Central Bank of Oman Occasional Paper No. 2006-2
MSM and the Efficient Market Hypothesis:
An Empirical Assessment
Central Bank of Oman
Economic Research and Statistics Department
Post Box-1161, Ruwi-112, Sultanate of Oman
Tel: 968-24702222, Fax: 968-24788513
E-mail: cboresb@omantel.net.om
Website:www.cbo-oman.org
Economic Research and Statistics Department
http://www.cbo-oman.org
CBO Occasional Paper No. 2006-2
Central Bank of Oman Occasional Paper No. 2006-2
MSM and the Efficient Market Hypothesis:
An Empirical Assessment
Ali Hamdan Al-Raisi
&
Sitikantha Pattanaik
CENTRAL BANK OF OMAN
Economic Research and Statistics Department
Post Box-1161, Ruwi-112
Sultanate of Oman
Tel: 968-24702222, Fax: 968-24788513
E-mail: cboresb@omantel.net.om
Website: www.cbo-oman.org
October 2006
CBO Occasional Paper No. 2006-2
FOREWORD
The movement in prices of stocks listed in the Muscat Securities Market
(MSM) represents one of the most closely watched and discussed
financial market variables in Oman. In view of the volatility seen in the
MSM-30 Index in the recent years, quite in line with the trends in other
regional and global stock markets, a common market curiosity has
generally been to better understand what may be causing cycles of
“overshooting and subsequent corrections” - if not “bubble and
subsequent crash” in stock prices, and how could one take a view on the
rational valuation of a stock. The debate on the Efficient Market
Hypothesis (EMH) is extremely relevant in this context. Believers in
EMH argue that market price of a stock always reflects all available
relevant information that should go into valuation, and hence, the
current price of a stock is its fair value. No amount of serious analysis of
available information about a stock can help one in identifying the
undervaluation or overvaluation of a stock as a source of excessive
profit, and any extra return accruing to anybody from such market
analysis could actually be a compensation for extra risk that the investor
may be taking, knowingly or unknowingly. As per the other extreme
viewpoint, stock prices are often driven by “fads and fashions” and
“mob psychology”, quite unrelated to fundamental value-determining
factors, and hence, there could be opportunities to beat the market.
In this issue of the CBO Occasional Paper, Mr. Ali Hamdan and
Mr. Sitikantha Pattanaik study this debate on Efficient Market
Hypothesis (EMH) in the specific context of the movement of MSM-30
index over the period 1997-2006. While random-walk test equations
indicate presence of serial correlation in daily return data for the MSM30 index, Auto Regressive Conditional Heteroscedasticity (ARCH) and
Generalised Autoregressive Conditional Heteroscedasticity (GARCH)
coefficients exhibit presence of conditional variance, which at times
could be predictable, if not the return itself. Both these tests indicate
rejection of the EMH for the MSM-30 index, even though there could be
other rational reasons as discussed in the study yielding such results,
which could in fact be found even in an efficient market. The study
emphasizes the importance of information sensitive investment
decisions backed by more equity research in Oman, so as to further
enhance the informational efficiency of the MSM. The views expressed
in this study, as is the case with all issues of CBO Occasional Papers,
are of the authors and not of the CBO.
Hamood Sangour Al-Zadjali
The Executive President
CBO Occasional Paper No. 2006-2
MSM and the Efficient Market Hypothesis:
An Empirical Assessment
Ali Hamdan Al-Raisi
&
Sitikantha Pattanaik*
Efficient stock markets are often seen as the symbol of modern day capitalism.
The widespread ownership of firms is also viewed as “peoples capitalism”,
that is believed generally to enhance the role of finance in promoting real
economic growth while also distributing the benefits of economic progress
more widely.
The rational market view even presents stock markets as
illustrations of competitive markets. While Baumol (1965) had viewed stock
market as “a relatively close approximation of a perfect market”, both Alfred
Marshall, the founder of partial equilibrium analysis, and Leon Walras, the
founder of general equilibrium analysis, had cited stock market as a real-world
case of a competitive market. Competitive stock market was viewed as
essential in neoclassical economics for encouraging capital accumulation and
allocating the capital to socially optimal uses. In a competitive market it is the
pricing mechanism which holds the key, and in respect of a stock market, the
price of a stock is always believed to be informationally efficient. The
efficient market hypothesis, thus, suggests that the market price of a stock
reflects all available information, leaving thereby no scope for yielding excess
returns through massaging of any market information. Informational
efficiency does not allow anybody to consistently beat the market, and higher
returns in such markets can result only from exposure to higher risks. The
“efficient market hypothesis (EMH)” for common stocks has received
significant empirical support in the past, and as noted by Jensen (1978), “there
is no other proposition in economics which has more solid empirical evidence
supporting it than the Efficient Market Hypothesis”.
At the other extreme, there is another equally strong view which suggests that
stock markets are paper casinos, where greedy and often ignorant small
investors tend to loose in the process of following the market trends.
