Enhancements to Algo Capital provide robust and realistic EPE values for counterparties across the trading book, while taking into account complex forms of credit mitigation.
As the Basel II implementation deadlines approach, the final pieces of the new regulatory capital framework are falling into place. Not the least of these are the new rules enabling banks and securities firms to measure counterparty credit risk for OTC derivatives and securities financing transactions using exposure simulation and modeling analytics. Expected positive exposure (EPE) is now a key element of the advanced approaches provided by Basel II for the capital treatment of counterparty credit risk.
ISDA lobbied strongly for the inclusion of these rules because they are more closely aligned with industry best practice and the underlying economic risks of these activities than the cruder "add-on" approach of Basel I. Banks are now free to create a modern risk management architecture for trading and capital markets that supports critical business needs and addresses Basel II regulations at the same time. Such an open, scalable risk architecture is typically seen as an essential foundation that supports high-growth business strategies, rapid innovation and increased customer focus. It can also fundamentally change the paradigm of trading and risk management: Financial institutions move from a world where incremental risks are assessed at the end of the day, after the trade has been completed, to a world where risks are fully and accurately assessed before the trade is executed. By adopting EPE for regulatory capital calculations, banks and securities firms can leverage their investment in intra-day exposure management systems to achieve Basel II compliance in a strategic way.Today: Do business, then compute risk.
Tomorrow: Compute risk, then do business.
The basic process of calculating EPE sounds straightforward enough: generate Monte Carlo scenarios spanning at least one year on various market risk factors such as interest rates, exchange rates and credit spreads; value each transaction under each scenario; sum transaction values and apply all allowed forms of credit mitigation to estimate the exposure to each counterparty at each future date; take the appropriate maximums and averages over one year or the effective maturity of the longest-dated transaction. Of course, there are always exceptional cases to consider. To take account of special cases effectively, and even when using the standard algorithm, significant business challenges emerge and details of the calculation must be carefully addressed. Business ChallengesManaging the Regulatory Capital Requirement
. To achieve approval under the Basel II rules for counterparty credit risk while at the same time optimizing capital, one must not simply comply with regulations but also seek to minimize EPE and multiple (alpha) values along the way. A full forward valuation approach (e.g., full modeling of risk-mitigating structures) and maximum recognition of permitted mitigation are an excellent beginning. Integration with the economic capital engine is critical to the ability to estimate a demonstrably conservative, but minimal, value for alpha. Converting Costs Into Investments
. Supporting regulatory compliance for all types of risk in all areas of operations can be an expensive undertaking. Establishing a comprehensive framework covering market risk, credit risk and operational risk, as well as supporting critical business processes such as limit management, economic capital allocation and collateral management, is therefore essential in helping to turn the costs of compliance into an investment in the business. Common components, hardware and expertise reduce expensive duplications in the short term and maintenance costs in the long term. Minimizing Project Risk.
Today, many banks struggle with fragmented systems resulting from mergers and rapid growth. Unifying the approach to market and credit risk measurement supports several initiatives, such as counterparty exposure management, the Internal Models Approach for market risk, and EPE calculations, and can help to reduce fragmentation. This allows the infrastructure to be leveraged effectively, thereby creating shorter, less risky Basel II projects.Calculation ConsiderationsFull Forward Valuation.
Full forward valuation of all transactions across numerous scenarios, as required by Basel II, can be time-consuming. This often tempts practitioners to take shortcuts and make approximations, which can conceal nuances of exposure profiles over time. A framework approach in which all products can be valued in a timely manner with appropriate accuracy at each future time, under each scenario, is essential.
Treatment of Mitigation - Netting.
Netting is an important form of credit mitigation, as it can reduce exposures significantly and impact not only the key exposures but also overall capital levels for the trading book. By facilitating the use of netting rules mandated by Basel II in a flexible manner, the calculation of lower yet still conservative exposure levels is possible.Treatment of Mitigation - Collateral.
Credit support annexes are commonly used to mitigate the risk of key exposures in the trading book. Modeling the more sophisticated features of such agreements (e.g., ratings-based thresholds and collateral lags) allows the calculation of minimal, comprehensive and appropriate exposures for all trading book counterparties. Stress Testing.
While EPE is the measure specified under Basel II, the new regulations also call for stress testing and allow for the possibility of adopting a more conservative exposure measure. A rich set of statistical results (e.g., EPE and peak exposure) can be repurposed by including measures that reflect an individual institution's approach to credit risk and limit management as well as those required for Pillar 1 compliance. Under Pillar 2, the emphasis on stress testing (e.g., obtaining detailed results - not just statistics - over the full tenor of the transaction) increases the demands on the simulation engine. Comprehensive Product Coverage.
The list of types of OTC derivatives and securities financing transactions grows continually, with the last several years seeing an ever-increasing rate of product innovation. To properly calculate EPE, a mark-to-model calculation for each product type is essential. Any robust EPE architecture must facilitate the adoption of additional modules and permit users to access analytics from other sources to ensure that 100% of the firm's counterparty credit exposures can be addressed. This inclusive approach is essential in facilitating regulatory compliance.Calculation of the "Alpha" Multiple
. Ideally, an economic capital calculation engine will facilitate the comparison of capital calculations under various assumptions, including stochastic vs. deterministic exposures, default/no-default vs. mark-to-market, full diversification vs. concentration modeling, and integration of market and credit risks vs. credit risk only. This framework for comparison should permit reconciliation of economic and regulatory capital, the calculation of a demonstrably conservative alpha, and the identification of wrong-way exposures.Developing an architecture that supports an integrated approach to meeting regulatory expectations and creating real business value will enable institutions to reap the maximum benefit from their investment in risk management. Algorithmics has helped more than 200 clients worldwide to attain their risk management goals using the integrated Algo Suite framework.