Giving up on QuantLib SWIG, I will now try JQuantlib for Java Quant development use.
I have given up on this QuantLib SWIG (maybe for now). I am looking into an alternative call JQuantLib which offers a completely written interpretation of QuantLib itself.
Benefits of this include:
• coverage of a wide range of financial instruments;
• running at speeds competitive with C++;
• smooth learning curve with lucid documentation;
• easy integration with other projects;
• shortening time to market.
Features in a nutshell
• Performs valuation of a wide variety of financial instruments;
• Employs analytical, stochastic and simulation algorithms;
• Offers functions for VaR (value at risk) valuation;
There are more benefits. I realize that this in Java and it is not quite one hundred per cent compatible with the current version of Quantlib. As it stands, the Quantlib SWIG is not up to my standards in terms of quality, support, or ease of use. I move forward but I can never get a positive Test run on my chosen language of Python or Ruby. Screw that, I no longer have the time or patience for it.
SWIG also appears to be meant for Linux only as the alternative workarounds within Windows. You need to use either MINGW or CYGWIN which kind of is substandard. There is too much monkeying around with MINGW to make sure the packages you use are compatible.
I hope JQuantlib is universal with less harassments I have found with QuantLib SWIG. I am sure my deficiencies are my own cause but I could never figure out how I could propose this to a potential client. This option of QuantLib SWIG is not a mature product or reliable enough.
I will report on my JQuantLib experience so wish me luck. The big disadvantage is that Quantlib SWIG offers of being able to bind to other programming languages like Python or Ruby. I have worked on this worked on this for a day and a half. I still have no successful results. Sorry QuantLib folks.