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#251
01-01-2020, 07:09 PM
 NormalDan Member CAS Join Date: Dec 2016 Location: NJ Posts: 10,882

Quote:
 Originally Posted by jumpyshrimp how many study days/hours do you guys have? I negotiated with my company (a small one) to finally get 5 study days plus the exam day. I heard many big companies offer 15+ days even for repetitive exam takers?
Exam day plus 120 hours for first attempt, 110 for second... materials paid for up to \$1K (not including cost of registration)
#252
01-01-2020, 08:08 PM

Quote:
 Originally Posted by jumpyshrimp I heard many big companies offer 15+ days even for repetitive exam takers?
To make you feel better, I got kicked out of the study program because I made no exam progress in consecutive 18 months, been using vacations to study for fellowship exams for a while
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ACAS 7 8 9
#253
01-02-2020, 12:01 PM
 SkolChicago Member CAS Join Date: Apr 2015 Posts: 1,244

Finally started today, got through Mack this morning and now on Hurlimann. So far I'm not really a fan of the way CF does his outlines. I'd rather have the notation sprinkled in than in a list format, and he's super brief. Might just jump to the source now on Hurlimann and revisit CF after.
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ACAS 7 8 9
#254
01-02-2020, 01:17 PM
 Unrealistic Ace Member CAS Join Date: Nov 2017 Posts: 234

Quote:
 Originally Posted by SkolChicago Finally started today, got through Mack this morning and now on Hurlimann. So far I'm not really a fan of the way CF does his outlines. I'd rather have the notation sprinkled in than in a list format, and he's super brief. Might just jump to the source now on Hurlimann and revisit CF after.
This is how I felt going through it the first time. I'm pretty certain CF assumes you have read the paper before reading the outline. In my opinion, if including examples/problems, CF has most of what is likely testable in it. I have added a few extra things from the source in my notes, but not a whole lot honestly.
#255
01-02-2020, 01:21 PM
 Unrealistic Ace Member CAS Join Date: Nov 2017 Posts: 234

Quote:
 Originally Posted by FreddyBabe I emailed CAS about this. Admissions Manager Stephanie Litrenta replied on 12/10, "I’ve reached out to the exam 7 leadership to address this. I will follow up with you when I hear back" Until I hear otherwise I will use t*=√(p) since that is what was on previous examiners reports. Until they clear up the inconsistency, they might have to provide the formula for t* as they did in S18Q3.

To add a little bit to what you have already said, definitely use t*=√(p) unless otherwise stated. Also, remember to use the same value of t* for the relative MSE across all methods instead of changing it to match each method, i.e, only the credibility values change in the MSE formula (t, p, q are the same throughout).
#256
01-02-2020, 03:43 PM
 SkolChicago Member CAS Join Date: Apr 2015 Posts: 1,244

The formulas for Hurlimann in CF are pissing me off and don't seem to make sense. Can you guys tell me what I'm misinterpreting?

Let's say you have a 4x4 triangle. The paper assumes that the reserve for the oldest year (year 1) should be 0 as it is at ultimate yes? But the way the formula is written for the reserve is R_i = Sum(S_i,k) from k = n - i +2 to k = n (apologies for notation). For the oldest row, that would imply the reserve should sum the incremental paid losses at periods 3 & 4, which doesn't make sense to me.
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ACAS 7 8 9
#257
01-03-2020, 08:07 AM
 Unrealistic Ace Member CAS Join Date: Nov 2017 Posts: 234

Quote:
 Originally Posted by SkolChicago The formulas for Hurlimann in CF are pissing me off and don't seem to make sense. Can you guys tell me what I'm misinterpreting? Let's say you have a 4x4 triangle. The paper assumes that the reserve for the oldest year (year 1) should be 0 as it is at ultimate yes? But the way the formula is written for the reserve is R_i = Sum(S_i,k) from k = n - i +2 to k = n (apologies for notation). For the oldest row, that would imply the reserve should sum the incremental paid losses at periods 3 & 4, which doesn't make sense to me.
Right below that formula, it says "where i=2, ..., n". This means the formula doesn't apply to the oldest row (i=1). For i=2, k=n-2+2=n. So I believe the formula is OK.

I'll mention as an aside, that even though Hurlimann states this formula (page 83 of the source paper) it really doesn't seem to ever come into play in the actual calculations again when credibility is applied. I think CF just states it here for consistency. I skipped this formula altogether in my notes.
#258
01-03-2020, 11:26 AM

Shapland: Include process variance by replacing the future incremental losses with simulated values from a Gamma distribution. The gamma distribution is fit by setting

Variance = ϕ*(future incremental loss)

Here's the part that confuses me. Shouldn't Variance = ϕ*(future incremental loss)^2 because the power z should be 2 under Gamma error?
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ACAS 7 8 9
#259
01-03-2020, 01:10 PM
 Unrealistic Ace Member CAS Join Date: Nov 2017 Posts: 234

Quote:
 Originally Posted by trueblade Shapland: Include process variance by replacing the future incremental losses with simulated values from a Gamma distribution. The gamma distribution is fit by setting Variance = ϕ*(future incremental loss) Here's the part that confuses me. Shouldn't Variance = ϕ*(future incremental loss)^2 because the power z should be 2 under Gamma error?
(I assume you are referring to the last paragraph of page 12):

The assumption is that we are in the ODP model, which has z=1. So the mean is $m_{w,d}$ and the variance is $\phi m_{w,d}$. At this point, we are only considering parameter variance.

To inject process variance, consider a gamma distribution with mean $m_{w,d}$ and variance $\phi m_{w,d}$. By sampling from this (simulating values for the incremental loss), we are considering a variety of possibilities while preserving the mean and standard deviation across simulations. This adds the process variance portion we need.

Essentially, the Gamma distribution is a new assumption that is not inherent from the original ODP model.
#260
01-03-2020, 01:40 PM

Quote:
 Originally Posted by Unrealistic Ace Essentially, the Gamma distribution is a new assumption that is not inherent from the original ODP model.
Thanks, I got it. It's like moment matching, using Gamma to model the ODP random variable, and consequently setting gamma variance to be the same as the ODP variance
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ACAS 7 8 9

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