

FlashChat  Actuarial Discussion  Preliminary Exams  CAS/SOA Exams  Cyberchat  Around the World  Suggestions 

MASI Old Exam S Forum 

Thread Tools  Search this Thread  Display Modes 
#151




Quote:
Quote:

#152




Yes. I'm going to remove the smoothing part from the question. The original exam question based on the textbook used then used a simpler smoothing method  they had 10 observations, with the first one being the 10th percentile, the second the 20th percentile, etc. So it's not the first time I'm changing to question to the current textbook's method.

#153




Likely a dumb question, but something I was curious about. I'm working through the Time Series portion of Mahler's manual and I came to a problem similar to 5/18 Q44.
You're given a fitted AR(1) model along with the Mean Squared Error and asked to calculate the twostep ahead forecast error. With the assumption that the first term of the series is known, I understand the procedure for solving this problem; the variance of the fitted value is driven by the variance of the white noise terms but I was thrown off by being given the MSE. Is the thought process here that the white noise terms should be equivalent to a residual error series, the variance of which is equal to the MSE? 
#154




How is everyone feeling at this point? I took my first practice exam yesterday (Fall 2018) and just barely passed.
I feel like so long as I keep on top of doing practice problems, drilling flashcards, and a few more practice exams, I should be able to pull out a pass assuming the real thing doesn't throw out too many wildcards. Coming to this after taking Exam 5 it doesn't feel anywhere even remotely close in terms of difficulty and the amount of advanced critical thinking required. The primary roadblock to getting a pass seems to just be remembering all the different formulas and more advanced concepts. 
#155




Not feeling good. its my 3rd time around... I do practice exams and score very well.. around 75%80%. But when the exam day comes... I just cant perform...its very frustrating...sometimes i feel at a loss...my hours and hours of practice does not pay off... how is everyone else doing?

#156




I'm feeling pretty good about my chances, I've studied for this exam for more time and more consistently than any other exam that I've passed.
I'm going back through Mahler practice exams and marking specific questions that I get wrong under exam conditions. A few topics that I'm pretty weak on are MVUE, and the different types of GLM models like 'cumulative logit' models that are very hard for me to tell apart. I also struggle with some of the more complicated order statistics stuff and maximum likelihood on grouped data due to algebraic complexity, but those problems are infrequent and I can handle simple questions on them. Good luck to everyone during the crunch time! 
#157




Quote:
__________________
1[✔] 2[✔] 3F[✔] MASI[] MASII[ ] 5[ ] 6[ ] 7[ ] 8[ ] 9[ ] VEE: Accounting and Corporate Finance[✔] Economics[✔] Online Course: 1[✔] 2[ ] Course on Professionalism[ ] 
#158




Maximum Covered Loss vs. Policy Limits in MLE
I'm having some trouble wrapping my head around how Maximum Covered Loss, Deductibles and Policy Limits work together when calculating MLE. I'm referencing Mahler Practice Exam #1, question 7 here. http://www.howardmahler.com/Teaching...S1Exam%231.pdf
I know maximum covered loss (MCL) as policy limit (u)  deductible (d). So for the two losses coming from the segment with MCL = 25,000 and d = 1000, i would've calculated their contribution to the likelihood function as S(24,000)^2, i.e. two losses above the policy limit of 24,000. In the solutions though, their contribution to the likelihood function is [S(25,000)/S(1,000)]^2. Can someone please explain to me why this is in an intuitive way? 
#159




The 2 losses are for amounts above 25000. If there were no deductible, their likelihoodx would be S(25000). However, due to the deductible, you receive no information about losses below 1000, so your observation of these two losses is conditional on them being greater than 1000. By the usual formula for conditional probability, their likelihoods are therefore Pr(X>25000 and X>1000)/Pr(X>1000), which is S(25000)/S(1000).

#160




Quote:
Maybe I'm misunderstanding what xbar is for binomial results. If you flipped 10 coins and got 5 heads, and then flipped 10 coins again and got a 7, is xbar 12/2 = 6? Or is it 12/20 = 0.6? I had assumed the former. 
Thread Tools  Search this Thread 
Display Modes  

