Massimo morini a guide to the validation and risk management of quantitative models used for pricing and hedging whereas the majority of quantitative finance books focus on mathematics and risk management books focus on regulatory aspects, this book addresses the elements missed by this literaturethe risks of the models themselves. Model risk should be managed like other type risks o. In this article, we explore the evolution of model risk, including regulatory drivers and industry challenges. Model risk in finance is defined as the risk of financial loss resulting from the use of financial models. At times, debated issues cannot be resolved easily and there is no clear escalation path to reach a conclusion failing a model causes signi. Applying erm principles and techniques to the risk of loss due to model risk. For example, a neanderthal confronting a saber toothed tiger faced risk despite there being no concept of probability at that time. He has more than 10 years of experience in areas that span from risk regulation, enterprise risk. Massimo morini at universita commerciale luigi bocconi.
Elevating enterprise resiliency practices to combat todays business challenges and disruptions. Request pdf on jun 1, 2012, michael verhofen and others published massimo morini. Fed in 201112, which, for the first time, accurately defined model risk and provided a set of guidelines establishing the need for entities to develop a boardapproved framework to identify and manage this risk though not necessarily quantify it. The three lines of defense frameworkwhich comprises ownership, controls, and compliancehelps ensure that risk management is part of the overall process and work culture, rather than just. Apr 18, 2014 model risk, which is the potential for different models to provide inconsistent outcomes, is shown to be increasing with market uncertainty. Risk management might be delegated to the audit or risk committee, but it is likely.
Here we point out an element of model risk that appears to be overlooked. Adopting an enterprise approach to model risk management disclaimer the following is intended to outline our general product direction. Factor models for asset returns and interest rate modelsand interest rate models scottish financial risk academy, march 15, 2011 eric zivot robert richards chaired professor. However, the disagreement between the various candidate models increases. Whereas the majority of quantitative finance literature focuses. Specific to otc derivativesthe model risk associated with using a possibly incorrect valuation.
Miles ravitz is a lead consultant within the risk and compliance practice of capgemini financial services. Whereas the majority of quantitative finance literature focuses on mathematics and numerical implementation, and conversely, books about risk management focus on the regulatory and bureaucratic aspects and lack in quantitative details, this book will. Organizational strategy, business models, and risk management. Specifically, it adopts the practice of managing inherent model risk. Model risk, 2018 a practitioners point of view people. Dr morini is a professor of fixed income at bocconi university and was research fellow at cass business school of london city university. Something happens in the reality of the markets that reveals an element of unrealism of the model to be more relevant than previously. The model can be created by writing code in a programming language.
Daring to open up the black box institute and faculty of. A valueatriskbased model is proposed to compute the. Jul 08, 2014 indeed, risk is a more fundamental notion than is probability. In reality all quants should remember the following the following famous quote by george e. Numerix model risk management independent, transparent, trusted as per key regulations such as the basel committee on banking supervision directive 21 and solvency ii, financial institutions are required to quantify model risk. Using models for risk analysisa risk analysis model could be a physical scale model, but it is most often a mathematical model. A practical guide for quants, traders and validators by massimo morini 20111107 massimo morini on. Model risk of risk models refers b oth to the range of risk estimates as well as the inability to forecast properly risk realizations. The most thoughtful and yet practical book ive seen on dealing with model risk. The office of the comptroller of the currency occ has adopted the attached supervisory guidance on model risk management. A practical guide for quants, traders and validators by massimo morini.
In finance, model risk is the risk of loss resulting from using insufficiently accurate models to make decisions, originally and frequently in the context of valuing financial securities. Understanding and managing model risk morini massimo. Specifically, it adopts the practice of managing inherent model risk at the source the assignment of model risk management responsibilities to model developers, owners and users. At times, debated issues cannot be resolved easily and there is no clear escalation path to reach a conclusion. Model risk is the risk of occurrence of a significant difference between the marktomodel value of a complex andor illiquid instrument, and the price at which the same instrument is revealed to have traded in the market. Factor models for asset returns and interest rate modelsand interest rate models scottish financial risk academy, march 15, 2011 eric zivot robert richards chaired professor of economicsrobert richards chaired professor of economics adjunct professor, departments of applied mathematics, finance and statistics. It is crucial for senior management to instill a strong risk culture supported by a sound model risk management framework. Functional correlation approach to operational risk in banking organizations. Rantala 2006 mentions that in the face of model risk, rather than to base decisions on a single selected best model, the modeller can base his inference on an entire set of models by using model averaging. Model risk management14 published by the occ and the u. A practical guide for quants, traders and validators brings together a wide range of detailed real world examples, quantitative analysis and regulatory issues. Integrate webenabled corporate risk registers with project schedule risk and analysis in microsoft excel using monte carlo simulation. The value approach model risk is the risk that the model is not a realistic or at least plausible description of the factors that affect the derivatives value by e. Model risk increases with greater model complexity, higher uncertainty about inputs and assumptions, broader use, and larger potential impact.
