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- Product code: 19701
- ISBN: 0195108094,
ISBN13: 9780195108095,
508 pages, hardback
Published by Oxford University Press on 1997
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Description of Investment Science |
Designed for those individuals interested in the current state of development in the field of investment science, this book emphasizes the fundamental principles and how they can be mastered and transformed into solutions of important and interesting investment problems. The book examines what the essential ideas are behind investment science, how they are represented, and how they can be used in actual investment practice. The book also examines where the field might be headed in the future, and goes much further in terms of mathematical content, featuring varying levels of mathematical sophistication throughout. End-of-chapter exercises are also included to help individuals get a better grasp on investment science.
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Contents of Investment Science |
Preface
1. INTRODUCTION
1.1 Cash Flows
1.2 Investments and Markets
1.3 Typical Investment Problems
1.4 Organization of the Book
PART I: DETERMINISTIC CASH FLOW STREAMS
2. THE BASIC THEORY OF INTEREST
2.1 Principal and Interest
2.2 Present Value
2.3 Present and Future Values of Streams
2.4 Internal Rate of Return
2.5 Evaluation Criteria
2.6 Applications and Extensions(*)
2.7 Summary
Exercises
References
3. FIXED-INCOME SECURITIES
3.1 The Market for Future Cash
3.2 Value Formulas
3.3 Bond Details
3.4 Yield
3.5 Duration
3.6 Immunization
3.7 Convexity(*)
3.8 Summary
Exercises
References
4. THE TERM STRUCTURE OF INTEREST RATES
4.1 The Yield Curve
4.2 The Term Structure
4.3 Forward Rates
4.4 Term Structure Explanations
4.5 Expectations Dynamics
4.6 Running Present Value
4.7 Floating Rate Bonds
4.8 Duration
4.9 Immunization
4.10 Summary
Exercises
References
5. APPLIED INTEREST RATE ANALYSIS
5.1 Capital Budgeting
5.2 Optimal Portfolios
5.3 Dynamic Cash Flow Processes
5.4 Optimal Management
5.5 The Harmony Theorem(*)
5.6 Valuation of a Firm(*)
5.7 Summary
Exercises
References
PART II: SINGLE-PERIOD RANDOM CASH FLOWS
6. MEAN-VARIANCE PORTFOLIO THEORY
6.1 Asset Return
6.2 Random Variables
6.3 Random Returns
6.4 Portfolio Mean and Variance
6.5 The Feasible Set
6.6 The Markowitz Model
6.7 The Two-Fund Theorem(*)
6.8 Inclusion of a Risk-Free Asset
6.9 The One-Fund Theorem
6.10 Summary
Exercises
References
7. THE CAPITAL ASSET PRICING MODEL
7.1 Market Equilibrium
7.2 The Capital Market Line
7.3 The Pricing Model
7.4 The Security Market Line
7.5 Investment Implications
7.6 Performance Evaluation
7.7 CAPM as a Pricing Formula
7.8 Project Choice(*)
7.9 Summary
Exercises
References
8. MODELS AND DATA
8.1 Introduction
8.2 Factor Models
8.3 The CAPM as a Factor Model
8.4 Arbitrage Pricing Theory(*)
8.5 Data and Statistics
8.6 Estimation of Other Parameters
8.7 Tilting Away from Equilibrium
8.8 A Multiperiod Fallacy
8.9 Summary
Exercises
References
9 GENERAL PRINCIPLES
9.1 Introduction
9.2 Utility Functions
9.3 Risk Aversion
9.4 Specification of Utility Functions(*)
9.5 Utility Functions and the
Mean-Variance Criterion(*)
9.6 Linear Pricing
9.7 Portfolio Choice
