Building a Scenario Revaluation VaR Framework with QuantLib

# VaR implementation using quantlib?


# VaR implementation using quantlib?












I am thinking of writing a VaR framework for my existing system, using quantlib to do the bulk of the calculations.

Despite several searches, I have not as yet come across a quantlib VaR implementation. Is anyone aware of a quantlib based VaR implementation that I may be able to use a s a starting point (to prevent reinventing the wheel)?

Assuming that such a library/framework does not exist - could someone please outline the main steps involved in putting together such a system - so I can make sure that I am not missing anything obvious/ I am on the right track.

For instance, I will have to map my current rate curves and instruments to the Quantlib objects. I will write adaptors to doing the mapping between the classes so assuming that is out of the way, it would be useful to get an outline of the steps required to put a VaR system together using quantlib (assuming there is no such library/framework to build from).

## Answer by Luigi Ballabio (score 7, accepted)

https://quant.stackexchange.com/a/3450

I'm guessing you're simulating rate curves etc. inside your system, and you want to reprice your instruments over the simulated curves using QuantLib. In this case, most of the logic is in your system already, and you have to plug pricing functionality in.

If so, I don't think there's many steps involved besides, well, pricing the instrument on the simulated scenarios. My suggestion for doing that is to use the facilities provided by QuantLib (like quotes and the observer/observable pattern) to avoid repeat all the mapping work on each scenario. For instance, you can instantiate a given instrument just once; for each scenario, you can then relink the relevant handles to the simulated curves and ask the instrument for its new price. The machinery is already in place; you can look at the test suite (say, to testGreeks in the europeanoption.cpp file, where we perturb market quotes to trigger changes in price) to see it in action. For a description of the framework, you can see http://implementingquantlib.blogspot.com/p/the-book.html.

For what is worth, the library provides the basic VaR functionality in its Statistics class; it's just the stats calculation given a set of numbers, but still it's one less small wheel to reinvent.

If you think that QuantLib might help somehow in simulating the curves, please comment here and I'll try to extend the answer. But since you already have a trading system, you already have a curve builder, so I guess you want to keep using that.

## Answer by Andre Miemiec (score 7)

https://quant.stackexchange.com/a/3480

There is experimental code available under https://sourceforge.net/tracker/?func=detail&atid=312740&aid=3413982&group_id=12740

Basically I tried to answer the question if you should do the riskfactor shifts on the level of the pricing engine or on the level of the market data. For me the answer is that one has to do it on the level of the market data. The code implements the shift on the level of the pricing engine. Its very experimental. Nevertheless I've checked the results with the output of some commerical software and found agreement. So it might be a starting point.

## Answer by mepuzza (score 2)

https://quant.stackexchange.com/a/3422

Why don't you try to contact them

http://quantlib.org/mailinglists.shtml

I've worked with them in the past, they're very nice people and will help you for sure if they can.