Vinod / Reagle Preparing for the Worst

Incorporating Downside Risk in Stock Market Investments
1. Auflage 2004
ISBN: 978-0-471-68651-4
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 320 Seiten, E-Book

Reihe: Wiley Series in Probability and Statistics

A timely approach to downside risk and its role in stock marketinvestments
When dealing with the topic of risk analysis, most books oninvestments treat downside and upside risk equally. Preparing forthe Worst takes an entirely novel approach by focusing on downsiderisk and explaining how to incorporate it into investmentdecisions. Highlighting this asymmetry of the stock market, theauthors describe how existing theories miss the downside and followwith explanations of how it can be included. Various techniques forcalculating downside risk are demonstrated.
This book presents the latest ideas in the field from the groundup, making the discussion accessible to mathematicians andstatisticians interested in applications in finance, as well as tofinance professionals who may not have a mathematical background.An invaluable resource for anyone wishing to explore the criticalissues of finance, portfolio management, and securities pricing,this book:
* Incorporates Value at Risk into the theoretical discussion
* Uses many examples to illustrate downside risk in U.S.,international, and emerging market investments
* Addresses downside risk arising from fraud and corruption
* Includes step-by-step instructions on how to implement themethods introduced in this book
* Offers advice on how to avoid pitfalls in calculations andcomputer programming
* Provides software use information and tips

Autoren/Hrsg.

Vinod, Hrishikesh (Rick)

Reagle, Derrick

Inhaltsverzeichnis

List of Figures.
List of Tables.
Preface.
1. Quantitative Measures of the Stock Market.
1.1. Pricing Future Cash Flows.
1.2. The Expected Return.
1.3. Volatility.
1.4. Modeling of Stock Price Diffusion.
1.5. Efficient Market Hypothesis.
Appendix: Simple Regression Analysis.
2. A Short Review of the Theory of Risk Measurement.
2.1. Quantiles and Value at Risk.
2.2. CAPM Beta, Sharpe, and Treynor Performance Measures.
2.3. When You Assume . . . .
2.4. Extensions of the CAPM.
Appendix: Estimating the Distribution from the Pearson Family ofDistributions.
3. Hedging to Avoid Market Risk.
3.1. Derivative Securities: Futures, Options.
3.2. Valuing Derivative Securities.
3.3. Option Pricing Under Jump Diffusion.
3.4. Implied Volatility and the Greeks.
Appendix: Drift and Diffusion.
4. Monkey Wrench in the Works: When the Theory Fails.
4.1. Bubbles, Reversion, and Patterns.
4.2. Modeling Volatility or Variance Explicitly.
4.3. Testing for Normality.
4.4. Alternative Distributions.
5. Downside Risk.
5.1. VaR and Downside Risk.
5.2. Lower Partial Moments (Standard Deviation, Beta, Sharpe,and Treynor).
5.3. Implied Volatility and Other Measures of Downside Risk.
6. Portfolio Valuation and Utility Theory.
6.1. Utility Theory.
6.2. Nonexpected Utility Theory.
6.3. Incorporating Utility Theory into Risk Measurement andStochastic Dominance.
6.4. Incorporating Utility Theory into Option Valuation.
6.5. Forecasting Returns Using Nonlinear Structures and NeuralNetworks.
7. Incorporating Downside Risk.
7.1. Investor Reactions.
7.2. Patterns of Downside Risk.
7.3. Downside Risk in Stock Valuations and WorldwideInvesting.
7.4. Downside Risk Arising from Fraud, Corruption, andInternational Contagion.
8. Mathematical Techniques.
8.1. Matrix Algebra.
8.2. Matrix-Based Derivation of the Efficient Portfolio.
8.3. Principal Components Analysis, Factor Analysis, andSingular Value Decomposition.
8.4. Ito's Lemma.
8.5. Creation of Risk-Free Nonrandom g(S,t) as a Hedge Portfolio.
8.6. Derivation of Black-Scholes Partial DifferentialEquation.
8.7. Risk-Neutral Case.
9. Computational Issues.
9.1. Sampling, Compounding, and Other Data Issues inFinance.
9.2. Numerical Procedures.
9.3. Simulations and Bootstrapping.
Appendix A: Regression Specification, Estimation, and SoftwareIssues.
Appendix B: Maximum Likelihood Estimation Issues.
Appendix C: Maximum Entropy (ME) Bootstrap for State-DependentTime Series of Returns.
10. What Does It All Mean?
Glossary of Greek Symbols.
Glossary of Notations.
Glossary of Abbreviations.
References.
Name Index.
Index.

Über Autor(innen)

HRISHIKESH D. VINOD, PhD, is Director of the Institute for Ethicsand Economic Policy and Professor of Economics at FordhamUniversity in New York. He is also a Fellow of the InternationalInstitute of Public Ethics and of the Journal of Econometrics.
DERRICK P. REAGLE, PhD, is Associate Chair for Graduate Studiesin the Department of Economics at Fordham University.