# Tag Info

8

Distance to default $DD$ should be measured in standard deviations. You convert this into a probability $p_{default}$ using the normal CDF: $p_{default} = N(-DD)$. So if $DD = 2.978$ then the firm is about 3 standard deviations from default and has a $\frac{1 - 0.997}{2} = 0.0015 = 0.15 \%$ chance of defaulting in the next period. I divided by two because ...

5

In practice, I would begin with the recovery assumption. In the case of Greece, dealers are probably already quoting recovery swaps, allowing you to set this parameter directly. In general, you have to be willing to make assumptions based on history or on conversations with bankruptcy experts. Once I have the recovery assumption, I can take any ...

3

CDS provides protection against default. So when a firm is unable to pay the coupon (and there are few more scenarios where firms default) CDS is triggered. After default the liability holders have first claim on the firm's assets. If the assets are less than loan (say 60% of loan amount) then recovery can only be 60%. if these are risky assets and there ...

3

This is, of course, a very old play. The main thing that gets in the way of trading it is that puts are rarely available in a quantity that matches typical credit instrument notionals. Here's a decent paper by Peter Carr on the topic, see equation (4) and surrounding.

3

I think the national regulators are more concerned with downturn LGD (sort of TTC LGD) rather than a TTC PD. Therefore most rating systems which I encounter are closer to being PIT and thereby easier to validate using the techniques you mentioned and also to backtest. But in any case, model validation is a very subjective field despite the various ...

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