Quantitative finance research language

Have you ever considered Python? There are many mature libraries that can be used for statistical analysis, data acquisition and cleaning. To name a few:

Numpy         - N-dim array objects
Scipy         - library of statistical and optimisation tools
statsmodels   - statistical modeling
Pandas        - data structures for time series, cross-sectional, or any other form of “labeled” data
matplotlib    - MATLAB-like plotting tools
PyTables      - hierarchical database package designed to efficiently manage very large amounts of data
CVXOPT        - convex optimization routines

I've personally implemented some pretty complex derivatives pring models in python, including a jump-diffusion Vasicek interest rate lattice, many stochastic processes, and even managed to write a genetic optimizer.

One of my professors is director of research ( PhD. in math ) at a Chicago hedge fund who uses Python exclusively.

Perhaps, every company has something on their own, but there are some materials available on the web ( mainly about DSL-s ):

• Going functional on exotic trades
• Composing contracts: an adventure in financial engineering

As for your own language ( and libraries / runtime! ) - there is not too much to say whithout knowing your requirements ( to name just few, which immediately came to my mind when I started to think about it ):

• Who will use it - sales or traders or quants or all
• How will it be used - just pricing of predefined blocks and/or solving optimization problems. It would lead to an ability to define workflows.
• Interaction with underlying infrastructure and its level of abstractions
• Extensibility ( to what an extent )
• Live calculations or simulation
• I/O support