Charles S. Tapiero

Risk Finance and Asset Pricing (eBook, ePUB)

Value, Measurements, and Markets

• Format: ePub

Produktbeschreibung

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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 478
• Erscheinungstermin: 4. Oktober 2010
• Englisch
• ISBN-13: 9780470892381
• Artikelnr.: 37300046

Autorenporträt

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.

Inhaltsangabe

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 returns (T.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. 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 SPV (BNP
Paribas, 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.