What all are we required to know in the copulas chapter for Part I.

I am not able to understand a word of it.

I would say this chapter, for me at least, was probably the most difficult to grasp conceptually…I think most find this part tough going. I’m not saying you don’t need to know it, but I found that not concentrating too much on it didn’t hurt my performance on the actual exam at all.

I wouldn’t get bogged down in it, try to grasp what you can and move on…there are other areas where this much more return on offer for your effort.

As per LO of Part I: • Define copula and describe the key properties of copulas and copula correlation. • Explain tail dependence. • Describe the Gaussian copula, Student’s t-copula, multivariate copula, and one factor copula. ------------------- In FRM Part I, I have not studied Copula…But as Part II has copula explanation I would like to share in brief. Copula function helps to join two different marginal distributions to form a multivariate elliptical distribution. Just understand that the previous two structures were not forming a normal distribution and after introduction of copula function the two distributions jointly formed a structure without losing relevance of their own earlier structure.