Quantitative analysis
All your hedges in one basket
Leif Andersen, Jakob Sidenius and Susanta Basu present new techniques for single-tranche CDO sensitivity and hedge ratio calculations. Using factorisation of the copula correlation matrix, discretisation of the conditional loss distribution followed by a…
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,…
Pricing exotics under the smile
Masterclass – with JP Morgan
Benchmarking asset correlations
Basel II stipulates that the asset correlation to be used in calibration of obligor risk weights is 20%. Here, Alfred Hamerle, Thilo Liebig and Daniel Rösch use a parametric model to empirically obtain asset correlations from a large database of…
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.
Breaking down the model
Brett Humphreys and Andy Dunn outline a method to help energy companies minimise potential model risk and thereby avoid costly errors in valuing deals.
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
Pay attention to interest
Masterclass – with JP Morgan
On the dependence of equity and asset returns
Asset returns play an important role in credit risk modelling. Here, Roy Mashal, Marco Naldiand Assaf Zeevi investigate the co-dependence behaviour of asset returns semiparamatrically.They find that the Student-t copula outperforms the normal copula as…
Modelling venture capital funds
Modelling venture capital funds is a challenge and has become more important due to recentand upcoming securitisation deals, the need for efficient portfolio management, and Basel II.Here, Thomas Meyer and Tom Weidig summarise the issues both industry…
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
Selling risk at a premium
Option strategies
Hedging using forward rate bias
Foreign exchange
Insurance optional
Asset/liability management
VAR for fund managers
Investment management
Collateral damage
Credit risk
Analysing counterparty risk
In an attempt to improve on existing regulatory approaches to derivatives counterparty creditrisk, Eduardo Canabarro, Evan Picoult and Tom Wilde present a new method based on expectedpositive exposure (EPE).
Creating an op risk loss-collection framework
To meet the Basel II advanced measurement requirements and improve op risk management, firms must establish robust loss databases. Ulrich Anders and Jürgen Platz of Dresdner Bank in Frankfurt outline such a framework.
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…
Analysing counterparty risk
In an attempt to improve on existing regulatory approaches to derivatives counterparty creditrisk, Eduardo Canabarro, Evan Picoult and Tom Wilde present a new method based on expectedpositive exposure (EPE). Using a one-factor conditional independence…
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…
On the slide
market trends