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.
- 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
Undergraduate and graduate students, professors, and professionals working with financial risk management techniques who want reference information about theoretical models and applications.
About The Authors
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
Chapter 2. A Primer on Risk Mathematics
Regression Analysis Statistics
Matrix Algebra Techniques
Linear Regression: Graphic Example
Log-Linear Regression Model
Log-Transformation: Graphic Example
Non-Linear Regression Model
Extreme Value Functions
Probability Distribution Functions
Continuous Distribution Functions
Extreme Value Functions
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
Chapter 4. Price Volatility
What is Volatility?
Market Observations: Empirical Findings
Forecasting Stock Volatility
Chapter 5. Factor Models
Degrees of Freedom
Types of Factor Models
Chapter 6. Equity Derivatives
Alternative Option Pricing Models
Chapter 7. Foreign Exchange Market and Interest Rates
How Much Does the FX Market Trade?
Foreign Exchange Markets
Exchange Rate Determinates
FX Quoting Conventions
Purchasing Power Parity (PPP)
Law of One Price
Balance of Payments Model
Asset Market Model
Interest Rate Parity
Uncovered Interest Arbitrage
Covered Interest Arbitrage
Time Value of Money
Market Observations and Analysis
Chapter 8. Algorithmic Trading Risk
Recent Growth in Algorithmic Trading
Classifications of Algorithms
Types of Algorithms
Algorithmic Trading Trends
Trading Venue Classification
Types of Orders
Algorithmic Decision-Making Process
The New Equity Exchange Environment
Trading Cost Equations
Trading Risk Components
Volume Forecasting Techniques
Trading Risk: Covariance Matrix
Chapter 9. Risk-Hedging Techniques
Dollar Hedge Value
Optimal Hedge Ratio
CAPM Dollar Value Hedging Technique
Chapter 10. Rating Credit Risk: Current Practices, Model Design, and Applications
Modeling Corporate Credit Risk
Specialized Lending Risk Models
Appendix. Corporate Risk Rating: Obligor and Facility Grade Requisites
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
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
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
Economic Capital and Value at Risk Illustrations
Efficient Portfolio Allocation and Economic Capital VaR
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
- No. of pages:
- © Academic Press 2014
- 16th December 2013
- Academic Press
- eBook ISBN:
- Hardcover ISBN:
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.
Lecturer in Finance & Business Economics, Fordham Graduate School of Business, New York, NY, USA
Dr. Robert Kissell is the president and founder of Kissell Research Group. He has over twenty years of experience specializing in economics, finance, math & statistics, risk, and sports modeling.
Dr. Kissell is author of the leading industry books, “The Science of Algorithmic Trading & Portfolio Management,” (Elsevier, 2013), “Multi-Asset Risk Modeling” (Elsevier, 2014), and “Optimal Trading Strategies,” (AMACOM, 2003). He has published numerous research papers on trading, electronic algorithms, risk management, and best execution. His paper, “Dynamic Pre-Trade Models: Beyond the Black Box,” (2011) won Institutional Investor’s prestigious paper of the year award.
Dr. Kissell is an adjunct faculty member of the Gabelli School of Business at Fordham University and is an associate editor of the Journal of Trading and the Journal of Index Investing. He has previously been an instructor at Cornell University in their graduate Financial Engineering program.
Dr. Kissell has worked with numerous Investment Banks throughout his career including UBS Securities where he was Executive Director of Execution Strategies and Portfolio Analysis, and at JPMorgan 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.
During his college years, Dr. Kissell was a member of the Stony Brook Soccer Team and was Co-Captain in his Junior and Senior years. It was during this time as a student athlete where he began applying math and statistics to sports modeling problems. Many of the techniques discussed in “Optimal Sports Math, Statistics, and Fantasy” were developed during his time at Stony Brook, and advanced thereafter. Thus, making this book the byproduct of decades of successful research.
Dr. Kissell has a Ph.D. in Economics from Fordham University, an MS in Applied Mathematics from Hofstra University, an MS in Business Management from Stony Brook University, and a BS in Applied Mathematics & Statistics from Stony Brook University.
Robert Kissell, PhD, 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 currently an adjunct faculty member of the Gabelli School of Business at Fordham University, and has held several senior leadership positions with prominent bulge bracket Investment Banks.
"…explains 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….focuses on the application of proper volatility and factor models, optimization techniques, and the evaluation of traditional and nontraditional sources of risk."--ProtoView.com, March 2014
"The financial crisis has shown that measurement and control of financial risks is a crucial task for a financial institution that cannot be delegated to a few specialists in the quant department. This very readable book provides a good introduction to many hot issues in financial risk management at a level accessible to the non-specialist."--Ruediger Frey, Wirtschaftsuniversität Wien
"Multi-Asset Risk Modeling presents a comprehensive overview and summary of methods employed in finance. The statistical methods based on real-world examples provide a practical introduction for students, and the book is a valuable source for financial engineering and risk management tools as well."--Alois Pichler, Universität Wien
"The text offers an up-to-date and practical coverage of a wide range of topics in risk modeling and risk management, representing a good source for both students and practitioners."--Giorgio Fazio, Università degli Studi di Palermo