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Hi @jan_science17 You are right to be confused, it's my mistake. The Ex 5.4. equation, in order to match the formula displayed as 25*exp(10%*0.5) = $26.28, and to also match the surrounding cost-of-carry (COC) instances, should read F(0) = S(0)*exp(r*T). Its a giveway (hint) that the formula is...

Hi @dtammerz The one approximates the other. That's all. It's called the Fisher equation, see https://en.wikipedia.org/wiki/Fisher_equation For example, let's say the real interest rate is 2.0% per annum with annual compound frequency and the expected inflation rate is 3.0%, then the nominal...

Sure @Eustice_Langham I just noticed that the thread to which I linked contains a link to GARP's own FAQ at https://www.garp.org/#!/frm/frequently-asked-questions where they say a Z-table is provided

Your understanding is correct. The exam will provide a z-lookup. Take a look at GARP's Practice Exam 1 and you'll see that it includes a Z-lookup. I think @Nicole Seaman can confirm (as this comes up every year, I think we checked recently); e.g...

Learning objectives: Describe the characteristics of e-money that could propel a rapid global adoption of this type of money. Describe the risks faced by the banking sector as e-money adoption increases. Evaluate regulatory and policy actions that could be implemented in response to risks...

@pascalb i don't know their exact testability. The LO is " Explain how to validate the calibration and the discriminatory power of a rating model" and the CAP/ROC are common for this so I tried to write a question that's helpful to that LO using material from the chapter. (I can see there's a...

@pascalb okay so they are in chapter 4. What's your point? What do you need clarified?

For those who might be interested, I generated these regressions in R (#rstats) with real datasets. This is more realistic, yes?! If you would like to learn more about data science, or just see the typical regression summary output, see the following links: As a post on my data science blog at...

Hi @dtammerz We can't confidently predict, but I would highly recommend being familiar with arithmetic versus geometric returns (and therefore, yes, I do recommend knowing how to calculate a geometric return), if for no other reason than the distinction makes more than one appearance in the FRM...

@Jash There is not a minimum in each topic. Can you try and read the thread first, then you can benefit from what's already been written. Above I shared a concrete (and counterintuitive) example which should be clarifying. Thanks,

@Hamam Yes, helpful point of view. That's exactly why this is not a good question: most of us will read it and immediately (and very naturally) waste time trying to figure out why there is a choice between 4.8%, 6.0%, 7.2% and 0.1% and where they came from. Giving choices with numeric...

Hi @ktrathen Yes, I agree with you! good catch .... see below. I get spot rates of (6.1856%, 7.3903%, 7.0744%, 7.3831%}. My XLS is here https://www.dropbox.com/s/e54dm851wo48ia5/083120-GARP-P1-T4-EOC-10-20.xlsx?dl=0

@Hamam I moved your question to this post. Notice @nag_san 's comment, and I totally agree with the implication: the question is sort of teasing you to ascertain the values but the values are not themselves meaningful. The more I think about it, the more I dislike this question: the choices...

Hi @nag_san The value of 7.2% is not meaningful; e.g., we could replace 7.2% with any value above 3*1.2% = 3.6% or 4*1.2% = 4.8% because any value above 3.6% would be +3 standard deviations. The question depends only on the fact that we assume actual returns have heavier tails than normally...

For those who might be interested, these regressions are run in R (#rstats), often with actual datasets for added realism. If you would like to learn more about data science, see the following links: Question 20.16.1: My blog (i.e., about the use of gt table to prettify the output) at...

@sailakshmisuresh Without going deep (implicit in Nicole's attempt to save me time is our frankly getting a little tired of supporting competitors, especially as people freely steal our content, but I honestly do like the people at Schweser. Going forward, I'll definitely be prioritizing those...

Hi @Eustice_Langham It might help to view the XLS, here is a simple one-sheet version https://www.dropbox.com/s/q4l43w3n1le5z8h/082520-cml.xlsx?dl=0 This concerns the CML (to my knowledge, it does not require SML/CAPM; for example, Elton who was the prior author in one of the authoritative...

Hi @mukeshramawat glad you figured it out :) You hopefully realize this is my XLS recreation of Jorion's Table 17-4. As you've already noted, the Portfolio's Relative Risk Budget value is given by $525.0 (in total to allocate) * 4.0% TEV * 2.326 (i.e., 99% confident normal deviate) = $48.85...

HI @cpsamdavid In 505.2, we're discounting by one-half a period (i.e., 0.5 periods) where each period is six months (aka, semiannual frequency) because we're discounting 3 months (0.25 years) and there are 2 periods per year. The general discrete form is PV = FV/(1+r/k)^(T*k) where T is the...

Hi @Jaskarn If you understand the computed t value, there's only one step. The computed t-value (aka, test statistic) of 0.54 is given (as already shown) by (45 - 40)/9.262 where 9.262 is the standard error and its calculation is also shown as 29.28/sqrt(10) = 9.262. I think many people skip...