Assessing the risk of an asset requires that we
have some sense for the range of possible outcomes.
For example, a judge sentencing a youthful offender
might consider the likelihood of different scenarios:
- worst case (pessimistic), the offender will
commit only another minor crime;
- expected case (normal), she will commit no
more crimes
- best case (optimistic), she will prevent others
from committing crimes
Given this distribution, the judge might suspend
the youthful offender's sentence.
Predicting a range of outcomes and assigning
to them different probabilities can give further
insight into risk. Using a probability distribution,
we can model different outcomes. For example,
the probability distribution of the results of
throwing two dice is shown in the table to the
right -- |
Example
|
Result |
Probability |
2 |
1/36 = 2.8% |
3 |
2/36 = 5.6% |
4 |
3/36 = 8.3% |
5 |
4/36 = 11.1% |
6 |
5/36 = 13.9% |
7 |
6/36 = 16.7% |
8 |
5/36 = 13.9% |
9 |
4/36 = 11.1% |
10 |
3/36 = 8.3% |
11 |
2/36 = 5.6% |
12 |
1/36 = 2.8% |
Total |
36/36 = 100% |
The most likely throw is a 7 -
but it happens only one-sixth of the time. Possible
outcomes range from 2 to 12, although the likelihood
of throwing a 2 or 12 is significantly lower
than throwing a 7. What if you wanted to throw
at least a 7? You would have to consider variability
in assessing risk. Even though 7 would be the
most frequent throw, you might throw less. In
fact, there is a 41.6% chance that you will
throw less than a 7.
|
2.2 Risk of a Single Asset