Various implementations of limit order books (matching engines)
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Latest commit 8dc24b0 May 23, 2012 @jordanbaucke jordanbaucke Update README


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:
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.