Speculation driven markets, as emphasized by Keynes, Veblen, Galbraith and
Shiller, have little to do with efficient pricing of new information. As per the
Marxian interpretation, stock movements and transfers reflect the result of
gambling at the stock exchange, where “the little fish are swallowed by the
sharks and the lambs by the wolves”. The markets, according to such views,
are driven by investors’ fads and fashions, instead of economic fundamentals.
Pure speculation, that often dominates such markets, is a psychological
phenomenon, where one may buy stocks purely on the basis of expectations
and behaviour of other market participants. As noted by Keynes (1936),
people in general could be too timid, greedy, impatient or nervous about their
investment to take long-term views on valuation, and it is their zest for making
*
The authors are grateful to both the Capital Market Authority (CMA) and the Muscat
Securities Market (MSM) for their encouragement and support. The views expressed in this
paper reflect the personal research findings of the authors, and errors in the paper, if any,
should be ascribed to the authors only.
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CBO Occasional Paper No. 2006-2
money quickly that the spontaneous mob optimism mostly drives the stock
markets. Such short-term mob expectations are not based on information, but
on “what average opinion expects the average opinion to be”. When the
market is driven by short-term mob psychology, even the very few long-term
investors may join the bandwagon to avoid the risk stemming from a policy of
going against the market.
In the context of this long standing debate between the rational market view
holding the supremacy of market efficiency, and the other extreme view
suggesting the predominant role of mob psychology and speculation in a
market, empirical research on the subject stands quite divided. This debate
merits a specific revisit in the context of the recent volatility that has been
witnessed in the stocks trading in the Muscat Securities Market (MSM).
Following the strong bullish trend in regional stock markets, and supported
by the initial enthusiasm about Omantel, the MSM 30 index exhibited a major
surge till the mid of 2005, which was subsequently taken over by a notable
correction in the first half of 2006, again reflecting the global and regional
market trends as well as the tapering off of strong expectations from the
Omantel. While in just one year time the index jumped by 57.6 percent (i.e.
end of June 2005 over end of June 2004), in the next one year the index fell by
10.8 percent (i.e. end of June 2006 over end of June 2005). The most startling
aspect during this phase of up-down cycle in the stock market in Oman has
been that the macroeconomic conditions continued to remain rather strong and
resilient, implying that the volatility in MSM was not reflective of the
macroeconomic conditions prevailing in the country. This phase of falling
stock prices in oil dependent Gulf economies in the face of high oil prices has
also been viewed as the Gulf conundrum, which calls for a realistic assessment
of the informational efficiency of these markets.
Against this backdrop, this study empirically evaluates the informational
efficiency of the MSM, and while narrating the theoretical and empirical
debate on the subject, it also aims at highlighting the important role of both
informed investors and greater equity research in further enhancing the
efficiency of the market. The concept of efficiency used here relates to
“informational efficiency” and not “allocational efficiency”. The scope of the
study is limited to empirical assessment based on available data for the MSM.
Section-I outlines the debate on efficient market hypothesis, which is often
overlooked by uninformed investors in their search for high returns. The
performance of the MSM in the past several years is reviewed in Section-II.
The empirical estimates of market efficiency for the MSM are setout in
Section-III. Section–IV contains a few concluding observations.
Section-I: The Efficient Market Hypothesis Debate
While walking on the Al Markazi street if you find a RO 50 currency note
lying unpicked by anyone else prior to you, an economist would immediately
advise you not to bother, since if it were a genuine RO 50 bill, then some
body else before you must have picked it up. The efficient market hypothesis
is often best explained with such a simple example to make the point clear to
the investors that there is no new information that can help them in beating the
market, since an efficient market prices all new information rapidly, leaving
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CBO Occasional Paper No. 2006-2
little scope for anybody to reap excess returns on a consistent basis. Based on
the assumption that market prices fully incorporate expectations and
information of all market participants, three forms of market efficiency are
commonly discussed in the literature. Weak form efficient market hypothesis
suggests that current price of any asset does not contain any information that
can be useful to predict the future price behaviour. As per this view, any
technical analysis or fundamental analysis that aims at predicting the future
course of market prices from past data, cannot yield correct results (such
analyses are ok as long as one may be selling those ideas instead of using
himself). Semi-strong form efficient market hypothesis states that all publicly
available information such as financial statements, strategy and past history,
etc. are fully reflected in the current price of the asset. Event studies, that track
the price developments before and after the announcement of such
information, often help in assessing how quickly any new information gets
priced in the market (in fact the market discounts most of the new
information much ahead of the actual release of the information, starting from
a change in the interest rate to announcement of dividends). Strong form
efficient market hypothesis advocates that all public
as well as private
information are fully reflected in the price and, therefore, agents having even
inside information cannot constantly beat the market. Fama (1970, 1991).