9.8 Log-Optimal Pricing(*)
9.9 Finite State Models
9.10 Risk-Neutral Pricing(*)
9.11 Pricing Alternatives(*)
9.12 Summary
Exercises
References
PART III: DERIVATIVE SECURITIES
10. FORWARDS, FUTURES, AND SWAPS
10.1 Introduction
10.2 Forward Contracts
10.3 Forward Prices
10.4 The Value of a Forward Contract
10.5 Swaps(*)
10.6 Basics of Futures Contracts
10.7 Futures Prices
10.8 Relation to Expected Spot Price(*)
10.9 The Perfect Hedge
10.10 The Minimum-Variance Hedge
10.11 Optimal Hedging(*)
10.12 Hedging Nonlinear Risk(*)
10.13 Summary
Exercises
References
11. MODELS OF ASSET DYNAMICS
11.1 Binomial Lattice Model
11.2 The Additive Model
11.3 The Multiplicative Model
11.4 Typical Parameter Values(*)
11.5 Lognormal Random Variables
11.6 Random Walks and Wiener Processes
11.7 A Stock Price Process
11.8 Ito's Lemma(*)
11.9 Binomial Lattice Revisited
11.10 Summary
Exercises
References
12. BASIC OPTIONS THEORY
12.1 Option Concepts
12.2 The Nature of Option Values
12.3 Option Combinations and Put-Call Parity
12.4 Early Exercise
12.5 Single-Period Binomial Options Theory
12.6 Multiperiod Options
12.7 More General Binomial Problems
12.8 Evaluating Real Investment Opportunities
12.9 General Risk-Neutral Pricing(*)
12.10 Summary
Exercises
References
13. ADDITIONAL OPTIONS TOPICS
13.1 Introduction
13.2 The Black-Scholes Equation
13.3 Call Option Formula
13.4 Risk-Neutral Valuation(*)
13.5 Delta
13.6 Replication, Synthetic Options, and
Portfolio Insurance(*)
13.7 Computational Methods
13.8 Exotic Options
13.9 Storage Costs and Dividends(*)
13.10 Martingale Pricing(*)
13.11 Summary
Appendix: Alternative Black-Scholes
Derivation(*)
Exercises
References
14. INTEREST RATE DERIVATIVES
14.1 Examples of Interest Rate Derivatives
14.2 The Need for a Theory
14.3 The Binomial Approach
14.4 Pricing Applications
14.5 Leveling and Adjustable-Rate Loans(*)
14.6 The Forward Equation
14.7 Matching the Term Structure
14.8 Immunization
14.9 Collateralized Mortgage Obligations(*)
14.10 Models of Interest Rate Dynamics(*)
14.11 Continuous-Time Solutions(*)
14.12 Summary
Exercises
References
PART IV GENERAL CASH FLOW STREAMS
15. OPTIMAL PORTFOLIO GROWTH
15.1 The Investment Wheel
15.2 The Log Utility Approach to Growth
15.3 Properties of the Log-Optimal Strategy(*)
15.4 Alternative Approaches(*)
15.5 Continuous-Time Growth
15.6 The Feasible Region
15.7 The Log-Optimal Pricing Formula(*)
15.8 Log-Optimal Pricing and the Black-Scholes Equation(*)
15.9 Summary
Exercises
References
16 GENERAL INVESTMENT EVALUATION
16.1 Multiperiod Securities
16.2 Risk-Neutral Pricing
16.3 Optimal Pricing
16.4 The Double Lattice
16.5 Pricing in a Double Lattice
16.6 Investments with Private Uncertainty
16.7 Buying Price Analysis
16.8 Continuous-Time Evaluation(*)
16.9 Summary
Exercises
References
Appendix A BASIC PROBABILITY THEORY
A.1 General Concepts
A.2 Normal Random Variables
A.3 Lognormal Random Variables
Appendix B CALCULUS AND OPTIMIZATION
B.1 Functions
B.2 Differential Calculus
B.3 Optimization
Answers to Exercises
Index
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About David G. Luenberger |
David G. Luenberger is Professor in Engineering Economics Systems and Operations Research, Stanford University
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