Behavioral Finance Perspective Blue Box Example #3

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Andrew3032's picture

Reading 7 page 41-42

Quite a convuluted process to wade through, if one were to actually perform all the necessary calcs.

I would like to think that the main objective on this reading would be to focus on areas that show up in the EOCs which appear to be more conceptual based understanding of the reading rather than burning up too much time making sure that one understands an example such as this one.

Would any retakers care to comment on this?  I know I’ve heard to make sure and practice these blue boxes at this level in addition to the EOCs, but this particular example just begs the question…. “My God man???!!!”

When the going gets weird, the weird turn pro.

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niraj_a's picture

i wouldn’t use a lot of time mastering behavioral finance. just know the main terms and what they mean. you should be able to identify a behavioral finance trait based on a given situation etc. that’s all.

noscrubs008's picture

Andrew3032 wrote:

I still don’t understand the Solution to this example. How did the author come up with such allocation? Could someone explain, please?

“Don’t run when you lose, don’t whine when it hurts. It’s like the first grade, Jerry… nobody likes a crybaby.”, Gordon Gekko.

cpk123's picture

do the search …. it has been discussed posted multiple times before please.

CP

noscrubs008's picture

cpk123 wrote:
do the search …. it has been discussed posted multiple times before please.

Thank you cpk123. I’ve found what I need in your old post. I’ll quote the answer here for those who haven’t found it.

cpk123 wrote:

1. Assume the second investor puts X amount into Layer 3 and the rest in Layer 1 (2000000 - X). You can find X using the following equation :

(2M - X)(1 + 0.01) + X (1 - 0.5) = 1.8M

Note that Layer 1 is expected to yield 1% and Layer 3 -50% with 15% prob. Since the first Layer is risk-free, the above allocation should result in 1.8M, which happens to be his safety level, with 15% probability.

2. Solve the equaton for X:

X = 431,373 (21.57%)
(2M - X) = 1,568,627 (78.43%)

- The 2nd investor would get 2,067,451 with 50% prob:

1,568,627 (1 + 0.01) + 431,373 (1+0.12) = 2,067,451 (12% of return given in the vignette)

- He’d get 2,339,216 with 35% prob:

1,568,627 (1 + 0.01) + 431,373 (1+0.75) = 2,339,216 (75% of return given in the vignette)

You might wonder why the 2nd layer is not being used at all. I bet CFAI won’t draw up a question with more than one unknown :)

I guess that given the low return on Portfolio 2 - with 4.6% - a better return is obtained with the portfolios layers 1 and 3.

“Don’t run when you lose, don’t whine when it hurts. It’s like the first grade, Jerry… nobody likes a crybaby.”, Gordon Gekko.

Andrew3032's picture

The op doesn’t really have anything to do with “how to calculate”.

When the going gets weird, the weird turn pro.

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