Chao-Jen Chen
The modern finance industry can’t operate without numerical computing. Financial institutions, such as investment banks, hedge funds, commercial banks, and even central banks, heavily use various numerical methods for derivatives pricing, hedging, and risk management. Usually the production systems of those numerical methods are implemented in general-purpose object-oriented languages like C++, C#, and Java. But there’s a steady, emerging trend in the industry: financial institutions are increasingly adopting functional languages, including F#, when implementing their new derivatives-pricing or risk-control systems. One of the reasons this is happening is that a functional language like F# is relatively expressive in turning mathematical equations into code. Moreover, F# has strong support for high-performance computing techniques, such as graphics processing unit (GPU) computing and parallelization. As such, F# enables programmers and quantitative analysts to spend less time coding and at the same time avoid compromising performance.