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In the fourth segment of FINCAD’s five-part video series featuring John Hull, PhD and Alan White, PhD we posed the question, “What is the value of real world versus risk neutral modeling?” Traditionally the derivatives business has been very concerned with the processes followed by market variables in a risk-neutral world. This is because their main focus has been on the valuation of derivatives

From a job market standpoint, repercussions of the 2008 credit crisis were not all negative. While the crisis did bring to light a need for reform in the banking system, at the same time it created new opportunity for the tech industry to come alive and innovate much-needed fixes to age-old problems. Even if the economy at large is not currently booming, I think it’s fair to say the technology

FINCAD recently held its 2016 Americas User Forum in New York City. The event gave FINCAD clients from across the United States the opportunity to network, gather new ideas and learn best practices for using FINCAD solutions to optimally manage their multi-asset derivatives portfolios. 2016 marked the first year that the Americas forum was held in the Big Apple. And I think the other attendees

FINCAD continued its video series with John Hull, PhD and Alan White, PhD, interviewing them on how adjoint algorithmic differentiation (AAD) is helping the buy-side to measure and manage risk more effectively. When compared to traditional risk methods known as “bumping,” AAD offers firms the ability to solve complex pricing and risk challenges quickly and accurately. “Adjoint algorithmic

Valuing derivatives used to be much simpler than it is today. For example, an interest rate swap could be valued by knowing nothing more than forward LIBOR rates. An interest rate cap could be valued by modeling the LIBOR short rate. Now, as explained in an earlier blog, it is necessary to worry about the behavior of OIS rates as well as LIBOR because OIS is generally accepted as being the correct