlation Analysis 289 2.6 Testing the Significance of the Correlation Coefficient 297 3 Linear Regression 300 3.1 Linear Regression with One Independent Variable 300 3.2 Assumptions of the Linear Regression Model 303 3.3 The Standard Error of Estimate 306 3.4 The Coefficient of Determination 309 3.5 Hypothesis Testing 310 3.6 Analysis of Variance in a Regression with One Independent Variable 318 3.7 Prediction Intervals 321 3.8 Limitations of Regression Analysis 324 CHAPTER 9 Multiple Regression and Issues in Regression Analysis 1 Introduction 2 Multiple Linear Regression 2.1 Assumptions of the Multiple Linear Regression Model 2.2 Predicting the Dependent Variable in a Multiple Regression Model 2.3 Testing Whether All Population Regression Coefficients Equal Zero 2.4 Adjusted R2 3 Using Dummy Variables in Regressions 4 Violations of Regression Assumptions 4.1 Heteroskedasticity 4.2 Serial Correlation 4.3 Multicollinearity 325 325 325 331 336 338 340 341 345 345 351 356 4.4 Heteroskedasticity, Serial Correlation, Multicollinearity: Summarizing the Issues 5 Model Specification and Errors in Specification 5.1 Principles of Model Specification 5.2 Misspecified Functional Form 5.3 Time-Series Misspecification (Independent Variables Correlated with Errors) 5.4 Other Types of Time-Series Misspecification 6 Models with Qualitative Dependent Variables 359 359 359 360 368 372 372 CHAPTER 10 Time-Series Analysis 1 Introduction 2 Challenges of Working with Time Series 3 Trend Models 3.1 Linear Trend Models 3.2 Log-Linear Trend Models 3.3 Trend Models and Testing for Correlated Errors 4 Autoregressive (AR) Time-Series Models 4.1 Covariance-Stationary Series 4.2 Detecting Serially Correlated Errors in an Autoregressive Model 4.3 Mean Reversion 4.4 Multiperiod Forecasts and the Chain Rule of Forecasting 4.5 Comparing Forecast Model Performance 4.6 Instability of Regression Coefficients 5 Random Walks and Unit Roots 5.1 Random Walks 5.2 The Unit Root Test of Nonstationarity 6 Moving-Average Time-Series Models 6.1 Smoothing Past Values with an n-Period Moving Average 6.2 Moving-Average Time-Series Models for Forecasting 7 Seasonality in Time-Series Models 8 Autoregressive Moving-Average Models 9 Autoregressive Conditional Heteroskedasticity Models 10 Regressions with More than One Time Series 11 Other Issues in Time Series 12 Suggested Steps in Time-Series Forecasting 375 375 375 377 377 380 385 386 386 387 391 391 394 397 399 400 403 407 407 409 412 416 417 420 424 425 CHAPTER 11 Portfolio Concepts 1 Introduction 2 Mean­Variance Analysis 2.1 The Minimum-Variance Frontier and Related Concepts 2.2 Extension to the Three-Asset Case 2.3 Determining the Minimum-Variance Frontier for Many Assets 2.4 Diversification and Portfolio Size 429 429 429 430 439 442 445 2.5 Portfolio Choice with a Risk-Free Asset 2.6 The Capital Asset Pricing Model 2.7 Mean­Variance Portfolio Choice Rules: An Introduction 3 Practical Issues in Mean­Variance Analysis 3.1 Estimating Inputs for Mean­Variance Optimization 3.2 Instability in the Minimum-Variance Frontier 4 Multifactor Models 4.1 Factors and Types of Multifactor Models 4.2 The Structure of Macroeconomic Factor Models 4.3 Arbitrage Pricing Theory and the Factor Model 4.4 The Structure of Fundamental Factor Models 4.5 Multifactor Models in Current Practice 4.6 Applications 4.7 Concluding Remarks 449 458 460 464 464 470 473 474 475 478 484 485 493 509 Appendices References Glossary About the CFA Program About the Authors Index 511 521 527 541 543 545

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