But what if I now tell you that Manager B has been around for
20 years and Manager A only for 5 years?
S clearly, you would say Manager B has more experience and may be, he has
a greater Drawdown because that Drawdown happened when Manager A did not exist.
If Manager A had existed then, may be he would have experienced a greater loss.
So, the way to solve the shortcoming of the MAR ratio is the CALMAR ratio.
And the CALMAR ratio is quite simply the same ratio of the MAR ratio but here,
instead of looking at the worst possible loss over its inception.
Basically, here, you're looking at the worst loss over the last 36 months or
the last 3 years.
So, CALMAR and MAR ratio need to be used together
because maybe the idea of a maximum loss of 5% within the last 3 years.
Does not give you an accurate picture because maybe the fund is
actually far more riskier than that and has experience of 46% loss 15 years ago.
So you need to use both but at least you can be sure that using
the CALMAR ratio you're comparing apples with apples.
And you're comparing managers who have been in existence and
over the same time period.
And clearly, this is something that is obviously very important to mention.
When you are doing this filtering, when you are extracting
from the database, managers based on return statistics,
risk measurements percentages of positive months and etc., etc.
You need to make sure that you are comparing apples with apples and
that all the managers have a similar mandate when investing their funds.
So in conclusion of this set of two videos,
we've seen here that to perform the peer group analysis.
What you need is a good database that will have
managers which are ranked by categories.
And we need to make sure that this is done professionally and each category,
you do find managers that have a specific investment philosophy.
And then, basically, you can filter that data base using
criteria's which best suit your investment philosophy.
I give you one example.
If you want to assemble a fund of funds which will be low risk,
then you will put a lot of emphasis on extracting from your database.
Managers who have the highest proportion of positive months
who have the minimum draw down, who have the lowest volatility.