"Current systems often take a silo approach to basket and portfolio credit derivatives, preventing firms from creating a consolidated, coherent view of risk," says Diane Reynolds, Director for Analytics at Algorithmics. "However, with this new module, risk managers have the option of treating basket and portfolio credit derivatives in the same manner as other asset classes, and aggregating risks across their holdings. By allowing users to perform a variety of risk analyses, including stress tests, across multi-asset portfolios, containing for example, both single- and multi-name credit derivatives, high-yield debt and various derivatives, Algo Suite helps risk managers to breakdown silos and form more accurate, holistic views of risk."
The module offers several valuation alternatives for CDO and BDS products, ranging from a general Monte Carlo valuation approach to a selection of analytical approaches including Algorithmics' performance-enhanced analytical approach. "At the moment, Monte Carlo is commonly used for valuing these instruments but is so computationally intensive that the required accuracy may not be achievable within the allotted timeframe," continues Reynolds. Analytical approaches run hundreds of times faster than standard Monte Carlo with little loss of accuracy, with Algorithmics' approach pricing up to three times faster than industry standard analytic approximations.
Algorithmics also recently announced a new, generic lattice-based pricing module that allows users to define and customize payouts for new structured products quickly, thereby reducing the time and effort required to introduce these new products into the risk management process.