This course integrates all the learning from the first three courses and guides the learner about ways of building a portfolio of strategies and integrating the same into a hedge fund. In the first part of the course, you will be taught ways of measuring the contribution of a strategy to a portfolio in terms of risk and return. You will be able to appreciate the consequences of including a strategy to a new as well an existing portfolio. Next, you are taught various ways of conducting the tilting analysis in order to determine the optimal weight to be placed on each strategy. After this you will learn to develop techniques for minimizing overall portfolio risk. You will also get a basic overview of the regulatory framework that is applicable to hedge funds. You will know about different types of investors and the expectations of each type of investors.
Mutual fund performance
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Module 2
In this module you will lean how to perform style analysis and performance attribution. You will also learn some facts about the mutual fund performance and timing measurement. In the second half of the module you will learn how to calculate the expected returns and risk. The module ends with an understanding of the utility theory.
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Ramabhadran ThirumalaiAssistant Professor
Indian School of Business
Prasanna TantriSenior Associate Director
Center for Analytical Finance
[MUSIC]
Learning Outcomes.
After watching this video, you will be able to, one,
understand the performance of mutual funds.
>> Now I want to present to you in the last part of this lecture the idea of,
do mutual fund managers actually beat the market?
And this ties in with what we discussed in the early part of this lecture,
which is the efficient markets part.
And if you remember there, we said one way of testing if the markets
are efficient is to see if people have indeed managed to beat the market.
And if the market is largely efficient, it should be the case that a large fraction
of managers, at least, cannot simply beat the market hollow, right?
So what somebody did, this a typical study by Professor Burton Malkiel.
This is an older study but further studies also confirm evidence like this.
He basically took all mutual funds around at that time for a 20-year period.
And essentially,
stacked them in a histogram based on their Jensen's Alphas and what do you see?
You see that a majority of these Alphas are stacked around zero,
are concentrated around zero.
Now that shouldn't come as a surprise.
This should tie in with exactly the statement I made before that
markets are largely, indeed, efficient.
Now to be sure, I'm not saying that money cannot be made.
If you look on the far right of this graph, there is somebody who is two,
three standard deviations, close to three standard deviations above the mean.
And of course, on the extreme left, there was people who did really, really badly,
and they're three standard deviations close to below the mean.
So obviously, you have really, really good performers and really,
really bad performers.
But the key takeaway here is a large fraction of them bunch up around zero.
In other words, this is some sort of evidence that the market is indeed largely
efficient to the extent that it's not so easy to make money.
So now another representative piece of research,
especially slightly more recent research, is this paper by Daniel Grinblatt,
Titman and Wermers, which was published in 97.
And what they essentially do is they take a bunch of
known risk factors on the right-hand side, like the Farmer and
French risk factors, plus there are the momentum factors on the right-hand side.
And what they do is they essentially take virtually every fund in existence and
essentially benchmark the returns of each of these funds against these factors.
And what you see in the table are the alpha numbers.
What you see in the parentheses are the t-statistics.
And what you see really is that except for
a few numbers of none of them is statistically significant.
Which is to say, the alpha or average for the universe of mutual
fund managers is not really statistically significant.
In other words, mutual funds in aggregate are not beating the market.
Yes, in certain segments,
during certain time periods, mutual funds are beating the market.
Now again, this begs the old question, was this just skill or was this pure luck?
Now other pieces of evidence from research suggest that there is manager persistence,
not fund persistence.
In other words, the question has been asked, if a fund does well today,
this year, will it do well next year?
Well, it turns out the right question to ask is not the way I asked it just now.
You should ask the question as follows.
If a fund manager outperforms this year,
is it likely that he will outperform next year?
In other words, the fund manager could've switched jobs.
So the persistence is about the manager, rather than the fund.
The other thing they noticed in their paper, Chevalier and
Ellison, also try and examine the characteristics of managers which
make them better mutual fund managers.
They find that age matters.