When the gaussian copula is applied to the computation of the probability of losses concentrated in time, it can give paradoxical. A practical guide for quants, traders and validators, by massimo morini, examines the risks arising. In spite of increased awareness of pricing model uncertainty, and its consequences. It is intended for information purposes only, and may not be incorporated into any contract. The usefulness of such a framework for preventing losses associated with model risk is demonstrated through case studies. The fact that the topic of model risk regularly shows up in actuarial papers and presentations supports wilmotts sentiment. Applies to all models not just models used in erm but also capital models, reserving models, underwriting models, pricing models. Risk is a human experience an experience of any cognizant being, actually that predates that invention. One more model risk when using gaussian copula for risk management. Emanuel derman, professor at columbia university, former head of quantitative risk management at goldman sachs, and author models. In this paper we deal with the management and measurement of model risk. A guide to the validation and risk management of quantitative models used for pricing and hedging whereas the majority of quantitative finance books focus on mathematics and risk management books focus on regulatory aspects, this book addresses the elements missed by this literaturethe risks of the models themselves. It investigates the interaction between mathematics and the reality of markets, including the explanation of model errors and misunderstandings. This book starts from regulatory issues, but translates them into practical.
A practical guide for quants, traders and validators by massimo morini 20111107. This guidance, developed jointly with the board of governors of the federal reserve system, articulates the elements of a sound program for effective management of risks that arise when using quantitative models in bank decision making. Model risk depends hugely on every selected model the application of solvency ii will speed up the study of model risk need of a precise approach to quantify this risk all models are wrong, but some are. We have a broad and deep team of model risk professionals whose experience covers virtually all financial model types, including those used to manage credit risk, market risk, operational risk and compliance riskas well as those used for financial. So lets explore the concept of model risk a little more deeply. Quantify model risk carefully, and with considerable thought choose models that might describe the distribution of possible outcomes. Organizational strategy, business models, and risk. Gaussian copula as a model for default correlation has been recently criticized for a. He has spent the last ten years inventing new models, implementing them, and helping practitioners in using them for buying, selling, and he. We are well qualified to deliver industryleading model risk management services. We examine model risk management methodologies, using. A model governance program provides the framework, oversight, and. Massimo morini author massimo morini is head of credit models and coordinator of model research at imi bank of intesa san paolo.
Bankf s should identify the sources of risk and assess the magnitude. Highly experienced team of model risk management specialists. Mathematical finance, and the journal of derivatives, and is the author of understanding and managing model risk. Understand, analyze, control and monitor the risks that drive your. During the most recent operational risk erm audio conference, elizabeth mays, chief model risk officer at pnc, discussed the importance of model risk management in finance and provided important points of guidance that banks should consider as they develop and use models. Models of risk management in organisations 11 trolled way, undertake a higher risk than an average company from the same business areai. The merton model is only a starting point for studying credit risk, and is obviously far from realistic. Actuarial risk modeling process 1 model costs process at the individual levelmodeling of loss distributions 2 aggregate risks at the collective levelrisk theory 3 determine revenue. In this paper, we analyze model risks separately in pricing models and risk measurement models as follows. This is the meaning of model risk that i intend to cover in this chapter. Understanding and managing model risk is a guide to the validation and risk management of quantitative models used for pricing and hedging. Understand, analyze, control and monitor the risks that drive your business. An effective risk management framework is built on four essential elements. Derman you may have not taken into account all the factors that affect valuation.
Assign prior probabilities to each model with bayes theorem, calculate the posterior probability of each model given the data you have. Geske 10 extended the merton model to the case of bonds of di. A practical guide for quants, traders and validators. Blog 6 key considerations for model risk management rma. First, a model risk framework is developed, adapting concepts such as risk appetite, monitoring, and mitigation to the particular case of model risk. The nonstationary structure of the debt that leads to the termination of operations on a. Understanding and managing model risk wiley online books. Integrated range of quantitative risk analysis and management software products, supported by consulting and training services. Understanding and managing model risk by massimo morini. Model risk depends hugely on every selected model the application of solvency ii will speed up the study of model risk need of a precise approach to quantify this risk all models are wrong, but some are useful georges box. During calm periods, the underlying risk forecast models produce similar risk readings. Massimo morini has provided a comprehensive and practical book on model risk that well covers the practitioners needs in these postcreditcrisis times. Models by their nature are simplifications of reality, and realworld events may prove those simplifications inappropriate. The model can be created by writing code in a programming language, statements in a simulation modeling language, or formulas in a microsoft excel spreadsheet.
Massimo morini is head of interest rate and credit models at imi bank of intesa san paolo, where he is also coordinator of model research. As a result, model risk is increasingly on every risk managers radar. Scenaroi s were usuay lll mi tied to observed events, and there was ltitle motivation for more. During the most recent operational riskerm audio conference, elizabeth mays, chief model risk officer at pnc, discussed. When the gaussian copula is applied to the computation of the probability of losses concentrated in time, it can give paradoxical and misleading results, where an increase of correlation reduces the model probability of loss concentration. First, a model risk framework is developed, adapting concepts such as risk appetite, monitoring, and mitigation to the. This framework incorporates recent trends in model risk management. Massimo morini, understanding and managing model risk. Fed in 201112, which, for the first time, accurately defined model risk and provided a set of guidelines establishing the need for entities to. Quantitative approaches model averaging vs worstcase approach. Banks should consider risk from individual models and in the aggregate. Model risk of risk models by jon danielsson, kevin r. Quantifying correlation uncertainty risk in credit derivatives. Dr massimo morini is currently head of interest rates, credit and inflation models at banca imi intesa sanpaolo where he is also responsible for coordinating model research.
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