Credit Metrics - Part I

Credit Metrics was developed by JP Morgan to simplify the credit risk calculation and is widely used across industry for its simplicity.

In credit metrics, credit rating transition matrix is used as representation of credit worthiness of the firm. Credit transition matrix will tell us the probability of transfer of asset from one rating class to other. At each rating class asset value will change depending upon the discount prevalent in the market for those particular ratings.

Probability of credit rating migration and change in value can be used to find the probability for given amount of loss in portfolio or amount of loss for given portfolio at given probability. (2^nd part is nothing but definition of VaR)

Advantages of using credit ratings in calculations is that it take care of small fluctuations in the ratings while other models include only default in their calculations.

We will first take one bond portfolio example to find out VaR. For the calculation I have taken following assumptions-

• Credit rating transition matrix is self made and does not represent any financial firm or company.
• Valuation at each credit rating is assumed (In real world forward rate curve data should be used to find out the correct pricing)

Step wise calculation is mentioned below. Please refer to the sheet ,It will be easy to follow below steps –

1. Convert individual probability data to commutative distribution by adding all the probabilities below that – for example commutative probability of loss at BBB will be combining BBB and all the below that. (this will represent that there is X probability that loss will be either value at BBB or more than)
2. For VaR calculations take down the value of Bond at the VaR point. 5% VaR point will be 95 and VaR will be

VaR point value – Actual Value

Result for 5% VaR will be 95-103 => (-) 8 , similarly result for 1% VaR will be (-)43.

Above result will help to set aside economic capital to bear any future fluctuations in the future.