Monte Carlo simulation
To store or not to store
Natural Gas
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
Running a smooth operation
Technology
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
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…
Margin notes
Brett Humphreys explains how to measure and manage margin risk, an often-overlooked – yet often-significant – risk exposure
Asian basket spreads and other exotic averaging options
Giuseppe Castellacci and Michael Siclari of OpenLink introduce a class of exotic options that simultaneously generalises both Asian and basket options. They develop approximate analytic models for real-time pricing of complex instruments that average…
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.
Kamakura upgrades key risk management system
Kamakura, a Honolulu-based risk management technology company, has released a new version of Kamakura Risk Manager (KRM), its integrated risk management application.
How to avoid overestimating capital charges for op risk
Pooling internal and external data is a central issue to estimating capital charges for operational risk. Here, Nicolas Baud, Antoine Frachot and Thierry Roncalli of Crédit Lyonnais discuss the methodology they have developed.
Enough’s enough
Brett Humphreys takes the guesswork out of determining how many simulations are needed to calculate value-at-risk
Abbey National Distributes Risk
A distributed computing system has solved the bank’s overnight batch processing needs. Next up: boosting intra-day processing capacity.
SAP makes play for risk territory
German software giant SAP is making a firm move into the risk management industry with the further development of its range of industry solutions. The Waldorf-based firm has already developed credit and market risk components for the financial services…
EU urged to recognise different op risk profiles of investment firms
MONTE CARLO - The European Union's plans to make investment firms as well as banks reserve capital against operational risk must acknowledge that one size does not fit all firms in the financial services industry, a leading European financial regulator…
Basel accord brings segmentation issues for systems companies
Basel II will segment the market for firms providing IT services to banks.
Reconciling ratings
How should internal credit ratings be calibrated to long-term default rates? This multibillion-dollar question is at the heart of the debate over Basel’s IRB approach. In thisarticle, Stefan Blochwitz and Stefan Hohl use simulations to demonstrate wide…
Hedge your Monte Carlo
Option pricing
Beyond the lognormal
Value-at-risk
Calculating with counterparties
Masterclass – with JP Morgan