The VaR Modeling Handbook: Practical Applications in Alternative Investing, Banking, Insurance, and Portfolio Management

by Gregoriou, Greg

• ISBN13: 9780071625159
• ISBN10: 0071625151
• Edition: 1st
• Format: Hardcover
• Copyright: 2009-06-02
• Publisher: McGraw-Hill Education

Summary

Value-at-Risk (VaR) is a powerful toolfor assessing market risk in real timea critical insight when making trading andhedging decisions.The VaR Modeling Handbookis the most complete, up-to-date reference onthe subject for today's savvy investors, traders,portfolio managers, and other asset and riskmanagers.Unlike market risk metrics such as the Greeks,or beta, which are applicable to only certainasset categories and sources of market risk,VaR is applicable to all liquid assets, makingit a reliable indicator of total market risk. Forthis reason, among many others, VaR has becomethe dominant method for estimatingprecisely how much money is at risk each dayin the financial markets.The VaR Modeling Handbookis a profoundvolume that delivers practical informationon measuring and modeling risk specificallyfocused on alternative investments, banking,and the insurance sector. The perfect primertoThe VaR Implementation Handbook(McGraw-Hill), this foundational resource features The experience of 40 internationallyrecognized experts Useful perspectives from a widerange of practitioners, researchers,and academics Coverage on applying VaR to hedgefund strategies, microcredit loanportfolios, and economic capitalmanagement approaches for insurancecompaniesEach illuminating chapter inThe VaR ModelingHandbookpresents a specific topic, completewith an abstract and conclusion for quick reference, as well as numerous illustrations thatexemplify covered material. Practitioners cangain in-depth, cornerstone knowledge of VaRby reading the handbook cover to cover ortake advantage of its user-friendly format byusing it as a go-to resource in the real world.Financial success in the markets requires confidentdecision making, andThe VaR ModelingHandbookgives you the knowledge you needto use this state-of-the-art modeling methodto successfully manage financial risk.

Author Biography

Greg N. Gregoriou is professor of.finance in the School of Business and Economics at State.University of New York (Plattsburgh), the author of 25 books,.he is also co-editor and editorial board member for multiple.peer-reviewed journals..

Table of Contents

Editor	p. xi
Contributors	p. xviii
Alternative Investments And Optimization
Asset Allocation for Hedge Fund Strategies: How to Better Manage Tail Risk	p. 3
Introduction	p. 3
Downside Risk and Risk Allocation	p. 6
Modeling Hedge Fund Return Distributions	p. 11
Optimal Hedge Fund Allocations	p. 21
Conclusion	p. 27
Mean-CVaR Optimization	p. 28
References	p. 29
Estimating Value at Risk of Institutional Portfolios with Alternative Asset Classes	p. 33
Introduction	p. 34
Data	p. 36
Descriptive Statistics	p. 39
Methodology	p. 40
Asset Return Distribution	p. 45
Generating Future Asset Return Scenarios	p. 46
Value at Risk and Conditional Value at Risk	p. 46
Results	p. 47
Conclusion	p. 52
References	p. 53
A Comparison between Optimal Allocations Based on the Modified VaR and Those Based on a Utility-Based Risk Measure	p. 55
Introduction	p. 55
Optimization Models	p. 56
Empirical Method	p. 61
Empirical Results	p. 62
Conclusion	p. 69
References	p. 69
Using CVaR to Optimize and Hedge Portfolios	p. 71
Introduction	p. 71
Measuring Risk (Coherent Risk Measures)	p. 72
Spectral Risk Measures	p. 73
Problems with Using VaR	p. 79
Value at Risk, CVaR, and the Optimal Capital Allocation	p. 81
Optimizing a Portfolio Using CVaR	p. 85
A Numerical Example	p. 86
Conclusion	p. 92
References	p. 94
Banking And Insurance Sector Applications
Value at Risk, Capital Standards, and Risk Alignment in Banking Firms	p. 97
Introduction	p. 98
Target Solvency and Value at Risk	p. 99
Bank Risk Preference Function	p. 102
Risk Ranking Criteria	p. 103
Compatibility of Risk Measures with Stochastic Dominance Criteria	p. 107
Risk Measures	p. 112
Example	p. 115
Conclusion	p. 119
References	p. 120
The Asset-Liability Management Compound Option Model: A Public Debt Management Tool	p. 123
Introduction	p. 123
Conceptual Foundations of the Model	p. 125
The Government Balance Sheet and Net Worth	p. 127
The ALM Compound Option Model	p. 129
An Example: Risk Analysis of New Zealand's Government Debt	p. 134
Extensions of the ALM Compound Option Model	p. 140
Conclusion	p. 143
References	p. 143
A Practitioner's Critique of Value-at-Risk Models	p. 147
Introduction	p. 147
Definition of VaR	p. 148
Data	p. 151
Case 1 One Linear Asset with Normal and Nonnormal Returns	p. 155
Case 2 Many Linear Asset with Normal and Nonnormal Returns	p. 160
The Nonstationarity of the Probability Distribution	p. 166
Case 3 Nonlinear Assets	p. 169
System Implementation and Conclusion	p. 178
References	p. 180
Value at Risk for a Microcredit Loan Portfolio: An African Microfinance Institution Case Study	p. 183
Introduction	p. 183
Literature Review	p. 185
Exploratory Data Analysis	p. 186
Value-at-Risk Modeling	p. 191
Conclusion	p. 194
List of Loan Characteristics in the Database	p. 196
Problem Loan Statistics with Various Factors	p. 197
References	p. 198
Allocation of Economic Capital in Banking: A Simulation Approach	p. 201
Introduction	p. 201
The Model	p. 204
Conclusion	p. 221
References	p. 224
Using Tail Conditional Expectation for Capital Requirement Calculation of a General Insurance Undertaking	p. 227
Introduction	p. 228
The Model	p. 229
Application	p. 237
Results	p. 245
Conclusion	p. 248
References	p. 250
Economic Capital Management for Insurance Companies	p. 253
Introduction	p. 253
Copula Functions and Dependence Structures	p. 255
Loss Ratio Modeling and Risk Measures	p. 259
Numerical Example	p. 261
Conclusion	p. 265
References	p. 266
Solvency II: An Important Case in Applied VaR	p. 267
Introduction	p. 268
Solvency II and QIS3	p. 271
Case Study	p. 285
Conclusion	p. 291
Acknowledgments	p. 292
References	p. 292
Portfolio Management
Quantile-Based Tail Risk Estimation for Equity Portfolios	p. 297
Introduction	p. 297
Risk Measures	p. 300
Modeling Procedure	p. 301
Data Description	p. 303
Empirical Findings	p. 307
Conclusion	p. 311
Acknowledgments	p. 312
References	p. 312
Optimal Mixed-Asset Portfolios	p. 315
Introduction	p. 316
Risk-Return Profiles of Alternative Investments	p. 318
Data Set Description	p. 326
Methodology	p. 330
Empirical Results	p. 334
Conclusion	p. 340
References	p. 341
Value-at-Risk-Adjusted Performance for Structured Portfolios	p. 349
Introduction	p. 349
The Opportunity Set	p. 352
An Equity-Linked Bond	p. 355
Computation of Results	p. 362
Findings	p. 365
Conclusion	p. 373
References	p. 374
Index	p. 375
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