Hi all, will we be expected to answer many state Bayesian problems in the FRM part 1 exam?
Example:
Suppose 3 types of managers: underperformers beat mkt 25% of the time. In-line performers beat mkt 50% of the time. Outperformers beat mkt 75% of the time. Prior belief is that manager has 60%...
Hi Everyone,
Apologies for my basic question but I am totally confused about how they calculated the probability of P(A/C) as 50% and P(B/C)? Which areas are they adding up?
Hey everyone,
I am having a hard time with the following task:
Question:
Q 29
A risk analyst estimates that the hazard rate for a company is 0.12 per year. Assuming a constant hazard rate model, what is the probability that the company will survive in the first year and then...
@David Harper CFA FRM , can you please share an example of the below case if possible?
Events can be conditionally independent yet unconditionally dependent. Events can be conditionally dependent, yet independent! [Chapter 1: Fundamentals of Probability, Study Notes, Pg. 5]
It will be easy to...
Session 2, Reading 9 (Part 2): This video reviews portfolio variance and covariance, where covariance is the expected cross-product. We look at correlation, which is given by the covariance divided by the product of standard deviations, and therefore standardizes the covariance into a unitless...
Hello
Can anybody help to guide how to answer these questions?
Thank you.
Edited by Nicole to include questions (please include questions in text format instead of an attachment):
1 What is the probability that a firm rated A will default in 1 year?
2 What is the...
How is the variance calculated? I'm sort of stuck on this problem, although I was able to understand it during the 6-sided die example.
Thanks for any help!
Hi David,
Apologies if this question is non-sensible or has been asked already (please tag a link if this question has been asked) but I just started preparing for an exam and I have one question so I know what to expect when I am learning it. Integration and calculus sort of questions as far as...
A function is a viable probability function if it has a valid CDF (i.e., is bounded by zero and one) which is the integral of the probability density function (pdf). The inverse CDF (aka, quantile function) returns the quantile associated with a probability, q = F^(-1)(p), whereas the CDF...
Learning objectives: Describe and distinguish between continuous and discrete random variables. Define and distinguish between the probability density function, the cumulative distribution function, and the inverse cumulative distribution function. Calculate the probability of an event given a...
Hello,
I am sure this has been addressed before but I have searched everywhere and really couldnt find the exact answer I am looking for.
I just started the Quant book, from GARP, and by page 20 I am already pretty lost. I understand the basic concepts covered up to that point (probability...
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