Which of the following actions is most likely the result of applying Bayes’ theorem of conditional probability? A fundamental analyst revises a stock recommendation when:
A) the firm experiences a major fire that destroys its production line. B) the firm issues an earnings report. C) she revises her inflation expectations. * From Qbank
i would think B).
after a firm issues an earnings report - stock expectations are revised upwards if earnings are higher, lower if lower earnings.
Why not A) this is an unforeseen circumstance, and cannot be anticipated.
Why not C) This would be built into expectations of share price - by the analyst. So you would not be using Bayes’ for that.
c
A. Because that will affect future earnings and growth.
Pretty divergent:)
I think B. But based on your history of posting the most questionable and possibly abstract questions, its probably A.
I reread the kaplan rationale but still don’t have idea about it…
Answer: C
Kaplan Rationale:
A fundamental analyst bases recommendations on firm or market fundamentals such as expected earnings. The fire would signal an unexpected change in the firm’s fundamentals as would a revised earnings announcement. Revising a recommendation based on the probability of a given level of inflation is an example of applying a Bayesian framework to an expectation. That is, the firm’s performance is based conditionally on the probability of a given level of inflation.
good practice for my review. Thanks Frank.
A) the firm experiences a major fire that destroys its production line.
B) the firm issues an earnings report.
C) she revises her inflation expectations. (perhaps this was the hint to choose C as expectations are derived based on calculated probabilities…)
Thanks arigolden. It makes sense.