http://www.opensourcetrader.com Limit Order Book - May, 2012 - Conducting some expirementation with various OS for executing the software. Using 'QuantCup' solution in C, one should avoid Windows for ease of use and go straight to a Linux OS for an implementation of: 'CLOCK_MONOTONIC_RAW' compiled into the the Kernal headers. I'm not sure, but this should be implemented somewhere in a library for Cygwin or MinGw, but I couldn't find it. Good luck! Hoping to get some more work in soon. October, 2011 - I have uploaded a historical copy of the winning engine (voyager) from the '11 QuantCup Challenge. It is implemented in C++, and is in this repo @/Others/C++. Please review @/Others/README-Others for notes and considerations. I will continue to expand the Limit Order Book project as necessary...! June, 2011 - A recent poll (conducted by the OST Project) of financial market professionals debating the merits of various software technologies for financial markets led to little consensus on the best choice for implementing large-scale financial market trading solutions. Some consensus amongst those surveyed existed regarding broad paradigms: Scalability Multitenancy Performance concerns (garbage-collection, memory management) Functional Language approaches tend to out-perform imperative languages Respondents to the poll also largely chose 'Java' as: "Which type of object oriented language technology is best for a large financial trading application?". The second most popular response was: "Something Else", referring broadly too object-oriented functional languages: OCaml implementations such as F#, and/or some version of Python. Third and fourth were C++ and C#.NET respectively. This project is attempt to begin to answer these questions via an open source project to implement a limit order book in 3 separate functional language technologies: F#, Scala, and Python. Interested parties are of course more than welcome to download, modify, and of course, contribute their knowledge to these projects. The idea is that these projects will eventually form a larger foundation of best practices in the financial software industry, via an open source framework.