Numerix, JPMorgan Eye Cross-Asset Application of Volatility Model

Previous work completed by Igor Halperin, executive director of model risk and development at JPMorgan, created a Markovian Bivariate Spread-Loss (BSLP) model that is now available in Numerix's library and used by several major sell-side firms.

The new research will use that knowledge, combined with previous quantitative work on unspanned stochastic volatility, to create a more practical and economic framework using “local” volatility than HJM-like models, which require a higher number of Markovian drivers for four-factor specification of interest-rate and equity derivatives pricing. The end result is a linearity-generating process (LGP), Halperin explains.

"Our framework for local volatility enables perfect matching of an arbitrary number of European vanilla options quotes with different strikes and maturities," he says. "This allows us to price both vanilla and exotic derivatives, especially if vanilla options are being used to hedge the exotics. By merging such flexibility with a multi-factor LGP framework, we hope to produce an accurate and efficient stochastic local volatility model that could work across different asset classes."

Steven O'Hanlon, Numerix CEO, says the new framework holds potential for future analytics offerings, as well. "The joint research of Itkin and Halperin represents the best of what the quantitative finance industry has to offer in terms of expertise, innovation and leadership. While the implementation and empirical validation of the new framework is still under way, this important research is sure to bring further benefits and efficiencies to the complex world of over-the-counter (OTC) derivatives pricing."