Quantitative Investment Analysis

ISBN-10: 0470052201

ISBN-13: 9780470052204

Edition: 2nd 2007 (Revised)

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Description: This edition is a guide to applying quantitative analysis to the investment process. Examples and problems are investment-oriented and reflect the changes currently taking place in the global investment community.

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Book details

List price: $100.00
Edition: 2nd
Copyright year: 2007
Publisher: John Wiley & Sons, Incorporated
Publication date: 1/22/2007
Binding: Hardcover
Pages: 600
Size: 7.50" wide x 10.25" long x 1.25" tall
Weight: 2.882
Language: English

RICHARD A. DeFUSCO, CFA, is an Associate Professor of Finance at the University of Nebraska-Lincoln. DeFusco 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. He earned his CFA charter in 1999.DENNIS W. McLEAVEY, CFA, is Head of Professional Development Products at CFA Institute. 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 in investment planning, portfolio analysis, and quantitative analysis. He holds an MBA from Baruch College and a PhD in finance from the Stern School. Pinto earned his CFA charter in 1992.DAVID E. RUNKLE, CFA, is Vice President and Research Manager at U.S. Bancorp Piper Jaffray. He is an adjunct professor of finance in the Carlson School of Management at the University of Minnesota. Runkle received a BA in economics from Carleton College and a PhD in economics from MIT.

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.

