"As a technically trained analyst, Marcelo Cruz summarizes a wide range of mathematical techniques. As an experienced capital markets trader and risk manager, he provides real world examples of their relevance for operational risk. This will be a common reference work in the field for years to come." David M. Rowe, Ph.D., Group Executive Vice President for Risk Management Sun Gard Trading and Risk Systems
Operational risk is an important, yet little explored, area within risk management. The need to model and measure the risks arising from operational errors and to allocate capital against them will be soon become a regulatory requirement for financial institutions. In this book, Marcelo Cruz provides a quantitative look at the subject, presenting several mathematical models that can be used and adapted to measure, manage and hedge operational risk.
Based on the author′s extensive experience, the book maps out state–of–the–art mathematical and statistical techniques that can be used to model operational risk. In addition, the book describes a variety of appropriate models that can be applied to specific structures or areas, including operational risk database modeling, stochastic models, statistical distributions for frequency and severity, extreme value theory, operational VaR models, artificial intelligence models, dynamic multifactor models, Bayesian analysis, Monte Carlo simulation, stress test/ scenario analysis, real options, state–space models and the Kalman filter, Markovian stochastic models and others. These models have been tested with real data in real operational events. Based on this experience, numerous examples are sited throughout.
Modeling, Measuring and Hedging Operational Risk provides a complete quantitative reference for all those involved in modeling and managing operational risk as well as for those involved with developing hedging products for operational risk within insurance companies and derivatives houses.
PART I: DATABASE MODELING
PART II: STOCHASTIC MODELING
Extreme Value Theory
The Operational Risk VaR
Stochastic Processes in Operational Risk
PART III: CAUSAL MODELS
Causal Models : Applying Econometrics and Time Series Statistics to Operational Risk
Non–Linear Models in Operational Risk
Bayesian Techniques in Operational Risk
PART IV: OPERATIONAL RISK MANAGEMENT
Operational Risk Reporting, Control and Management
– Stress Tests and Scenario Analysis in Operational Risk
PART V: HEDGING OPERATIONAL RISK
Operational Risk Derivatives
Developing an OR Hedging Program
PART VI: OPERATIONAL RISK REGULATORY CAPITAL
Operational Risk Regulatory Capital
PART VII: MEASURING "OTHER RISKS" –
FOREGONE REVENUE MEASUREMENT MODELS
An Enterprise–Wide Model for Measuring Reputational Risk
– Measuring Concentration (or Key Personnel) Risk
– Using Real Options in Modeling and Measuring Operational and ′Other′ Risks
Valuing Networks –
Understanding the basics of e–ventures valuation
Dr Cruz regularly writes for several academic and industry journals and magazines including The Journal of Risk, RISK magazine, the Financial Times and Derivatives Week. He has also contributed to several risk management books, the most recent of which include ′Extremes and Integrated Risk Management′, ′Managing Hedge Fund Risk′, ′Mastering Risk, Volume 2′ and ′Advances in Operational Risk: Firmwide Issues for Financial Institutions′. Dr Cruz is a sought–after speaker in risk management conferences and seminars and had lectured in many countries in Europe, Asia and the Americas as well as leading universities in Europe, USA and Latin America. He holds a Ph.D. in Mathematical Finance, a M.Sc., M.B.A., Diploma and a B.Sc. in Economics.