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QuantDay 2007
Quantitative Modeling & Financial Market Dynamics
October 31, 2007

The first public NAG event for financial quantitative analysts in North America, QuantDay 2007 was presented by NAG, Wilmott Magazine, 7city Learning, and Quantstar.

The event was held in the heart of New York City's Financial District from 4:00 to 8:00 PM at New York Marriott Financial Center, 85 West Street (website, googlemap), just a few steps from Wall Street and around the corner from the American Stock Exchange.

In addition to the program of world-class speakers (as outlined below), this event featured a Technical Q&A pre-event from 2:30 to 3:30 PM and a cocktail reception following the last presentation from 8:00 to 9:30 PM.

Quantitative Modeling & Financial Market Dynamics

Abstract: Financial markets produce large quantities of high-frequency data which must be processed and analyzed in order to inform trading decisions. Software systems are therefore essential to competitiveness in this environment. The steps leading from the pre-processing of tick data through to analysis of underlying patterns throw up many interesting problems for the design and implementation of numerical software. These can be viewed as independent components for functions such as data cleaning and wavelet analysis, each with their theoretical underpinnings. However, the response of the software to extreme events reflected in market data must be considered, both in terms of the individual numerical components and as part of a more complex software system. Aspects of numerical software development in this context are discussed with reference to FX trading and in terms of specific techniques, such as wavelet analysis.

Abstract: This presentation will address the multilevel method which combines results from Monte Carlo path simulations with differing time steps to achieve a user-specified accuracy at a much lower cost than standard Monte Carlo. The ideas will be introduced with a simple Euler discretization of a European call option, and then extended to the higher-order Milstein method and Asian, lookback, barrier and digital options. Further computational savings will be demonstrated by combining the technique with Quasi Monte Carlo methods.

Abstract: In dynamic environments, asset allocations based on static portfolio models can lead to excessive transaction costs or significant imbalances. Dynamic portfolio allocation can provide improved performance by balancing transaction costs with efficient allocation and response to market conditions and benchmark positions. The resulting models can quickly become quite large and complex, requiring some form of approximation for solution. This talk will describe the range of potential approximation methods and in particular will focus on serial decomposition using global value function outer approximation and on solution of the corresponding variational inequality using a finite-element approach with high-order basis functions.

NAG has a rich, 30-year history of collaboration in a variety of sectors, one of which is Finance. NAG software components underpin the models and applications for many of the world's most prominent financial institutions – and this event is a natural extension of our ongoing collaborative relationships within this sector.