Value at risk is affected by tails and there is so much stuff in the PRMIA handbook about dealing with heavy tails.  This can be confusing as the handbook sort of presumes an understanding of how tails affect VaR - so here is a short tutorial to explain how heavy tails affect Value at Risk.

The constituents of capital under Basel II

This brief article intends to clarify the differences between some concepts relating to credit VaR.  One thing to note about credit risk is that you need to watch out whether you are inferring VaR from a distribution of the value of the portfolio, or from a distribution of the losses in the portfolio.  One is a mirror image of the other, they give the same results, but they are not identical and you should intuitively understand the difference.

This is a brief article on default correlations – what it means, and how to interpret it.  To keep things simple, let us consider only two securities– A and B.  Let us look at how default correlations are calculated, and then try to think about how to intuitively interpret a given default correlation number between two securities. 

This is the first of five articles that provide a high level understanding of the various portfolio models of credit risk covered in the PRMIA syllabus.  Being the first one, this discusses the credit migration framework.  (I am still working on the others.)  This article is intended to provide a conceptual understanding of the approach and I have not provided numerical examples for the reason that I don’t want to duplicate what is already there in the Handbook.  Once you have read this, the scattered explanation in the Handbook will hopefully make more sense.

This is the second of five articles that discuss the various approaches to measuring credit risk in a portfolio.  This article covers CreditPortfolio view.  CreditPortfolio View is conceptually not too dissimilar from the Credit Metrics model described earlier, ie it relies upon a knowledge of the transition matrices between the different credit ratings.  The only difference is that the transition matrix itself has an adjustment applied to it for the business cycle.  But once this adjusted transition matrix has been obtained, the rest of the process works in the same way as for the Credit Metrics model.

This is the third of five articles covering credit risk - this one addresses the 'structural approach'.

This is the fourth of five articles covering each of the main portfolio approaches to credit risk as explained in the handbook.  The idea is to provide a high level and concise explanation of each of the approaches so it may be easier to deal with the detail provided in the handbook.  I hope you find it useful.

This is the final of five articles - each explaining at a high level one each of the five credit risk models in the PRMIA handbook.  This write-up deals with the actuarial, or the 'CreditRisk+' model.Credit Risk +, or the actuarial approach

This article covers how Marginal and Component VaRs are calculated.  We follow up (in a separate article) with a real life example of how VaR, MVaR, undiversified VaR, Component VaR are calculated - based on actual price data pulled from Quandl, an open source market data website.

This article is a practical and real example of how value-at-risk, marginal VaR, betas, undiversified VaR and component VaRs are calculated.  Credit to Pawel Lachowicz for the idea for this article, he has done the same thing in Python here: http://www.quantatrisk.com/2015/01/18/applied-portfolio-value-at-risk-decomposition-1-marginal-and-component-var/

The level of detail here may not be required for the PRM exam, for that just the previous tutorial will do (the one with the formulae and explanations).  This article will be useful for practising risk analysts - we will extract real end-of-day prices, and perform our analysis on those in R.  To run the R code, you will need to install R on your machine.  The good thing with R is that it does not require administrative privileges, so if you can download it from Cran, you can run it.  If you are looking for an introduction to R, you can look at this 20 minute video I posted a few years ago: https://www.youtube.com/user/riskprep