Computational finance leverages computer technologies to build models from large amounts of data to extract insight. In today's networked world, the amount of data available to build and refine models has been increasing exponentially. Often times the difference between seizing an opportunity and missing one is the latency involved in processing this data. The need to do complex processing with minimal latency over large volumes of data has led to the evolution of different data processing paradigms. Increasingly there is a need to develop an event-oriented application development paradigm to decrease the latency in processing large volumes of data. Such an event-oriented system incorporates the lessons that we have learnt from earlier data processing platforms, i.e., declarative programming, etc. and adapts them for incremental processing. Some of the systems have adopted techniques from artificial intelligence while others have adopted techniques from database management systems...
Badrish Chandramouli, Mohamed H. Ali, Jonathan Gol