Quantitative Methods for Investment Analysis,9780935015690

Quantitative Methods for Investment Analysis

by ; ; ;
ISBN13: 9780935015690
ISBN10: 0935015698
Format: Hardcover
Pub. Date: 2001-11-01
Publisher(s): Professional Book Distributors
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Table of Contents

Foreword v
Preface vii
Acknowledgments ix
About the Authors xi
The Time Value of Money
1(52)
Interest Rates and Discount Rates
1(2)
The Future Value of a Single Cash Flow
3(8)
The Frequency of Compounding
7(2)
Continuous Compounding
9(1)
Stated and Effective Rates
10(1)
The Future Value of a Series of Cash Flows
11(3)
Equal Cash Flows-Ordinary Annuity
12(1)
Unequal Cash Flows
13(1)
The Present Value of a Single Cash Flow
14(3)
Finding the Present Value of a Single Cash Flow
14(2)
The Frequency of Compounding
16(1)
The Present Value of a Series of Cash Flows
17(7)
The Present Value of a Series of Equal Cash Flows
17(4)
The Present Value of an Infinite Series of Equal Cash Flows-Perpetuity
21(1)
Present Values Indexed at Times Other Than t = 0
22(2)
The Present Value of a Series of Unequal Cash Flows
24(1)
Solving for Rates, Number of Periods, or Size of Annuity Payments
24(7)
Solving for Interest Rates and Growth Rates
25(2)
Solving for the Number of Periods
27(1)
Solving for the Size of Annuity Payments
28(3)
Almost Even Cash Flows
31(5)
Review of Present and Future Value Equivalence
32(1)
The Cash Flow Additivity Principle
33(1)
Applying Equivalence and Additivity to Almost-Even Cash Flows
34(2)
Summary
36(17)
Problems
37(2)
Solutions
39(14)
Discounted Cash Flow Applications
53(48)
Discounted Cash Flow Analysis
54(6)
The Net Present Value Rule
54(2)
The Internal Rate of Return Rule
56(3)
Problems with the Internal Rate of Return Rule
59(1)
Money Market Yields
60(5)
Basic Bond Valuation
65(7)
Zero-Coupon Bonds and the Arbitrage-Free Valuation Approach
65(4)
Coupon Bonds and the Yield to Maturity Valuation Approach
69(3)
Basic Equity Valuation
72(9)
Portfolio Return Measurement
81(6)
Dollar-Weighted Rate of Return
81(1)
Time-Weighted Rate of Return
82(5)
Summary
87(14)
Problems
90(3)
Solutions
93(8)
Statistical Concepts and Market Returns
101(72)
The Nature of Statistics
102(2)
What Is Statistics?
102(1)
Populations and Samples
102(1)
Measurement Scales
103(1)
Frequency Distributions
104(7)
Graphic Presentation
111(4)
The Histogram
111(1)
The Frequency Polygon and the Cumulative Frequency Distribution
112(3)
Measures of Central Tendency
115(15)
The Population Mean
115(1)
The Sample Mean
115(2)
Properties of the Arithmetic Mean
117(1)
The Median
117(1)
The Mode
118(1)
Quartiles, Quintiles, Deciles, and Percentiles
119(2)
Using Quantiles for Portfolio Formation
121(2)
The Weighted Mean
123(2)
The Geometric Mean
125(5)
Measures of Dispersion and Their Applications
130(8)
The Range
130(1)
The Mean Absolute Deviation
131(1)
Population Variance and Standard Deviation
131(1)
Sample Variance and Standard Deviation
132(2)
Chebyshev's Inequality
134(1)
Relative Dispersion
135(2)
The Sharpe Measure of Risk-Adjusted Performance
137(1)
Symmetry and Skewness in Return Distributions
138(4)
Kurtosis in Return Distributions
142(2)
Using Geometric and Arithmetic Means
144(3)
Summary
147(26)
Problems
148(6)
Solutions
154(19)
Probability Concepts
173(52)
Introduction
174(1)
Probability, Expected Value, and Variance
175(20)
Portfolio Expected Return and Variance
195(9)
Topics in Probability
204(7)
Bayes' Formula
204(3)
Principles of Counting
207(4)
Summary
211(14)
Problems
214(4)
Solutions
218(7)
Common Probability Distributions
225(54)
Introduction to Common Probability Distributions
226(1)
Discrete Random Variables
227(13)
The Discrete Uniform Distribution
228(2)
The Binomial Distribution
230(10)
Continuous Random Variables
240(21)
Continuous Uniform Distribution
240(3)
The Normal Distribution
243(8)
Applications of the Normal Distribution
251(6)
The Lognormal Distribution
257(4)
Monte Carlo Simulation
261(5)
Summary
266(13)
Problems
269(4)
Solutions
273(6)
Sampling and Estimation
279(36)
Introduction
280(1)
Sampling
280(6)
Simple Random Sampling
280(2)
Stratified Random Sampling
282(1)
Time-Series and Cross-Sectional Data
283(3)
Distribution of the Sample Mean
286(3)
The Central Limit Theorem
286(3)
Point and Interval Estimates of the Population Mean
289(9)
Point Estimators
289(2)
Confidence Intervals for the Population Mean
291(7)
More on Sampling
298(4)
Data-Snooping/Data-Mining Bias
298(1)
Sample Selection Bias
299(1)
Look-Ahead Bias
300(1)
Time-Period Bias
