quick risk management indicator

[Grison PG Pierre (External DEXIA-US)]

Hello,

 

Is there anything in quantlib (or in other languages such as C#, VBA, R… ) that could be used to perform quick risk management. For instance, given:

-time series for a set of underlying

-a portfolio of these underlying (let s start with static positions only)

I would like to find an easy way to get the volatility, the VaR and maybe some other risk indicators…

 

Thanks for any help/comments,

 

Pierre

 

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[Jonathan Budd-2]

Dear Pierre

Quick is a relative term :-D

The Performance Analytics package in R will take a time series and compute a number of risk statistics, including VaR. See the table of contents in the manual here for a list of the its methods — http://cran.r-project.org/web/packages/PerformanceAnalytics/PerformanceAnalytics.pdf

QuantLib provides a number of risk statistics through the GenericRiskStatistics class — http://quantlib.org/reference/class_quant_lib_1_1_generic_risk_statistics.html. You may also want to look at the statistics functions in QuantLib XL — http://quantlib.org/quantlibxl/func_statistics.html#qlStatisticsValueAtRisk

I’m not aware of anything pre-rolled in C# or VBA that you wouldn’t have to pay for.

I hope you find something that meets your requirements.

Best regards


Jonathan

— Begin forwarded message —

From: "Grison PG Pierre (External DEXIA-US)" <[hidden email]>
Subject: [Quantlib-users] quick risk management indicator
Date: 15 April 2015 16:01:37 BST
To: "[hidden email]" <[hidden email]>


Hello,
 
Is there anything in quantlib (or in other languages such as C#, VBA, R… ) that could be used to perform quick risk management. For instance, given:
-time series for a set of underlying
-a portfolio of these underlying (let s start with static positions only)
I would like to find an easy way to get the volatility, the VaR and maybe some other risk indicators…
 
Thanks for any help/comments,
 
Pierre

— End forwarded message —

Jonathan Budd
PhD Candidate
School of Mathematics & Statistics
The University of Melbourne, Australia
AU: [phone]
UK: [phone]
[hidden email]


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Learn Process modeling best practices with Bonita BPM through live exercises
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source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
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