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Q1. How are they mathematically getting the values for k under the Basel penalty zone to go from 3 to 4 for a 250 day 99% CI when the number of exceptions goes from 5 to 10. Or is it something that has been set by Basel?

Q2. There is an example in Jorion where they have found that when p = 0.01 and T = 250 the number of exceptions above 4 is 10.8% (when modeled correctly - what does that mean - to model correctly? and how did they calculate 10.8%??)

Then they have shown that the number of exceptions when the model is calibrated incorrectly, that is, when p = 0.03 instead of 0.01, the value calculated is coming to 12,8% - meaning that we will not reject the incorrect model more than 12.8% of the time. (so how did they get 12.8%? and what does it mean to incorrectly model? what are they meaning to say when they talk about 0.03 vs 0.01 in plain english?)

Thanks.

Q2. There is an example in Jorion where they have found that when p = 0.01 and T = 250 the number of exceptions above 4 is 10.8% (when modeled correctly - what does that mean - to model correctly? and how did they calculate 10.8%??)

Then they have shown that the number of exceptions when the model is calibrated incorrectly, that is, when p = 0.03 instead of 0.01, the value calculated is coming to 12,8% - meaning that we will not reject the incorrect model more than 12.8% of the time. (so how did they get 12.8%? and what does it mean to incorrectly model? what are they meaning to say when they talk about 0.03 vs 0.01 in plain english?)

Thanks.

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