Mutual Fund industry today, with
about 34 players and more than five hundred schemes, is one of the most
preferred investment avenues in India.
However, with a plethora of schemes to choose from, the retail investor faces
problems in selecting funds. Factors such as investment strategy and management
style are qualitative, but the funds record is an important indicator too.
Though past performance alone can not be indicative of future performance, it
is the only quantitative way to judge how good a fund is at present. Therefore,
there is a need to correctly assess the past performance of different mutual
funds. Quite simply then a fund generating
more returns than the other is considered better than the other. But this is
just half the story. Return alone should not
be considered as the basis of measurement of the performance of a mutual fund
scheme, it should also include the risk taken by the fund manager because
different funds will have different levels of risk attached to them.Risk
associated with a fund can be defined as fluctuations in the returns generated
by it. The higher the fluctuations in the returns of a fund during a given
period, higher will be the risk associated with it. These fluctuations in the
returns generated by a fund are resultant of two guiding forces. First, general
market fluctuations affecting all the securities present in the market are
called market risk or systematic risk and second, fluctuations due to specific
securities present in the portfolio of the fund, called unsystematic risk. The
Total Risk of a given fund is sum of these two and is measured in terms of
standard deviation of returns of the fund.
Systematic
risk is measured in terms of Beta, which represents fluctuations in the NAV of
the fund vis-à-vis market. The more responsive the NAV of a mutual fund is to
the changes in the market; higher will be its beta. Beta is calculated by
relating the returns on a mutual fund with the returns in the market. While
unsystematic risk can be diversified through investments in a number of
instruments, systematic risk cannot. By using the risk return relationship, we
try to assess the competitive strength of the mutual funds vis-à-vis one
another in a better way. It should be
appreciated that there is a level of risk that a fund has taken to generate this
return. So what is really relevant is not just performance or returns. What
matters therefore are Risk Adjusted Returns (RAR).
The
only caveat whilst using any risk-adjusted performance is the fact that their
clairvoyance is decided by the past. Each of these measures uses past
performance data and to that extent are not accurate indicators of the future.
There
are different statistical parameters available on which a fund may be analyzed.
These are:
The
most basic of all measures- Standard Deviation allows evaluating the volatility
of the fund. Alternatively, it allows measuring the consistency of the returns.
Volatility is often a direct indicator of the risks taken by the fund. The
standard deviation of a fund measures this risk by measuring the degree to
which the fund fluctuates in relation to its mean return, the average return of
a fund over a period of time.
A security that is volatile is also considered higher risk because its
performance may change quickly in either direction at any moment.
A
fund that has a consistent four-year return of 3%, for example, would have a
mean, or average, of 3%. The standard deviation for this fund would then be
zero because the fund's return in any given year does not differ from its
four-year mean of 3%. On the other hand, a fund that in each of the last four
years returned -5%, 17%, 2% and 30% will have a mean return of 11%. The fund
will also exhibit a high standard deviation because each year the return of the
fund differs from the mean return. This fund is therefore more risky because it
fluctuates widely between negative and positive returns within a short period.
Beta
is a fairly commonly used measure of risk. It basically indicates the level of
volatility associated with the fund as compared to the benchmark.
So quite naturally the success of Beta is heavily dependent on the correlation
between a fund and its benchmark. Thus if the fund's portfolio doesn't have a
relevant benchmark index then a beta would be grossly inadequate.
A beta that is greater than one (ß >1)
means that the fund is more volatile than the benchmark, while a beta of less
than one (ß <1) means that the fund is less volatile than the index. A fund
with a beta very close to 1 (ß ~1) means the fund's performance closely matches
the index or benchmark.
If,
for example, a fund has a beta of 1.03 in relation to the BSE Sensex, the fund
has been moving 3% more than the index. Therefore, if the BSE Sensex increased
10%, the fund would be expected to increase 10.30%.
Investors
expecting the market to be bullish may choose funds exhibiting high betas,
which increase investors' chances of beating the market. If an investor expects
the market to be bearish in the near future, the funds that have betas less
than 1 are a good choice because they would be expected to decline less in
value than the index.
The
success of Beta is dependent on the correlation of a fund to its benchmark or
its index. Thus whilst considering the beta of any security, investors should
also consider another statistic- R squared that measures the Correlation.
The
R-squared of a fund advises investors if the beta of a mutual fund is measured
against an appropriate benchmark. Measuring the correlation of a fund's
movements to that of an index, R-squared describes the level of association
between the fund's volatility
and market risk, or more specifically, the degree to which a fund's volatility
is a result of the day-to-day fluctuations experienced by the overall market.
R-squared values range between 0 and 1, where 0 represents no correlation and 1
represents full correlation. If a fund's beta has an R-squared value that is
close to 1, the beta of the fund should be trusted. On the other hand, an
R-squared value that is less than 0.5 indicates that the beta is not
particularly useful because the fund is being compared against an inappropriate
benchmark.
Alpha = (Fund return-Risk free return) - Funds
beta *(Benchmark return- risk free return).
Alpha is the difference between the returns
one would expect from a fund, given its beta, and the return it actually
produces. An alpha of -1.0 means the fund produced a return 1% higher than its
beta would predict. An alpha of 1.0 means the fund produced a return 1% lower.
If a fund returns more than its beta then it has a positive alpha and if it
returns less then it has a negative alpha. Once the beta of a fund is known,
alpha compares the fund's performance to that of the benchmark's risk-adjusted
returns. It allows you to ascertain if the fund's returns outperformed the
market's, given the same amount of risk.
The higher a funds risk level, the greater the returns it must generate in
order to produce a high alpha.
Normally
one would like to see a positive alpha for all of the funds owned. But a high
alpha does not mean a fund is doing a bad job nor is the vice versa true as
alpha measures the out performance relative to beta. So the limitations that
apply to beta would also apply to alpha.
Alpha
can be used to directly measure the value added or subtracted by a fund's
manager.
The
accuracy of an alpha rating depends on two factors:
1) The assumption that market risk, as measured by beta, is
the only risk measure necessary;
2) The strength of fund's correlation to a chosen benchmark
such as the BSE Sensex or the NIFTY.
Sharpe
Ratio= Fund return in excess of risk free return/ Standard deviation of Fund.
In case funds have low correlation with indices or benchmarks, they should be
evaluated using the Sharpe ratio. Since it uses only the Standard Deviation,
which measures the volatility of the returns there is no problem of benchmark
correlation.
The higher the Sharpe ratio, the better a funds returns relative to the amount
of risk taken.
Sharpe ratios are ideal for comparing funds that have a mixed asset classes.
That is balanced funds that have a component of fixed income offerings
