Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

GARP 2016-FRR Exam - Topic 3 Question 17 Discussion

Which of the following statements are reasons for mathematical valuation and risk assessment models to be misleading or inaccurate?I . There could be missing factors in models.II . The data used as input for the model could be bad or wrong.III . Model results could be misinterpreted.IV . There could be errors in the derivation of the model.
A) I, II, III IV
B) III and IV
C) I, II, and III
D) I, III, and IV

GARP 2016-FRR Exam - Topic 3 Question 17 Discussion

Actual exam question for GARP's 2016-FRR exam
Question #: 17
Topic #: 3
[All 2016-FRR Questions]

Which of the following statements are reasons for mathematical valuation and risk assessment models to be misleading or inaccurate?

I . There could be missing factors in models.

II . The data used as input for the model could be bad or wrong.

III . Model results could be misinterpreted.

IV . There could be errors in the derivation of the model.

Show Suggested Answer Hide Answer
Suggested Answer: A

by Tamekia at Apr 02, 2026, 03:54 PM

Limited Time Offer

25%

Off

Get Premium 2016-FRR Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Marica
5 hours ago
I think all options are valid. A is the best choice.
upvoted 0 times
...
Marti
5 days ago
I think all four reasons are valid!
upvoted 0 times
...
Chandra
11 days ago
Errors in derivation can really mess things up.
upvoted 0 times
...
Matthew
16 days ago
Wait, are we sure about model misinterpretation being a big deal?
upvoted 0 times
...
Margurite
2 months ago
I agree, bad data is a huge issue too!
upvoted 0 times
...
Kallie
2 months ago
Missing factors can totally skew results.
upvoted 0 times
...
In
3 months ago
I vaguely recall that errors in model derivation can also lead to inaccuracies, which makes me think IV should be considered too.
upvoted 0 times
...
Corinne
3 months ago
I think misinterpretation of results is a common problem we talked about, so III definitely seems relevant.
upvoted 0 times
...
Twana
3 months ago
I'm not entirely sure, but I feel like bad data is a huge issue too, so maybe II should be included as well.
upvoted 0 times
...
Latosha
4 months ago
I remember discussing how missing factors can really skew the results, so I think I would lean towards including I.
upvoted 0 times
...

Save Cancel