Choosing Financial Libraries to Reduce Quantitative Implementation Risk

# What commercial financial libraries are available to outsource implementation risk?


# What commercial financial libraries are available to outsource implementation risk?












During our daily jobs as quants, we tend to be willing to develop all the quantitative libraries ourselves. While I know that we need to develop specific algorithms which are the foundations of our strategies, I believe there are 2 major disadvantages in implementing quantitative libraries (including statistics such as performance, standard deviation, etc) in-house:

- You take the risk of making a mistake in the implementation

- You waste a lot of time implementing and testing functions that already exist

I have hence been considering using available libraries as a foundation to develop a new quantitative analysis platform. Although I know there are a few open-source libraries, I think most companies would be ready (and would prefer) to pay for the guarantee of continued support and maintenance. I also would like to have a library that I can use from .Net. So I started looking and I found:

- NAG

- MATLAB (as it can be compiled)

Is there something wrong in my argument, and do you know any other commercial library I could consider?

## Answer by Joshua Ulrich (score 4)

https://quant.stackexchange.com/a/3812

How about a commercial company with an open-source product? OpenGamma was a R/Finance sponsor this year, and I've considered using some of their code.

## Answer by Tal Fishman (score 3)

https://quant.stackexchange.com/a/3830

I use both NAG and Matlab a great deal. They are both excellent choices for exactly the reasons you describe. Having solid technical support and maintenance is a very serious concern for most reasonable-sized firms, and that tends to rule out open-source products. I have generally also observed much greater reliability (albeit at the cost of less features) in commercial products, and in NAG and Matlab in particular.

I also would not underestimate the value of professionally written documentation, something both NAG and Matlab excel at, and which competitors (such as R) are horrible at. In fact, particularly for quantitative work, having an adequate description of the statistical techinque you are about to use, along with cross-references to similar alternative techniques which may be a better fit, right there beside you as you code, is invaluable.

I think you will often find die-hard advocates of open-source software online, and particularly in forums such as stack overflow and various stack exchange sites, but I have found people in the real-world to be far more likely to go for commercial software, and as with anything else, ultimately you get what you pay for. While the turnaround time for eliminating bugs may be much shorter for open-source software, I think it also speaks volumes that I have never in my 5-year career as a quant plus 5 years as a grad student found a bug in Matlab. Every time I thought I found a bug, it turned out to be my code that was the culprit. Eliminating that nagging feeling that the bug in your code is really the fault of the software package or library is worth paying for.

Having said that, I do use open-source software for non-core aspects of my work, such as the database, version control, file compression, etc. We also use Java for coding the front-end and for working with some commercial risk vendors that only provide a Java interface.

## Answer by Samik R (score 0)

https://quant.stackexchange.com/a/3824

You can consider the Oracle Crystal Ball API which is available in .NET. The basic product is an add-in to MS Excel for MC simulation, stochastic optimization and time-series forecasting.

From the API, you can run MC simulation and time-series forecasting (for stochastic optimization you will need a separate license from another vendor).

The product (and the underlying API) is very stable (we are in existence for around 20 years now), has strong development and support team, mature documentation to get you started quickly and very large user base.

Note that the product/API is not specific to finance, but there are lots of clients in financial domain, who use it for risk simulation.

Disclaimer: I work for Oracle Crystal Ball and am one of the math developers.

## Answer by pyCthon (score 0)

https://quant.stackexchange.com/a/3826

if you are serious about commerical risk software FinAnalytica is worth looking into. It is a full software suite , and has implemented everything you will need and more for risk management, it also includes many cutting edge techniques that the other solutions do not.