Modeling Sovereign Risk. Part 2: Quantification
“The Bloomberg sovereign risk model starts by dividing countries into two types,” said Rajan Singenellore, “reserve-currency countries and non-reserve currency countries. Everything else depends on that distinction.” Singenellore is Product Manager, Risk & Valuations at Bloomberg and was the second of two speakers to address a GARP webinar audience on September 12, 2013. A reserve-currency country is one whose currency is held in significant quantities by other governments as part of their foreign exchange reserves, such as the US and the Japan. There is a pressing need for quantification in the area of sovereign credit risk, he said, citing as […]
Modeling Sovereign Risk. Part 1: Emerging Markets
“Country-specific factors such as government debt and the sovereign credit rating change slowly but global aggregates such as the risk appetite change quickly, thus leading to confusion the part of observers,” said Michael Rosenberg, Foreign Exchange Consultant, Bloomberg and author of Currency Forecasting: A Guide to Fundamental and Technical Models of Exchange Rate Determination. He was the first of two speakers to address a GARP webinar audience on September 12, 2013. Much of Rosenberg’s talk focused on the sovereign credit risk of emerging markets (EM), because the accelerating flow of net private capital into EM from 1980-2014 has been unprecedented. […]
Quant Chalkboard: A New Way to Aggregate
The Gumbel copula is the best way to aggregate losses in economic capital, says Yimin Yang, Director of Model Risk and Capital Management Practice at Protiviti, a global consulting firm. “This copula has asymmetrical behaviour and can model fat tails the best” of the numerous copulas he has tried recently. He was speaking at a GARP webinar on August 20, 2013. Yang began by explaining that a copula was a broad class of mathematical function that could be used to describe the joint distribution function between two or more other functions. Such a joint cumulative distribution function (CDF) must determine […]
Risk Models: From Governance to Validation: Part 3. Examples
“The calculation of the spread on the tranches is quite involved but essentially boils down to dependencies between names,” said Frederic Siboulet, Principal at iEpsilon and the third of three speakers at a GARP webinar on risk models held June 11, 2013. The tranches in structured credit products he referred to were apparently diversified, but in reality not so. Siboulet chose to illustrate the subtle and embedded risk of models with actual structured product examples. In particular, he said that “We must not overlook the importance of the parameters and their interpretation.” The first example involved stressed correlation within a […]
Risk Models From Governance to Validation: Part 2. A Model of Model Management
No longer should a firm just use financial models; it should have a “model of model management,” said Donna Howe, Chief Risk Officer at Sovereign Bank. She was the second of three speakers at a June 11, 2013 webinar on risk models organized by the Global Association of Risk Professionals (GARP). Such a “meta-model” would help a firm sort and track models. Howe said that risk models must be understood within the wider frame of compliance and other non-prudential risk. Model parsimony, or Occam’s razor, that was recommended by the first speaker, is good but in the real world “cannot […]
Risk Models From Governance to Validation: Part 1. Don’t Forget the Story
The best practices of risk models–and model building–boil down to one thing: “we can’t forget the story behind it,” said Peter Went, VP, Banking Risk Management Programs at GARP. He was the first of three speakers at a GARP webinar on risk models held June 11, 2013. “There must always be a qualitative story expressible in quantitative terms.” And, vice versa, since any model reduces the complexities of the real world into snippets of mathematical relationships, the opposite must hold true. Went, a trained econometrist, described three main types of models. Fundamental models are based on rules relating basic variables […]
Monitoring Risk While Pursuing High Returns: The Importance of Being Quantitative
“A quantitative model provides a very different insight than a rating,” said Rajan Singenellore, Global Business Manager of Risk & Valuations at Bloomberg. Models are based on objective inputs and usually publicly available information, whereas ratings are based on subjective factors and inside information. Singenellore was speaking about quantitative models as the second part of a two-part webinar presentation “Monitoring Risk While Pursuing High Returns” on March 7, 2013 organized by the Global Association of Risk Professionals (GARP). “A quantitative model lets you understand risk drivers and sensitivities,” he said, such as the effects of input changes on default risk […]
Monitoring Risk While Pursuing High Returns: Who Pays the Piper?
“Rating biases affect how we think about methodologies,” said Elliot Noma, Managing Director at Garrett Asset Management. “A rating agency paid by the issuer will likely give the firm the benefit of the doubt,” whereas a rating agency paid by the investor might want to more stringently evaluate the firm. “Both evaluations have the risk of error” due to bias. Noma was speaking about evaluation of credit risk as part of the webinar presentation “Monitoring Risk While Pursuing High Returns” on March 7, 2013 organized by the Global Association of Risk Professionals (GARP). He began by dividing non-structured credit exposure […]
Managing Model Risk: Part 3. Collective Hubris
There are more things in heaven and earth, Horatio, Than are dreamt of in your philosophy. – Wm. Shakespeare, Hamlet, Act 1, Scene 5. “We are building the language in which to discuss model risk,” said Boris Deychman, Director of Model, Market and Operational Risk Management at RBS Citizens Financial Group. He drew an analogy with the world of wine experts, who have developed specific vocabulary to talk about aroma and taste. “They don’t say just: this tastes like wine.” Deychman was the third and final speaker of a panel invited by the Global Association of Risk Professionals to discuss […]
Managing Model Risk: Part 2. The Impact of Basel III
“More consideration must be made for regulatory capital changes that focus on small but potentially devastating risks or risk factors,” said Peter Went, VP, Banking Risk Management Programs at GARP. He was speaking about Basel III and its impact on modelling regulatory capital at a webinar on January 29, 2013, organized by the Global Association of Risk Professionals to discuss model risk management. Went mentioned three developments in the Basel III that directly impact capital models and model risk in regulatory capital determination. First, Basel III introduces a risk-invariant leverage ratio of 3 percent in recognition that models may be […]