I recently attended this year’s Risk USA conference, which was held in late October in New York City. For those unfamiliar with the event, it’s a great forum for professionals from banks, buy-side institutions and regulatory bodies around the world to meet and learn about the latest trends in risk and portfolio management, as well as quantitative finance.
This year’s presentations focused mainly on how the flurry of regulatory reform since the financial crisis is affecting the markets. Attendees learned that US federal authorities are likely to take a hands-off approach in the areas of high-frequency trading and support for central counterparties. Another interesting highlight was that the growing use of XVAs and the introduction of speculative position limits will both receive increasing attention from regulators in the coming months.
Russell Goyder, PhD, Director of Quantitative Research and Development at FINCAD presented on the challenges and benefits of adopting algorithmic differentiation (AD) for calculating risk sensitivities in derivatives portfolios. Russell explained how calculating Greeks is the foundation of effective portfolio hedging. The problem is that many firms continue to rely on the traditional method of finite difference (or “bumping”) for performing this function.
Unfortunately, bumping is inordinately slow, making it difficult for firms to gain an accurate view of intra-day risk, and therefore preventing them from making informed trading decisions. In the current landscape, bumping risk management is akin to navigating a dark and dangerous landscape with only a small flashlight. Often firms will try to optimize this approach by reducing the number of calculations run or adding more hardware. But neither of these workarounds serve to really solve the problem.
As such, many financial organizations are leaving bumping behind and embracing AD, a move that is helping them realize remarkable performance improvements. In fact, when stacked up against bumping, firms using AD will often see calculation speeds that are 100 to 1000 times greater. Under this method, managing exposures is not an end-of-day exercise, but rather a continuous intraday one. This way, you get crystal clear visibility into your entire risk landscape, including all sensitivities to all of your relevant quotes.
Historically, the biggest challenge to adopting AD has been the high implementation cost, putting it beyond the reach of most firms. But today there are more affordable tools available in the marketplace. FINCAD’s F3 platform incorporates its own patented implementation of the method we call Universal Algorithm Differentiation (UAD). UAD offers financial institutions comprehensive, real-time measurement of the sensitivities of a portfolio, trading book or fund. This helps you take advantage of more trading opportunities by allowing rapid assessment of the impact of a new trade’s exposure on your portfolio.
“The biggest advantages of FINCAD’s UAD are that it is truly universal and future-proofing. You can be confident that whatever you trade—whether it is exotic or vanilla—and whenever you trade—whether it be today, tomorrow or next week – it will be covered and handled in a consistent manner. Furthermore, by using UAD to extend your models you can cover new markets and take advantage of new opportunities all while safely managing your exposure throughout,” commented Russell.
For more information on how AD can help you drive better trade decisions, view our on-demand webinar: Improve Trading Performance with Faster Analytics
