Value-at-risk (VAR)
Using the grouped t-copula
Student-t copula models are popular, but can be over-simplistic when used to describe credit portfolios where the risk factors are numerous or dissimilar. Here, Stéphane Daul, Enrico De Giorgi, Filip Lindskog and Alexander McNeil construct a new,…
Operational and market risks of a regulated power utility
Victor Dvortsov and Ken Dragoon present an analytical method for including market and operational risks when estimating utility portfolio value-at-risk.
Operational and market risks of a regulated power utility
Victor Dvortsov and Ken Dragoon present an analytical method for including market and operational risks when estimating utility portfolio value-at-risk
Getting it together
Data consolidation is now a vital foundation to any successful risk management implementation, as Dave Rose and Stuart Cook of The Structure Group report
VAR: history or simulation?
Greg Lambadiaris, Louiza Papadopoulou, George Skiadopoulos and Yiannis Zoulis assess the performance of historical and Monte Carlo simulation in calculating VAR, using data from the Greek stock and bond market. They find that while historical simulation…
Crossing the frontier
Portfolio risk management
VAR for fund managers
Investment management
Correlation stress testing for value-at-risk
The correlation matrix is of vital importance for value-at-risk (VAR) modelsin the financial industry. Risk managers are often interested in stressing a subsetof market factors within large-scale risk systems containing hundreds ofmarket variables…
Evaluating credit risk models using loss density forecasts
The evaluation of credit portfolio risk models is an important issue for both banks and regulators. It is impeded by the scarcity of credit events, long forecasthorizons, and data limitations. To make efficient use of available information, the…
VAR: history or simulation?
Greg Lambadiaris, Louiza Papadopoulou, George Skiadopoulos and Yiannis Zoulis assess theperformance of historical and Monte Carlo simulation in calculating VAR, using data from theGreek stock and bond market. They find that while historical simulation…
A true test for value-at-risk
The three classic approaches for measuring portfolio value-at-risk do not compare like with like, argues Richard Sage. Here he presents a test portfolio to highlight the differences between calculation methods
European buy side still lags in risk management
The findings of a recent survey show that buy-side firms have increased their focus on risk management, but are still well behind their sell-side counterparts.
How to run a market
Former-derivatives-trader-turned-author Frank Partnoy wants to see tougher accounting standards and risk disclosures to deter corporate crooks. But are the regulators listening? Maria Kielmas reports
How to spot a VaR cheat
Traders can use weaknesses in VaR measurement to make it appear that they are not taking any risks. Brett Humphreys exposes how easily this can be done
Sophis updates buy-side software
Sophis, a risk management technology vendor based in Paris, has released Value v2.0, a new version of its product for buy-side insitutions.
Project risk: improving Monte Carlo value-at-risk
Cashflows from projects and other structured deals can be as complicated as we are willing to allow, but the complexities of Monte Carlo project modelling need not complicate value-at-risk calculation. Here, Andrew Klinger imports least-squares valuation…
Basel's CDO solution
As the Basel Committee on Banking Supervision continues its stately progress towards a revised capital Accord, one area remains under debate: the proposed capital rules for asset securitisations.
Margin notes
Brett Humphreys explains how to measure and manage margin risk, an often-overlooked – yet often-significant – risk exposure
Waiting for guidance
South Korea's banks have made huge strides in implementing risk management systems over the past few years, but Basel II is not yet a driving force, with banks waiting for the Korean regulator to publish local guidelines.
Risk management based on stochastic volatility
Risk management approaches that do not incorporate randomly changing volatility tend to under- or overestimate the risk, depending on current market conditions. We show how some popular stochastic volatility models in combination with the hyperbolic…
Fitch upgrades OpVar tool for operational risk
Fitch Ratings has added a range of new services to its OpVar software suite, an operational risk management quantification tool. Version 5.0, scheduled for release in March, now offers an enhanced data collection module and improved data management…
Extreme forex moves
What is the appropriate statistical description of tail risk in a market portfolio? In the context offoreign exchange, Peter Blum and Michel Dacorogna address this problem using extreme valuetheory. Using 20 years of data, they estimate parameters for an…
Enough’s enough
Brett Humphreys takes the guesswork out of determining how many simulations are needed to calculate value-at-risk