Fact or fiction?

[Sukumar.N]

William sharpe propounded the capital asset pricing model in 1962, for
which he was honoured with the Nobel Prize in Economic Sciences in
1990. The
reason why the most prestigious award was bestowed upon him was that
with this invention, the subjectivity revolving around stock prices
boiled down to one formula. The cornerstone of that model was ‘beta’ ,
which compares the sensitivity of a stock’s price movement to that of
the broader index.

This can be easily explained with the help of an example. Suppose the
beta of Infosys Technologies is 1.2; this implies that with every 1%
change in the index, the stock price of Infosys should move by 1.2% in
the same direction. Higher the beta, higher will be the volatility in
the stock price, and hence, riskier the investments . Lesser the beta,
lesser will be the volatility in the stock price, and hence, it will
be safer to invest in that stock.

Also, if beta is positive, then the stock will move in the same
direction as the index, which means that the stock price will go up if
the index goes up and viceversa . If the beta is negative, the stock
will move in the opposite direction visà-vis the index, but in
reality, beta is rarely negative. The beta of the index or market is
pegged at 1.
Perhaps, all equity analysts use beta to estimate the cost of equity.
In this edition, ET Intelligence Group tries to find out how powerful
is the forecasting ability of beta in the context of the Indian stock
market. Our sample comprises stocks of 44 companies, which have
performed most consistently over the past decade.

It includes companies like Reliance Industries, Tata Steel, HDFC,
Hindustan Unilever and Colgate-Palmolive from the fast-moving consumer
goods (FMCG) sector; Ambuja Cements and ACC from the cement sector;
auto majors like Mahindra & Mahindra and Tata Motors; engineering
giants like ABB, L&T and Siemens; besides leading stocks from pharma,
financial services, hospitality and information technology sectors.
This has been done to ensure that all sectors in the economy are duly
represented in the sample.

To check its effectiveness, we have taken the beta at the start of a
year and then observed how the stock fared visà-vis the Nifty in that
year. For instance, the beta of ABB was 0.76 on December 31, 1998.

This indicates that ABB’s stock was expected to rise less than the
Nifty and fall less than the Nifty. In 1999, ABB’s stock price fell by
49.7%, while the Nifty was up by 66.2%. The beta logic did not hold in
this case because if the beta is positive, both the stock and Nifty
should move in the same direction, instead of the opposite direction.
The exercise was repeated for 44 stocks over 10 years from the start
of calendar year 1999 to ’08 till date.

We ended up with 440 observations, as there are 44 stocks over the
course of 10 years. The logic of beta holds for only 172 of such
observations, which implies a success rate of 39%. This shows that the
odds are against the investor if he takes a call based on beta. In
some cases, the success rate can be even worse. The chart clearly
shows that for ABB, the basic rule of beta holds good only for one
year out of 10. It must be observed that beta is positive for all 10
years. The beta logic does not hold in years ’01 to ’08 because though
the beta is less than 1, ABB’s stock has shown higher volatility. This
shows that estimating one-year returns considering the beta at the
start of the year can be a self-defeating exercise.

At this point, we must inform our readers that the purpose of our
exercise is not to belittle the work done by William Sharpe. We only
want to highlight the fact that the theory does not yield results, at
least in the Indian context. However, the story does not end here.

Upon further analysing data, we found that stocks with a beta higher
than 1 — i.e. stocks which rise more with every rise in the market and
fall more with every fall in the market — have given close to three
times the returns of stocks with beta less than 1. To establish this,
we made two portfolios of stocks:

Portfolio 1

includes stocks which had a beta higher than 1 for a major part of the
past 10 years. It includes stocks like Reliance Industries, Larsen &
Toubro, Tata Steel, ACC, Tata Motors, Wipro et al.


Portfolio 2

includes stocks which had a beta of less than 1 during most years in
the past decade. It includes stocks like Asian Paints, Hindustan
Unilever, Hero Honda, Colgate-Palmolive and Indian Hotels.

While the high beta portfolio has yielded a return of 19.7% per annum
on an average, the low beta portfolio has given only 7.1% return per
annum in the past 10 years. Though in hindsight, this pattern appears
to be very obvious, it must be noted that the outperformance is after
including ’08, which has seen the worst crash of all times. Also, the
extent of outperformance is beyond the estimate of market
intellectuals.

This shows that investors are better off investing in companies having
beta higher than 1, rather than investing in companies with beta less
than 1. In simple words, investors are better off betting money on
seemingly risky stocks. However, the investment must be for a very
long term, since we have already seen in the case of ABB that
investing for one, two or three years based on beta can be risky.

Another reason why keeping an eye on beta is important is that it
tells investors what the market thinks of a particular stock. Suppose
there is a company which is performing better than average, but the
stock market does not give due consideration to this fact, and
therefore, the stock does not move. In such cases, the beta tends to
be lower. An astute investor should always be wary of investing in
such stocks, as it indicates that the stock market is not discounting
the fundamentals in stock price.

Though it is clear that beta is one of the important factors to be
considered while making investments, what is more important is how one
uses it.

Source : Economic Times