Cover image for Risk finance and asset pricing : value, measurements, and markets
Title:
Risk finance and asset pricing : value, measurements, and markets
Personal Author:
Series:
Wiley finance

Wiley finance series
Publication Information:
Hoboken, NJ. : Wiley, 2010
Physical Description:
xix, 456 p. : ill. ; 26 cm.
ISBN:
9780470549469
Abstract:
"Charles Tapiero, as the head of the biggest financial engineering program in the world and business consultant, has his finger on the pulse of the shift that is coming in financial engineering applications and study. With an eye toward the future, he has crafted a comprehensive and practical book that emphasizes an intuitive approach to the financial and quantitative foundations of financial and risk engineering and its many applications to asset pricing and risk management. Covering the theory from a practitioner perspective, he then applies it to a variety of real world problems. The book presents important techniques to price, hedge, and manage risks in general - while acknowledging the high degree of uncertainty in the real world"-- Provided by publisher.

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30000010212211 HG176.7 T37 2010 Open Access Book Book
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Summary

Summary

A comprehensive guide to financial engineering that stresses real-world applications

Financial engineering expert Charles S. Tapiero has his finger on the pulse of shifts coming to financial engineering and its applications. With an eye toward the future, he has crafted a comprehensive and accessible book for practitioners and students of Financial Engineering that emphasizes an intuitive approach to financial and quantitative foundations in financial and risk engineering. The book covers the theory from a practitioner perspective and applies it to a variety of real-world problems.

Examines the cornerstone of the explosive growth in markets worldwide Presents important financial engineering techniques to price, hedge, and manage risks in general Author heads the largest financial engineering program in the world
Author Charles Tapiero wrote the seminal work Risk and Financial Management .


Author Notes

CHARLES S. TAPIERO is the Topfer Distinguished Professor of Financial Engineering and Technology Management at the New York University Polytechnic Institute. He is also Chair and founder of the Department of Finance and Risk Engineering, as well as cofounder and co-Editor in Chief of Risk and Decision Analysis. An active researcher and consultant, Professor Tapiero has published over 350 papers and thirteen books on a broad range of issues spanning risk analysis, actuarial and financial risk engineering, and management, including Risk and Financial Management: Mathematical and Computational Methods, also by Wiley.


