Very general question

[shanlane]

Hello,

A friend who took the test In May of last year said that part 1 was much more quantitative than part 2. Is this true? If so, how should our preparation be different for part 2 than it was for part 1?

I see lots of problems with long algorithms (cash flow for MBS) and/or complicated formulas (the duration formulas in Tuckman or the delta of an option given a volatility smile) and with two months left until the test I am trying to figure out how best to spend my time. There are also long lists of reasons to do certain things or implications of doing them (like in the investment section). I am certainly not able tot memorize dozens of lists but I know they are there for some reason and I assume they are fair game.

Any general advice you could give I think would help us out a lot.
Thanks!

Shannon

 

[David Harper CFA FRM]

Hi Shannon,

Your friend's observation is consistent with the feedback in this forum: historically, P2 has been less quantitative than P1 (although P2 is less mature in general, making extrapolation less accurate, since it changes more rapidly). I do not have a complete answer to your question, but I would offer (all with IMO caveat):

• GARP has gotten much better w.r.t. the significance of the AIM action verbs. If you look at P2, non-quant AIMs vastly predominate (e.g., describe, explain, identify, ~ compare, discuss). The best theoretical advice is to rely on the action verbs in the AIM and to know the formulas where a calculate/similar verb applies
• Knowing what I know, if it were me sitting for P2, I would utilize a two-pass strategy: one "shallow" pass (to include review of the many lists you identify), then a selected detail pass. This due to the fact the P2 domain is broader than the exam, so I *think* you want get the breadth first, then address depth selectively.
• I'd keep in mind that several quantitative exercises are very useful in creating qualitative understanding/retention. Styles vary, but for most of the FRM, for myself, my grasp of even qualitative ideas is incomplete until i work with some numerical examples. For example, the qualitative text on liquidity risk is fine; but to engage with the LVaR models, even a little bit, is to render the whole idea much more solid
• At the same time, given the GARP methodology (i.e., they will query a subset of the broad domain), i would not lose too much time in any one quant area. A good example of this (IMO) is Ong on portfolio UL: you could lose a day (whole days) and it might not even be tested.

I'd be interested in others' views, too! Thanks,

 

[shanlane]

Thanks. I have the same feeling about some of the quantitative stuff in Dowd, such as the VaR confidence intervals. Idea seems relatively straight forward, but parts of the algorithm are so tedious and just have to be memorized without adding a heck of a lot of value to your understanding of the material.

Thanks again!

Shannon

 

[Aleksander Hansen]

David,

Post-vacation, I would be very interested to hear your views on this. Has anything changed: that is, post study-notes, videos, spreadsheets, practice question and Part 2 exam feedback from May?

I'm planning on doing a thorough reading of both the core readings and your notes, and obviously support with videos and spreadsheets, and the practice questions of course.

However, personally, I find parts of the material more relevant and interesting than other parts, so I'll probably do a single thorough reading of those [less relevant] topics; but will put more weight and additional review on the readings I see as particularly relevant and interesting.With that in mind it would be interesting to have you weigh in on the approach here, and most interestingly, on what topics/readings you see as truly core, and which ones you consider to be less so.

I guess this is "safety check", and a roundabout way of checking whether my views coincide with yours on this, as well as whether to delve deeper [than the curriculum suggests] into topics by buying a couple of the books and reading it all. [doesn't necessarily need to have testability troughout]
As an example I read among other things, Hull and Jorion as well as C. Alexander's Market Risk volume, and Green's Econometric Analysis and Hamiton's book on Time Series econometrics, pre part 1 (admittedly not all in a few months or as part of the prep). But having previously covered a lot of themath, stats, finance and econ definitely didn't hurt.