We are evaluating different risk libraries for VaR. Can anyone point me to the details of the approach used by QuantLib. My apologies in advance if this was obvious in the docs, and I missed it.
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On Thu, Aug 14, 2008 at 3:11 PM, ssykowski <[hidden email]> wrote:
> We are evaluating different risk libraries for VaR. Can anyone point me to > the details of the approach used by QuantLib. there is not a proper VAR model in QuantLib, only the ability for a statistic accumulator to calculate VAR and assorted tail risk measures for a given observed distribution, with and without Gaussian assumption ciao -- Nando ------------------------------------------------------------------------- This SF.Net email is sponsored by the Moblin Your Move Developer's challenge Build the coolest Linux based applications with Moblin SDK & win great prizes Grand prize is a trip for two to an Open Source event anywhere in the world http://moblin-contest.org/redirect.php?banner_id=100&url=/ _______________________________________________ QuantLib-users mailing list [hidden email] https://lists.sourceforge.net/lists/listinfo/quantlib-users |
I'm very interested in developing QuantLib in VaR calculations. Please feel free to contact me if you plan on any projects.
Thank you, Cavit (Javit) Hafizoglu
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Hi Cavit,
Please include me in the project for developing Quantlib in VaR calculation
I am very interested in it as I am a little attached to development of VaR Models , as I developed and empirically tested different VaR Models including POT model and back testing in Matlab as part of my doctoral dissertation as well as I am presently involved in developing and implementing Matlab-based VaR models in some banks in GCC region. So it would be an immense learning experience for me.But I need guidance for Quantlib development as I have never developed anything in Quantlib.
I suggest let us first make an implementation plan step wise for developing QuantLib in VaR calculation and then let us work together. We can also post our progress/queries time to time regarding developent for having advice/suggestions from our friends in Quantlib Fraternity.
So Let us start and Cheers!
Kind Regards,
Debashis
On 26/08/2008, javit <[hidden email]> wrote:
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Debashis,
Okay, let's start by reading the riskstats.cpp file to see what was developed. Thank you, Javit
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In reply to this post by Debashis Dutta
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I am also interesting, please include me.
thanks,
sun From: [hidden email] [mailto:[hidden email]] On Behalf Of Alok Jain Sent: Thursday, August 28, 2008 9:16 AM To: javit; Debashis Dutta Cc: [hidden email] Subject: Re: [Quantlib-users] VAR Methodology
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In reply to this post by Alok Jain-5
Dear project members,
I'm not sure if you recevied my e-mail about the riskstats.cpp file. In case, that is the file where some statistical functions are implemented. It would be helpful to read the source code for a beginning.
The next thing is to decide what to implement as a VaR methodology. I am in favor of Monte Carlo VaR which I think would be easier to implement, but I think we should discuss this further.
Quantlib has a very beatifully structured design. We have to get familiar with various pricing engines, processes and the instrument classes. Then, the next step is to discuss how to implement VaR. I would recommend reading source codes in the test-suite. Maybe, we should share the instruments and then implement our solutions piece by piece.
Let me know what you think.
Thank you,
Javit
On Thu, Aug 28, 2008 at 4:15 AM, Alok Jain <[hidden email]> wrote:
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Hi Javit & All Project Memers,
I have hot received your mail about the riskstats.cpp file you talked about. Please resend the same to me and other project members who have not received the same.
While in VaR, there are basically two approaches, parametric and non-parametric.Parametric VaR like VCV VaR requires variance covariance matrix, where codes can pay a lot making validation rule for making it positve semi definitive etc. Here many things we can play in code and add value to real practitioners as well as researchers.
While non-parametric VaR like Historical Simulation and Monte Carlo VaR does not requires parameters, HS requires data. While Basel II stipulates atleast 1 year data, the ideal is 3 to 5 years data for Historical Simulation as it seen empirically. But here code can not play much unless we use bootstrapped Historical Simulation VaR to handle data scarcity.
While I agree with Javit, Monte Carlo a little straight forward to implement and a good candidate as a VaR as it tackles path dependency, fat tails, non-linearity and optionality. But we need to fix the methodological issues at the beginning. We must have clarity regarding
1. Whether we shall choose intitally Monte Carl with Single risk factor or multiple risk factors
2, Which Variance Reduction Techniques
After we freeze these issues , we could move forward.
I think it is a good idea of Jevit we should share the instruments and then implement our solutions piece by piece.But I believe before actually kick start the project, a quick step by step approach regarding existing development life cycle defining various pricing engines, processes and the instrument classes to all project members could be a good beginning.
So I propose initial briefing to all project members about existing development process with example codes and other briefing regarding engines.The we fix methodologies and thereafter devolve a distributed process for developement.
Charles is also back on the project and he is also a good resource at it as he contributed to South Korean Calender in Quantlib version 0.9.6.
Wish all Project Members the best,
Kind Regards,
Debashis
On 31/08/2008, Cavit Hafizoglu <[hidden email]> wrote:
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In reply to this post by ssykowski
Meritz Securities Co. LTD. Manager/OTC Derivatives Team T. +82-2-6309-4875, C. +82-16-541-5807 25-1, Yoido-dong, Youngdeungpo-ku, Seoul, Korea 150-878 [hidden email]
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Dear all,
what is the status of this project? Regards, Nchekwube W.
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