C. Albanese, G. Gimonet, S. White: Global Valuation and Dynamic Risk Management

C. Albanese, G. Gimonet, S. White: An Introduction to Global Valuation

C. Albanese, H. Li: Monte Carlo Pricing Using Operator Methods and Measure Changes

C. Albanese: Global Calibration

C. Albanese, A. Vidler: Dynamic Conditioning and Credit Correlation Baskets

C. Albanese: Stochastic Integrals and Abelian Processes

C. Albanese: Kernel Convergence Estimates for Diffusions with Continuous Coefficients

C. Albanese: Operator Methods, Abelian Processes and Dynamic Conditioning

C. Albanese: Callable Swaps, Snowballs and Videogames

C. Albanese, A. Osseiran: Moment Methods for Exotic Volatility Derivatives

C. Albanese, M. Trovato: Monetary Policy Risk and CMS Spreads

C. Albanese, A. Vidler: A Structural Model for Credit-Equity Derivatives and Bespoke CDOs

C. Albanese, H. Lo, A. Mijatovic: Convergence Estimates for Diffusions on Continuous Time Lattices

C. Albanese, M. Trovato: A Stochastic Monetary Policy Interest Rate Model

C. Albanese, H. Lo, S. Tompaidis: A Numerical Method for Pricing Electricity Derivatives for Jump-Diffusion Processes Based on Continuous Time Lattices

C. Albanese, M. Trovato: A Stochastic Volatility Model for Callable CMS Swaps and Translation Invariant Path Dependent Derivatives

C. Albanese, H. Lo, A. Mijatovic: Spectral Methods for Volatility Derivatives

C. Albanese, O. Chen, A. Dalessandro, A. Vidler: Dynamic Credit Correlation Modelling

C. Albanese, A. Mijatovic: A Stochastic Volatility Model for Risk-Reversals in Foreign Exchange

C. Albanese, M. Trovato: A Stochastic Volatility Model for Bermuda Swaptions and Callable Constant Maturity Swaps

C. Albanese, A. Kuznetsov: Transformations of Markov Processes and Classification Scheme for Solvable Driftless Diffusions

C. Albanese, O.Chen: Pricing Equity Default Swaps

C. Albanese, O. Chen: Discrete Credit Barrier Models

C. Albanese, S. Lawi: Laplace Transforms for Integrals of Stochastic Processes

C. Albanese, A. Kuznetsov: Affine Lattice Models

C. Albanese, A. Kuznetsov: Discretization Schemes for Subordinated Processes

C. Albanese, A. Kuznetsov: Unifying the Three Volatility Models

C. Albanese, O. Chen: Implied Migration Rates from Credit Barrier Models

C. Albanese, J. Campolieti, O. Chen, A. Zavidonov: Credit Barrier Models

C. Albanese, S. Lawi: Spectral Risk Measures for Credit Portfolios

C. Albanese, J. Campolieti, P. Carr, A. Lipton: Black-Scholes Goes Hypergeometric

C. Albanese, S. Jaimungal, D. Rubisov: Jumping in Line

C. Albanese, S. Jaimungal, D. Rubisov: A Two State Jump Model

C. Albanese, K. Jackson, P. Wiberg: A New Fourier Transform Algorithm for Value-at-risk

C. Albanese, G. Campolieti: Integrability by Quadratures of Pricing Equations

C. Albanese, K. Jackson, P. Wiberg: Dimension Reduction for Value-at-risk

C. Albanese, S. Tompaidis: Small Transaction Cost Asymptotics and Dynamic Hedging

]]>**Abstract**

The Dodd-Frank Act and the recently proposed Basel Committee regulatory framework for CCPs are a game changer for counterparty credit risk management. The practice of charging an upfront fee as a Credit Valuation Adjustment (CVA) to provision against counterparty credit risk liabilities is being abandoned as it was blamed for as much as two thirds of the losses recorded during the financial crisis. Instead, a key role will be played by margin financing, whereby periodically marked-to-market revolving lines of credit are used to cover margin variations on a cross-product basis.

The emerging pay-as-you-go funding strategy for counterparty credit risk liabilities has a fair value equal to the CVA upfront fee but an entirely different risk profile. Using margin financing, the process for expected loss is locked at zero by construction and CVA volatility risk is passed on to the counterparties themselves. As a side effect, wealth is transferred from bankrupt entities to healthy ones. Moreover, in a Dodd-Frank world, there is no DVA because there is no counterparty credit risk and the paradoxes of DVA accounting and CSA discounting are removed.

To further optimize the funding strategy, interest inflows from portfolios of margin revolvers can be redirected through securitization vehicles to a hierarchy of bond holders to which tranches of risk are apportioned. With this construction, banks can purchase nearly full counterparty default protection from capital markets at a fair cost equal to the CVA, the theoretical optimum. The only remaining risk is concentrated in the equity tranche as there could be a mismatch between interest inflows and outflows.

]]>Quantitative Strategies, Investment Banking Division, Credit Suisse Group, One Cabot Square, London, E14 4Q, UK

**Abstract. **

Valuing, hedging and securitizing counterparty credit risk involves analyzing large portfolios of netting sets over time horizons spanning decades. Theory dictates that the simulation measure should be coherent, i.e. arbitrage free. It should also be used consistently both to simulate and to value all instruments.This article describes the Mathematics and the software architecture of a risk system that accomplishes this task. The usage pattern is based on an offline phase to calibrate and generate model libraries. Valuation and simulation algorithms are planned offline with portfolio specific optimizations. The interactive user-driven phase includes a coherent global market simulation taking a few minutes and a real time data exploration phase with response time below 10 seconds. Data exploration includes 3-dimensional risk visualization of portfolio loss distributions and sensitivities. It also includes risk resolution capability for outliers from the global portfolio level down to the single instrument level and hedge ratio optimization. The network bottleneck is bypassed by using heterogeneous boards with acceleration. The memory bottleneck is avoided at the algorithmic level by adapting the mathematical framework to revolve around a handful of compute-bound algorithms.

]]>