Numerix Introduces New Attribution Profile Functionality
Numerix announced new attribution functionality in Leading Hedge, Numerix's production platform for end-to-end risk management and the hedging of life and annuity products.
 
Leading Hedge provides a risk neutral or real world stochastic modeling framework that is used for capital calculations, product pricing and ongoing valuations, trading and hedging, and regulatory and accounting compliance.
The upgrade will allow users to run drill-down analysis and performance attribution tracking, enabling users to explain P&L within risk factors, isolate the impact of un-hedged risk factors and capture higher order risk factors, such as cross effects, according to a release.
"Performance attribution analysis is a critical function of any dynamic hedging strategy as risk managers need to explain sources of gains and losses from hedging programs," said Pawel Konieczny, vice president of insurance solutions of Numerix's client solutions group. "However, dynamic hedging strategies introduce new risks to the firm including strategy risk, model risk, operational risk and counterparty exposure. While sophisticated hedging programs explain over 95 percent of hedge P&L for assets and liabilities across all hedged and un-hedged risk factors ─ market risk, actuarial risk and basis risk ─ small ‘leaks' can compound over time, or remain hidden until market volatility spikes."
Clients can use Leading Hedge to compare expected versus actual changes within risk factors. The solution also provides ongoing real-time model validation.
"Through this process users are able to constantly evaluate on a daily basis how well Greeks performed, and how assets changed with respect to liabilities," Steven O'Hanlon, CEO and president of Numerix, said in a statement. "It allows users to explain a daily change in P&L and determine what risk factor is causing that movement. With this information, users can then report to management if their hedging program is over or under hedged, or if their Greeks are not predicting changes in liabilities the way they should."
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