Multi-Asset Risk Modeling

Multi-Asset Risk Modeling

Techniques for a Global Economy in an Electronic and Algorithmic Trading Era

1st Edition - December 3, 2013

Write a review

  • Authors: Morton Glantz, Robert Kissell
  • Hardcover ISBN: 9780124016903
  • eBook ISBN: 9780124016941

Purchase options

Purchase options
Available
DRM-free (PDF, Mobi, EPub)
Sales tax will be calculated at check-out

Institutional Subscription

Free Global Shipping
No minimum order

Description

Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management. Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the 2008 financial crisis and talks about current and future banking regulation. Importantly, it also explores algorithmic trading, which currently receives sparse attention in the literature. By giving coherent recommendations about which statistical models to use for which asset class, this book makes a real contribution to the sciences of portfolio management and risk management.

Key Features

  • 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

Readership

Undergraduate and graduate students, professors, and professionals working with financial risk management techniques who want reference information about theoretical models and applications.

Table of Contents

  • 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

Product details

  • No. of pages: 544
  • Language: English
  • Copyright: © Academic Press 2013
  • Published: December 3, 2013
  • Imprint: Academic Press
  • Hardcover ISBN: 9780124016903
  • eBook ISBN: 9780124016941

About the Authors

Morton Glantz

Morton Glantz
Professor Morton Glantz serves as a financial consultant, educator, and adviser to a broad spectrum of professionals, including corporate financial executives, government ministers, privatization managers, investment and commercial bankers, public accounting firms, members of merger and acquisition teams, strategic planning executives, management consultants, attorneys, and representatives of foreign governments and international banks. Professor Morton Glantz is a principal of Real Consulting and Real Options Valuation, firms specializing in risk consulting, training, certification, and advanced analytical software in the areas of risk quantification, analysis, and management solutions.

As a JP Morgan Chase (heritage bank) senior banker, Professor Glantz built a progressive career path specializing in credit analysis and credit risk management, risk grading systems, valuation models, and professional training. He was instrumental in the reorganization and development of the credit analysis module of the Bank’s Management Training Program-Finance, which at the time was recognized as one of the foremost training programs in the banking industry.

Professor Glantz is on the (adjunct) finance faculty of the Fordham Graduate School of Business. He has appeared in the Harvard University International Directory of Business and Management Scholars and Research, and has earned Fordham University Deans Award for Faculty Excellence on three occasions. He is a Board Member of the International Standards Board, International Institute of Professional Education and Research (IIPER). The IIPER is a global institute with partners and offices around the world, including the United States, Switzerland, Hong Kong, Mexico, Portugal, Singapore, Nigeria, and Malaysia. Professor Glantz is widely published in financial journals and has authored 8 books.

Affiliations and Expertise

Lecturer in Finance & Business Economics, Fordham Graduate School of Business, New York, NY, USA

Robert Kissell

Robert Kissell, Ph.D., is President of Kissell Research Group, a global financial and economic consulting firm specializing in quantitative modeling, statistical analysis, and algorithmic trading. He is also a professor at Molloy College in the School of Business and an adjunct professor at the Gabelli School of Business at Fordham University. He has held several senior leadership positions with prominent bulge bracket investment banks including UBS Securities where he was Executive Director of Execution Strategies and Portfolio Analysis, and at JP Morgan where he was Executive Director and Head of Quantitative Trading Strategies. He was previously at Citigroup/Smith Barney where he was Vice President of Quantitative Research, and at Instinet where he was Director of Trading Research. He began his career as an Economic Consultant at R.J. Rudden Associates specializing in energy, pricing, risk, and optimization. Dr. Kissell has written several books and published dozens of journal articles on Algorithmic Trading, Risk, and Finance. He is a coauthor of the CFA Level III reading titled “Trade Strategy and Execution,” CFA Institute 2019.”

Affiliations and Expertise

President, Kissell Research Group; Professor, Molloy College; Adjunct Professor, Fordham University

Ratings and Reviews

Write a review

There are currently no reviews for "Multi-Asset Risk Modeling"