Quant Programming
Financial Apps feel the need for speed – this can come via parallelization, and via infrastructure - fast messaging and non-blocking distributed memory management. This blogpost gives an overview + examples of various technologies that can squeeze performance out of your trading apps and clock cycles out of your modeling apps. Low Latency via Infrastructure ZeroMQ · ZeroMQ is a messaging library - ‘messaging middleware’ , ‘TCP on steroids’ , ‘new layer on the networking stack’. not a complete messaging ......
I've just opened a project on CodePlex - http://algonet.codeplex.com/ !!! This project will implement various algorithms related to artificial intelligence, numerical analysis, NLP, object recognition and quantitative finance. It will initially target C#, and eventually F#. First exercise - port Java AIMA 3 to C# from http://code.google.com/p/ai... AIMA3 so far I've ported the utils - helpers, data structures and basic linear algebra classes Matrix class - Implemented ICloneable, ISerializable.GetObjectData ......
LMAX provides a .NET API for automating your financial trading strategy. sign up & download here:http://www.lmaxtrader.... If you can combine software engineering skills + numerical analysis skills + an understanding of financial markets --> the whole is greater than the sum of the parts. You can build products that make money, and you can save money by being a cross-domain expert. http://en.wikipedia.org/wik... - see here to learn more about this lucrative field. A good ......
I recently read an informative and succint book - A mathematician Plays the Market, by John Allen Paulos. Heres my summary of key points: Behavioral finance · Anticipating other's anticipations · A trading strategy can yield the illusion of effectiveness, when only chance is at work. · Keynes - short-term investors anticipate what average opinion expects the average opinion to be. · Distinction between being smart & rich, and distinction between being right & being right about the market. ......