Mathematical theory comes to market

Macquarie Bank and the University of New South Wales (UNSW) have joined together to develop and apply new mathematical technologies to value complex financial products.

The project is supported by an Australian Research Council (ARC) Linkage Grant. It aims to manage the risk associated with complex financial products by devising faster and more accurate methods for their valuation.

Doug Moss, division director of Macquarie Bank’s Quantitative Applications
Division, said finance sector products are becoming increasingly complex and there is a need for faster and more accurate valuation tools to meet modern demands.

“The finance industry continues to develop more complex structured offerings to meet market demand but is finding itself restrained by the time it takes to do the complex risk calculations associated with those products," Moss said.

The joint venture between UNSW and Macquarie Bank is aiming to develop new algorithms that can be used in financial services software applications to reduce the time taken for complex risk calculations from minutes to seconds – without compromising accuracy, he said.

Moss said Macquarie Bank would be working with researchers from UNSW's
ARC Centre of Excellence for Mathematics and Statistics of Complex Systems
(MASCOS) a national research centre with a major node in Sydney.

As well as the Australian Research Council, MASCOS is also supported by the
NSW Government, which in its recent innovation statement committed to developing NSW's innovative capacity in a number of key economic sectors, including financial services.

Moss said, "The global economy, expansion of funds management and the development of new and more advanced financial services products are helping propel continued growth and development, which Australia needs to be a part of through innovative research projects like this.”

The Monte Carlo method extends that simple idea into a powerful computational algorithm used every day by financial institutions around the world. Although effective, Monte Carlo methods are too slow for many practitioners in the financial world.