Table of Contents

Introduction
Who This Book is For
How This Book is Structured
What's on the Companion Website
Chapter 1 Risk, Finance, Corporate Management and Society
Overview
1.1 Risks Everywhere-A Consequence of Uncertainty
1.2 Risks and Finance: Basic Concepts
Example: An IBM day-trades record
Example: Constructing a portfolio
1.3 Option Contracts
Problem 1.1 Options and their Price
Example: Options and the Price of Equity
Example: Management Stock Options
1.4 Options and Trading in Specialized Markets
1.5 Real Life Crises and Finance
1.6 The 2008 Meltdown and Financial Theory
1.7 Finance and Ethics
Summary
Test Yourself
References
Chapter 2 Applied Finance
Overview
2.1 Finance and Practice
2.2 Financial Risk Pricing: A Historical Perspective
2.3 Essential of Financial Risk Management
2.4 Technology and Complexity
2.5 Market Making and Pricing Practice
Summary
Test Yourself
References
Chapter 3 Risk Measurement and Volatility
Overview
3.1 Risk, Volatility and Measurement
3.2 Moments and Measures of Volatility
Example: IBM Returns Statistics
Example: Moments and the CAPM
Problem 3.1 Calculating the Beta of a Security
3.3 Statistical Estimations
Example: The AR(1) ARCH(1) Model
Example: A Garch (1,1) Model
3.4 High-Low Estimators of Volatility
3.5 Extreme Measures, Volume, and Intraday Prices
Problem 3.2 The Probability of the Range
3.6 Data Transformation
Example: Taylor Series
3.7 Value at Risk and Risk Exposure
Example: VaR and Shortfall
Example*: VaR, Normal ROR and Portfolio Design
Summary
Test Yourself
References
Chapter 4 Risk Finance Modeling and Dependence
Overview
4.1 Introduction
4.2 Statistical Dependence
Example: Risk Factors Aggregation
Example: Principal Components Analysis (PCA)
Example: A Bi-Variate Data Matrix and PCA
Example: A Market Index and PCA
4.3 Dependence and Copulas
Example: The Gumbel Copula, the Highs and the Lows
Example: Copulas and Conditional Dependence
Example: Copula and the Conditional Distribution
4.4 Financial Modeling and Inter-Temporal Models
4.5 The R/S Index
Summary
Test Yourself
References
Chapter 5 Risk, Value, and Financial Prices
Overview
5.1 Value and Price
5.2 Utility, Risk and Money
5.3 Lotteries and Utility Functions
Example: The utility of a lottery
Example: The power utility function
Example: Valuation and the Pricing of Cash Flows
Example: Risk and the Financial Meltdown
5.4 Utility Rational Foundations
Examples: Specific Utility Functions
5.5 The Price and the Utility of Consumption
Example: Kernel Pricing and the exponential utility function
Example: The Pricing Kernel and the CAPM
Example: Kernel Pricing and the HARA utility function
Summary
Test Yourself
References
Chapter 6 Applied Utility Finance
Overview
6.1 Risk and the Utility of Time
6.2 Assets Allocation and Investments
Example: A Two securities problem
Example: A 2 stocks portfolio
Problem 6.1 The Efficiency Frontier
Problem 6.2 A Two Securities Portfolio
6.4 Conditional Kernel Pricing and the Price of Infrastructure Investments
6.5 Conditional Kernel Pricing and the Pricing of Inventories
6.6 Agency and Utility
Example: A linear risk sharing rule
6.7 Information Asymmetry: Moral Hazard and Adverse Selection
6.8 Adverse Selection
6.9 The Moral Hazard Problem
6.10 Signaling and Screening
Summary
Test Yourself
References
Chapter 7 Derivative Finance and Complete Markets
Discrete States
Overview
7.1 The Arrow-Debreu Fundamental Approach to Asset Pricing
Example: Generalization to n states
Example: Binomial Option Pricing
Problem 7.1 The Implied Risk Neutral Probability
Example: The Price of a Call option
Example: A generalization to multiple periods
Problem 7.2 Options and their Prices
7.2 Put Call Parity
Problem 7.3 Proving the Put-Call Parity
Example: Put Call Parity and Dividend Payments
Problem 7.4 Options PUT-CALL Parity
7.3 The Price deflator and the Pricing Martingale
7.4 Pricing and Complete Markets
7.5 Options Galore
Example: Look-Back Options
Example: Asiatic Options
Example: Exchange options
Example: Chooser Options
Example: Barrier and Other Options
Example: Passport Options
7.6 Options and Their "Real Uses"
Example: Pricing a Forward
Example: Pricing a floating rate bond
Example: Pricing fixed rate bond
Example: The Term Structure of Interest Rate
Problem 7.5 Annuities and Obligations
7.7 Pricing and Franchises with a Binomial Process
7.8 Pricing a Pricing Policy
7.9 Options Trading, Speculation, and Risk Management
Example: Options and Trading Practice
Example: Insuring and derivative hedges
Problem 7.6 Portfolio Strategies
Summary
Appendix A Martingales
Example: Change of Measure in a Binomial Model
Example: A Two Stages Random Walk and the Radon Nikodym Derivative
Appendix B Formal Notations, Key terms and Definitions
Test Yourself
References
Chapter 8 Options Applied
Overview
8.1 Introduction
8.2 Optional Applications
Problem 8.1 Pricing a Multi Period Forward
Example: Options Implied insurance pricing
8.3 Random volatility and options pricing
8.4 Real Assets and Real Options
8.5 The Black Scholes Vanilla Option and the Greeks
8.6 The Greeks and Their Applications
Summary
Test Yourself
References
Chapter 9 Credit Scoring and the Price of Credit Risk
Overview
9.1 Credit and Money
9.2 Credit and Credit Risk
9.3 Pricing Credit Risk: Principles
9.4 Credit Scoring and Granting
9.5 Credit Scoring: Real- Approaches
Example: A Separatrix
Example: The Separatrix and Bayesian Probabilities
9.6 Probability Default Models
Example: A Bivariate Dependent Default Distribution
Example: A Portfolio of default loans
Example: A Portfolio of dependent default loans
Problem 9.1 The joint Bernoulli default distribution
9.7 Credit Granting
Example: Credit Granting and Creditor's Risks
Example: A Bayesian default model
Example: A Financial Approach
Example: An Approximate Solution
Problem 9.2 The rate of return of loans
9.8 The Reduced Form (Financial) Model
Example: Calculating the spread of a default bond
Example: The Loan Model Again
Example: Pricing default bonds
Example: Pricing default bonds and the hazard rate
9.9 Examples
Example: The bank interest rate on a house loan
Example: Buy insurance to protect the portfolio from loan defaults
Example: Use the portfolio as an underlying and buy or sell derivatives on this underlying
Problem: Lending rates of returnsT.S. Ho and E.O. Vieira
9.10 Credit Risk and Collaterals Pricing
Example: Hedge funds rates of returns
Example: Equity Linked Life Insurance
Example: Default and the price of homes
Example: A banks profit from a loan
9.11 Risk Management and Leverage
Summary
Test Yourself
References
Chapter 10 Multi-Names and Credit Risk Portfolios
Overview
10.1 Introduction
10.2 Credit Default Swaps
Example: Total Returns Swaps
Example: Pricing a project launch
10.3 Credit Derivatives: A Historical Perspectives 1.
10.4 CDOs: Examples and Models
Example: Collateralized Mortgage Obligations (CMOs)
Example: Insurance and Risk Layering
Example: A CDO with numbers
Example: The CDO and SPVBNP Paribas and France)
Example: A Synthetics CDO
Example: A Portfolio of Loans, VaR and the Normal Approximation
Example: Insurance and Reinsurance and Stop/Excess Loss Valuation
10.5 Constructing a Credit Risk Portfolio and CDOs
Example: A Simple Portfolio of Loans
Example: Random and Dependent Default
Example: The KMV Loss Model
Summary
Test Yourself
References
Chapter 11 Engineered Implied Volatility and Implied Risk Neutral Distributions
Overview
11.1 Introduction
11.2 The Implied Risk Neutral Distribution
Example: An Implied Binomial Distribution
Example: Calculating the implied risk neutral probability
11.3 The Implied Volatility
Example: The implied volatility in a lognormal process
11.4 Implied Distributions: Parametric Models
Example: The Generalized Beta of the second kind
11.5 A-parametric Approach and the Black-Scholes Model
Example: The Shimko technique
11.6 The Implied Risk Neutral Distribution and Information Discrimination
Example: Entropy in discrete states
Example: Discrimination Information and the Binomial Distribution
Problem 11.1 The Lognormal model and discrimination information
11.7 The Implied Risk Neutral Distribution and its Implied Utility
Example: Discrimination Information as a utility objective
Summary
Appendix A The Implied Volatility-The Dupire Model
Test Yourself
References
Acknowledgments
About the Author
Index