Foreword
Acknowledgments
Introduction
The Time Value of Money
Introduction
Interest Rates: Interpretation
The Future Value of a Single Cash Flow
The Frequency of Compounding
Continuous Compounding
Stated and Effective Rates
The Future Value of a Series of Cash Flows
Equal Cash Flows-Ordinary Annuity
Unequal Cash Flows
The Present Value of a Single Cash Flow
Finding the Present Value of a Single Cash Flow
The Frequency of Compounding
The Present Value of a Series of Cash Flows
The Present Value of a Series of Equal Cash Flows
The Present Value of an Infinite Series of Equal Cash Flows-Perpetuity
Present Values Indexed at Times Other Than t = 0
The Present Value of a Series of Unequal Cash Flows
Solving for Rates, Number of Periods, or Size of Annuity Payments
Solving for Interest Rates and Growth Rates
Solving for the Number of Periods
Solving for the Size of Annuity Payments
Review of Present and Future Value Equivalence
The Cash Flow Additivity Principle
Discounted Cash Flow Applications
Introduction
Net Present Value and Internal Rate of Return
Net Present Value and the Net Present Value Rule
The Internal Rate of Return and the Internal Rate of Return Rule
Problems with the IRR Rule
Portfolio Return Measurement
Money-Weighted Rate of Return
Time-Weighted Rate of Return
Money Market Yields
Statistical Concepts and Market Returns
Introduction
Some Fundamental Concepts
The Nature of Statistics
Populations and Samples
Measurement Scales
Summarizing Data Using Frequency Distributions
The Graphic Presentation of Data
The Histogram
The Frequency Polygon and the Cumulative Frequency Distribution
Measures of Central Tendency
The Arithmetic Mean
The Median
The Mode
Other Concepts of Mean
Other Measures of Location: Quantiles
Quartiles, Quintiles, Deciles, and Percentiles
Quantiles in Investment Practice
Measures of Dispersion
The Range
The Mean Absolute Deviation
Population Variance and Population Standard Deviation
Sample Variance and Sample Standard Deviation
Semivariance, Semideviation, and Related Concepts
Chebyshev's Inequality
Coefficient of Variation
The Sharpe Ratio
Symmetry and Skewness in Return Distributions
Kurtosis in Return Distributions
Using Geometric and Arithmetic Means
Probability Concepts
Introduction
Probability, Expected Value, and Variance
Portfolio Expected Return and Variance of Return
Topics in Probability
Bayes' Formula
Principles of Counting
Common Probability Distributions
Introduction
Discrete Random Variables
The Discrete Uniform Distribution
The Binomial Distribution
Continuous Random Variables
Continuous Uniform Distribution
The Normal Distribution
Applications of the Normal Distribution
The Lognormal Distribution
Monte Carlo Simulation
Sampling and Estimation
Introduction
Sampling
Simple Random Sampling
Stratified Random Sampling
Time-Series and Cross-Sectional Data
Distribution of the Sample Mean
The Central Limit Theorem
Point and Interval Estimates of the Population Mean
Point Estimators
Confidence Intervals for the Population Mean
Selection of Sample Size
More on Sampling
Data-Mining Bias
Sample Selection Bias
Look-Ahead Bias
Time-Period Bias
Hypothesis Testing
Introduction
Hypothesis Testing
Hypothesis Tests Concerning the Mean
Tests Concerning a Single Mean
Tests Concerning Differences between Means
Tests Concerning Mean Differences
Hypothesis Tests Concerning Variance
Tests Concerning a Single Variance
Tests Concerning the Equality (Inequality) of Two Variances
Other Issues: Nonparametric Inference
Tests Concerning Correlation: The Spearman Rank Correlation Coefficient
Nonparametric Inference: Summary
Correlation and Regression
Introduction
Correlation Analysis
Scatter Plots
Correlation Analysis
Calculating and Interpreting the Correlation Coefficient
Limitations of Correlation Analysis
Uses of Correlation Analysis
Testing the Significance of the Correlation Coefficient
Linear Regression
Linear Regression with One Independent Variable
Assumptions of the Linear Regression Model
The Standard Error of Estimate
The Coefficient of Determination
Hypothesis Testing
Analysis of Variance in a Regression with One Independent Variable
Prediction Intervals
Limitations of Regression Analysis
Multiple Regression and Issues in Regression Analysis
Introduction
Multiple Linear Regression
Assumptions of the Multiple Linear Regression Model
Predicting the Dependent Variable in a Multiple Regression Model
Testing Whether All Population Regression Coefficients Equal Zero
Adjusted R[superscript 2]
Using Dummy Variables in Regressions
Violations of Regression Assumptions
Heteroskedasticity
Serial Correlation
Multicollinearity
Heteroskedasticity, Serial Correlation, Multicollinearity: Summarizing the Issues
Model Specification and Errors in Specification
Principles of Model Specification
Misspecified Functional Form
Time-Series Misspecification (Independent Variables Correlated with Errors)
Other Types of Time-Series Misspecification
Models with Qualitative Dependent Variables
Time-Series Analysis
Introduction
Challenges of Working with Time Series
Trend Models
Linear Trend Models
Log-Linear Trend Models
Trend Models and Testing for Correlated Errors
Autoregressive (AR) Time-Series Models
Covariance-Stationary Series
Detecting Serially Correlated Errors in an Autoregressive Model
Mean Reversion
Multiperiod Forecasts and the Chain Rule of Forecasting
Comparing Forecast Model Performance
Instability of Regression Coefficients
Random Walks and Unit Roots
Random Walks
The Unit Root Test of Nonstationarity
Moving-Average Time-Series Models
Smoothing Past Values with an n-Period Moving Average
Moving-Average Time-Series Models for Forecasting
Seasonality in Time-Series Models
Autoregressive Moving-Average Models
Autoregressive Conditional Heteroskedasticity Models
Regressions with More than One Time Series
Other Issues in Time Series
Suggested Steps in Time-Series Forecasting
Portfolio Concepts
Introduction
Mean-Variance Analysis
The Minimum-Variance Frontier and Related Concepts
Extension to the Three-Asset Case
Determining the Minimum-Variance Frontier for Many Assets
Diversification and Portfolio Size
Portfolio Choice with a Risk-Free Asset
The Capital Asset Pricing Model
Mean-Variance Portfolio Choice Rules: An Introduction
Practical Issues in Mean-Variance Analysis
Estimating Inputs for Mean-Variance Optimization
Instability in the Minimum-Variance Frontier
Multifactor Models
Factors and Types of Multifactor Models
The Structure of Macroeconomic Factor Models
Arbitrage Pricing Theory and the Factor Model
The Structure of Fundamental Factor Models
Multifactor Models in Current Practice
Applications
Concluding Remarks
Appendices
References
Glossary
About the CFA Program
About the Authors
Index
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