Multi-Asset Risk Modeling

Multi-Asset Risk Modeling

Last edition Elsevier Techniques for a Global Economy in an Electronic and Algorithmic Trading Era Finance students and professionals researching risk management tools and techniques currently use one reference for equity risk modeling, another for futures and derivatives, and yet others for credit markets, foreign exchange, and commodities. This single volume describes the latest and most advanced risk modeling techniques for all asset classes, including equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Foregrounding mathematics, the authors present standard risk-management and asset allocation models, discuss the laws in standard models that contributed to the 2008 financial crisis, and talk about current and future banking regulation. Importantly, they also explore algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, they make a real contribution to the sciences of portfolio management and risk management.

Last Edition

ISBN 13: 9780124016903

Imprint: Elsevier

Language: English

Authors: Morton Glantz

Pub Date: 01/2014

Pages: 544

Illus: Illustrated

Weight: 1,280.000 grams

Size: h 191 X 235 mm

Product Type: Hardcover

List Price
grn 2818
$ 95,52
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  • • Covers all asset classes
  • • Provides mathematical theoretical explanations of risk as well as practical examples with empirical data
  • • Includes sections on equity risk modeling, futures and derivatives, credit markets, foreign exchange, and commodities
  • Morton Glantz, Lecturer in Finance & Business Economics, Fordham Graduate School of Business, New York, NY, USA and Robert L. Kissell, President, Kissell Research Group and Adjunct Faculty Member, Gabelli School of Business, Fordham University
  • Dedication Preface About The Authors Acknowledgements
  • Chapter 1. Introduction to Multi-Asset Risk Modeling—Lessons from the Debt Crisis
  • Types of Risk Faulted Risk Models Financial Models Breaking Down in the Equity Markets Risk Models Breaking Down References
  • Chapter 2. A Primer on Risk Mathematics
  • Introduction Regression Analysis Regression Analysis Statistics Unbiased Estimators Matrix Algebra Techniques Estimate Parameters Linear Regression: Graphic Example Log-Linear Regression Model Log-Transformation: Graphic Example Non-Linear Regression Model Probability Models Probability Distributions Extreme Value Functions Descriptive Statistics Probability Distribution Functions Continuous Distribution Functions Extreme Value Functions Discrete Distributions Endnotes References
  • Chapter 3. A Primer on Quantitative Risk Analysis
  • A Brief History of Risk: What exactly is Risk? The Basics of Risk The Nature of Risk and Return Uncertainty Versus Risk Risk Simulation Applications Exercise 1: Basic Simulation Model Exercise 2: Correlation Effects Model Reference
  • Chapter 4. Price Volatility
  • Introduction What is Volatility? Volatility Measures Definitions Market Observations: Empirical Findings Forecasting Stock Volatility Conclusions References
  • Chapter 5. Factor Models
  • Introduction Data Limitations False Relationships Degrees of Freedom Factor Models Types of Factor Models Conclusion References
  • Chapter 6. Equity Derivatives
  • Introduction Option Contracts Alternative Option Pricing Models Futures Contracts Forwards Contract Swaps Contracts Conclusions Endnotes References
  • Chapter 7. Foreign Exchange Market and Interest Rates
  • Introduction How Much Does the FX Market Trade? Foreign Exchange Markets Exchange Rate Determinates Spot Market FX Quoting Conventions Bid-Ask Spreads Arbitrage Triangular Arbitrage Purchasing Power Parity (PPP) Law of One Price Balance of Payments Model Asset Market Model Interest Rate Parity Interest Arbitrage Uncovered Interest Arbitrage Covered Interest Arbitrage Interest Rates Time Value of Money Market Observations and Analysis Conclusion Endnotes References
  • Chapter 8. Algorithmic Trading Risk
  • Introduction Market Environment Recent Growth in Algorithmic Trading Classifications of Algorithms Types of Algorithms Algorithmic Trading Trends Trading Venue Classification Types of Orders Algorithmic Decision-Making Process High-Frequency Trading The New Equity Exchange Environment Trading Cost Equations Trading Risk Components Volume Forecasting Techniques Daily Volumes Trading Risk: Covariance Matrix Estimation Error Conclusion References
  • Chapter 9. Risk-Hedging Techniques
  • Introduction Definitions Hedge Ratio Dollar Hedge Value Optimal Hedge Ratio CAPM Dollar Value Hedging Technique Examples Conclusions References
  • Chapter 10. Rating Credit Risk: Current Practices, Model Design, and Applications
  • External Ratings Internal Ratings Modeling Corporate Credit Risk Specialized Lending Risk Models Appendix. Corporate Risk Rating: Obligor and Facility Grade Requisites References
  • Chapter 11. A Basic Credit Default Swap Model
  • Determining Probability of Default from Market Spreads Probability of Default and Recoveries Default and Survival Probabilities Present Value of the CDS Premiums Present Value of a Default Payment Calculating the CDS Spread Premium Other Considerations References
  • Chapter 12. Multi-Asset Corporate Restructurings and Valuations
  • Building Blocks of Valuation Stochastic Analysis of Multi-Asset Restructuring: A Banker’s Perspective Appendix A. Banker’s Guide: Valuation Appraisal of Business Clients References
  • Chapter 13. Extreme Value Theory and Application to Market Shocks for Stress Testing and Extreme Value at Risk
  • Value at Risk and Systemic Shocks Extreme Value Theory and Application to Market Shocks for Stress Testing and Extreme Value at Risk Technical Details Economic Capital and Value at Risk Illustrations Efficient Portfolio Allocation and Economic Capital VaR Conclusion References
  • Chapter 14. Ensuring Sustainability of an Institution as a Going Concern: An Approach to Dealing with Black Swan or Tail Risk
  • Sustainability Management is Critical to Weather a Crisis Tail Risk and Sustainability Management Need Explicit Focus Measurement is a Prerequisite to Effective Management Effective Tail Risk Management PML-Based Sustainability Management has Large Rewards Sustaining a Going-Concern Through Tail-Risk Management
  • References Index
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