301(1)
Summary
302(13)
Problems
305(3)
Solutions
308(7)
Hypothesis Testing
315(46)
Introduction
316(1)
Hypothesis Testing
317(9)
Hypothesis Tests Concerning the Mean
326(15)
Tests Concerning a Single Mean
326(7)
Tests Concerning Differences between Means
333(4)
Tests Concerning Mean Differences
337(4)
Hypothesis Tests Concerning Variance
341(4)
Tests Concerning a Single Variance
341(2)
Tests Concerning Differences between Variances
343(2)
Other Issues In Inference
345(2)
Summary
347(14)
Problems
350(5)
Solutions
355(6)
Correlation and Regression
361(66)
Introduction
362(1)
Correlation Analysis
363(16)
Scatter Plots
363(1)
Correlation Analysis
364(2)
Calculating and Interpreting the Correlation Coefficient
366(2)
Uses and Limitations of Correlation Analysis
368(9)
Testing the Significance of the Correlation Coefficient
377(2)
Linear Regression
379(24)
Linear Regression with One Independent Variable
379(3)
The Assumptions of the Linear Regression Model
382(4)
The Standard Error of Estimate
386(2)
The Coefficient of Determination
388(2)
Confidence Intervals and Testing Hypotheses
390(6)
Analysis of Variance in a Regression with One Independent Variable
396(3)
Prediction Intervals
399(2)
Limitations of Regression Analysis
401(2)
Summary
403(24)
Problems
405(12)
Solutions
417(10)
Multiple Regression and Issues in Regression Analysis
427(60)
Introduction
428(1)
Multiple Linear Regression
428(11)
Assumptions of the Multiple Linear Regression Model
432(2)
The Standard Error of Estimate in Multiple Linear Regression
434(2)
Predicting the Dependent Variable in a Multiple Regression Model
436(1)
Testing Whether All Population Regression Coefficients Are Equal to Zero
437(2)
Is R2 Related to Statistical Significance?
439(1)
Using Dummy Variables in Regressions
439(6)
Heteroskedasticity
445(5)
Types of Heteroskedasticity
447(2)
Correcting for Heteroskedasticity
449(1)
Serial Correlation
450(7)
The Consequences of Serial Correlation
450(1)
Testing for Serial Correlation
451(2)
Correcting for Serial Correlation
453(4)
Multicollinearity
457(2)
Heteroskedasticity, Serial Correlation, and Multicollinearity: Summarizing the Issues
459(1)
Models with Qualitative Dependent Variables
460(2)
Summary
462(25)
Problems
465(12)
Solutions
477(10)
Time Series Analysis
487(70)
Introduction to Time Series Analysis
488(3)
Trends
491(6)
The Limitations of Trend Models
497(1)
Fundamental Issues in Time Series
498(2)
Autoregressive Time-Series Models
500(12)
Mean Reversion
503(1)
Multiperiod Forecasts and the Chain Rule of Forecasting
504(3)
Comparing Forecast Model Performance
507(2)
Instability of Regression Coefficients
509(3)
Random Walks and Unit Roots
512(9)
Random Walks
512(4)
Unit Roots
516(5)
Moving-Average Time-Series Models
521(4)
Smoothing Past Values with an n-Period Moving Average
521(2)
Moving-Average Time Series Models for Forecasting
523(2)
Seasonality in Time-Series Models
525(6)
Autoregressive Moving-Average Models
531(1)
Autoregressive Conditional Heteroskedasticity
532(3)
Other Issues In Time Series
535(1)
Suggested Steps in Time-Series Forecasting
536(2)
Summary
538(19)
Problems
540(10)
Solutions
550(7)
Portfolio Concepts
557(79)
Introduction
559(1)
Mean-Variance Analysis and Diversification
560(33)
Optimal Portfolios with Three Assets
570(3)
Determining the Minimum-Variance Frontier for Many Assets
573(3)
Instability in the Minimum-Variance Frontier
576(3)
Diversification and Portfolio Size
579(4)
Risk-Free Assets and the Trade-Off between Risk and Return
583(6)
The Capital Allocation Line Equation
589(2)
The Capital Asset Pricing Model
591(2)
Practical Issues in Mean-Variance Analysis
593(5)
Estimates Based on Historical Means, variances, and Covariances
594(1)
The Market Model
594(3)
Adjusted Beta Market Models
597(1)
Multifactor Models
598(21)
The Structure of Factor Models
599(3)
Arbitrage Pricing Theory and the Factor Model
602(11)
Multifactor Models in Current Practice
613(5)
Concluding Remarks
618(1)
Summary
619(17)
Problems
627(3)
Solutions
630(6)
Appendix A Cumulative Probabilities for a Standard Normal Distribution P(Z ≤ x) = N(x) for x ≤ 0 or P(Z ≤ z) = N(z) for z ≤ 0 636(2)
Appendix B Table of the Student's t-Distribution (One Tailed Probabilities) 638(1)
Appendix C Values of X2 (Degrees of Freedom, Level of Significance) 639(1)
Appendix D Table of the F-Distribution 640(4)
Appendix E Critical Values for the Durbin-Watson Statistic (α = .05) 644(1)
References 645(4)
Glossary 649(10)
Index 659

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