Younger managers are better.
Managers with MBAs or better, so that's a big shout-out to all B schools out there.
And they also find that undergrad institution matters.
Now undergrad institution might simply be a proxy, and
I'm speculating here, for something like their SAT score, or
the sort of type of personality that a person might have, etc.
But certainly, these are the findings, right?
Now after all of this having been said and done,
if the average mutual fund manager doesn't beat the market and
if a large fraction of mutual fund managers don't beat the market, and
tying back to our initial part of the lecture, if markets are largely efficient.
And this having been proved through a battery of performance measures, then
the final question that one has to ask is, why should I invest in mutual funds?
Well, there is very good reasons to invest in mutual funds.
Even if we know all of these facts that the average mutual funds
manager doesn't add value, in terms of beating the market.
Number one, ready-made diversification.
Remember the first lesson of finance theory.
In fact, if there's one lesson of finance theory which one has to master
at a personal investing level, it is that diversification is a good thing.
In other words, never put all your eggs into one basket.
Now as an investor, if you're like me, you're a small investor.
Now diversification amongst a bunch of stocks, say 100 stocks, might
just be impossible for me alone, simply because I have a capital constraint.
In other words, there is a limit to the amount of money
I can invest amongst a broad array of stocks.
Whereas with a mutual fund, with a very small amount as an entry amount,
I can actually buy in to this large pool of investment and
buy ready-made diversification.
And that's a great reason, number one, to invest in mutual funds.
Number two, the opportunity costs of keeping up with markets.
Remember, these guys are professionals.
Albeit the fact that most of them don't add value, this is their daytime job.
Now my daytime job is teaching.
Now even if I thought I had some expertise in investing,
now I would have to give up my daytime job if I had to do a proper job
of monitoring my portfolio on a day to day basis and a month to month basis, etc.
But the fact of the matter is I might simply enjoy what I'm doing.
For example, I like teaching, and hence I would not give up my job.
I would rather delegate the management of my money,
my retirement fund, to a professional money manager.
Number three, transaction costs.
Basic idea here is these mutual funds are large institutions.
And in terms of brokerage and transaction costs, it is almost certain that they have
a huge advantage in transaction costs, compared to an investor like you and me.
So that is another good reason why one might actually choose to
invest in mutual funds.
Of course, there's always that final reason called hope, which is basically
the idea that maybe, just maybe, I will hit upon the next Fidelity Magellan fund,
which of course, in the 70s and 80s, were the superstar mutual fund,
and actually have a happy, cushy retirement, right?
So all of these are good reasons.
However, at this point, we have sort of restated our lecture.
Now you have to make up, as intelligent students of finance,
your mind about what your philosophy is regarding markets.
If you are one of those who believe that markets are largely efficient and
hence only a few people will beat the market, and most important,
as an investor, it is unlikely that a priori,
that is before the fact, I can identify the superstar.
Now if I could identify the superstar at the beginning of the year, no problem.
We would all actually entrust him or her with our money.
The big problem is we can only identify superstars looking backwards,
not looking forward.
This is sort of like what Steve Jobs said.
You can always connect the dots looking backward, not necessarily forward.
So now if you can't really identify the superstars going forward, what do you do?
Well, if you are like me and
if you believe that the market is largely efficient, then you index.
In other words,
you invest in an investment vehicle which simply seeks to mimic a well-known index.
So, for example, you might choose to mimic an S&P 500.
Or, if you're in the India, you might choose to mimic the NIFTY.
And there, essentially, you're betting on the market movement.
So you're saying, I'm a long-term investor.
I believe that in the long run, so and so index is going to perform well.
So I'm going to pick a low cost alternative.
An index fund, or nowadays what is known as an exchange traded fund, which
has its sole objective to simply mimic the performance of this particular index.
Hence, stick all your money into that.
And with lots of prayer and hope, we might just get there and
have a happy retirement.
So that's efficient markets and portfolio performance measurement, thanks.
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