VaR Optimizer Reduces Monte Carlo Burden


LONDON --Integrating additional risk factors like credit spreads and repo spreads would normally create an error-prone process associated with running Monte Carlo simulations on such a large amount of data. Yet, ING Barings risk officials have found a way around this potential problem through an optimization technique.

The firm uses Summit's Monte Carlo VaR engine that includes Gamma VaR as an optimizer to first isolate the scenarios that would have the most negative impact on positions, and then

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