Lo and MacKinlay (2002) raised the most valid empirical question as to
whether it is “possible for stock market prices to be predictable to some degree
in an efficient market?”. They explained succinctly that if the prices are not
forecastable, that is not always an indication of efficiency, and similarly,
market efficiency does not necessarily mean that prices cannot be forecasted.
As per their practical version of the efficient market hypothesis, it could be
difficult, though not impossible, to generate consistently superior returns in a
market. Such beating the market performance could arise from some
competitive advantage associated with superior information, superior
technology, financial innovations, etc. In an efficient market, thus, “the only
way to earn positive profits consistently is to develop a competitive advantage,
in which case the profits may be viewed as the economic rents that accrue to
this competitive advantage”. If the markets were perfectly efficient, then
return to information gathering and analysis could be zero. In practice,
investment on information gathering and analysis helps in generating higher
returns in relation to what the efficient market hypothesis would suggest, and
hence, the profession of financial analysis has become so lucrative over the
years. Higher profits resulting from investment on information gathering and
analysis, thus, represent economic rent arising from activities that enhance the
competitive advantage. The most relevant related question then is who pays
these rent in a competitive market. According to Black (1986), it is the noise
traders, who trade on noise rather than fundamental information, pay such
rent. This line of assessment clearly sends a warning signal to investors who
trade on pure noise and completely ignore the importance of information and
fundamental value analysis.
There is an equally strong counter view which almost ridicules the practical
relevance of analysis driven investments. Ashley (2003) noted in this context
that “much of what is said and written about in financial markets is often
dreadful rubbish. As we all know, the truth does not count in finance, it’s what
everybody else believes that is important.” When the market is dominated by
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speculators aiming at maximizing short-term profits, more than anticipating
the extremely difficult future earnings prospects of a stock, the analysts, like
any other common investors, tend to anticipate the much easier mob
psychology. Emphasizing the role of mob psychology on the behaviour of
uninformed investors, and hence the markets, Keynes(1971) noted that the
ignorance of even the best-informed investors about the more remote future is
much greater than their knowledge. If even the best informed are completely
informed, the vast majority of people buying and selling securities make their
decisions without possessing even the rudiments of the knowledge required for
a valid judgement. In such a state of ignorance, they are prey of hopes and
fears that are easily aroused, and just as easily dispelled, by transient events.
The so called best informed may often profit by anticipating mob psychology
rather than the real trend of events.
Mob psychology assumes such great importance because of the dominance of
financial professionals and speculators, with very short investment horizon but
high return expectations. Such investors do not intend to stay invested in any
stock for long, and are constantly in search of an opportunity to resell the
stock to the mob. Every buy and sell decision, thus, requires predicting the
mob psychology. The markets are accordingly driven by “what average
opinion expects the average opinion to be”. In hindsight, the experience with
Omantel IPO in Oman somewhat vindicates the role of mob psychology in the
stock market. But history is replete with such examples. Prior to bursting of
the technology bubble in the late 1990s, for example, Lowenstein (1996)
wrote that “investing in stocks has become a national hobby and a national
obsession. People may denigrate their government, their schools, their soiled
sports stars. But belief in the market is almost universal. To update Marx, it is
the religion of the masses”.
The bigger fool syndrome often gives rise to stock market bubbles, and
eventual crashes, clearly unrelated to fundamentals. Surowiecki (2004), who
strongly believes in “the wisdom of crowds”, also recognizes that “bubbles
and crashes are textbook examples of collective decision making gone
wrong”. Bubbles are typical characteristics of a stock market because of the
bigger fool syndrome, that is, one may purchase a stock at a high price
because there will be somebody else (i.e. the bigger fool) to buy at an even
higher price, irrespective of the fact that both prices may be quite unjustified
in terms of underlying fundamentals. This does not happen in markets for
goods and services ( i.e. nobody buys a car, TV or a cell phone with the only
intention to resell at a higher price, and even when one wants to resell after use
for some time, it would be quite difficult to get bigger fools like what one may
get in case of stocks). Because of the presence of bigger fools, stock prices
tend to overshoot the fair value. Unlike goods and services market, of course,
there is always uncertainty about the valuation of a stock. However, even
when full information is made available (through an experiment with known
dividend flows for the number of years up to which a firm may remain in
production), market prices may still exceed the discounted present value of all
known dividend earnings, because of the bigger fool syndrome. Unlike periods
of orderly market behaviour when expectations are more uneven, during
periods of bubbles and the eventual corrections expectations increasingly
converge and become unidirectional. According to Surowiecki (2004), “ a
market, in other words, turns into a mob”. When the market is driven by mob
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psychology, there may be complete disregard for information. As highlighted
by Fisher (1930), four factors may justify a rise in the price level of stocks: (a)
earnings are continuously ploughed back into business instead of being
declared as dividends, resulting in an accumulation for future growth, (b)
expected earnings increase on account of technical progress, (c) earnings are
viewed to be less risky than what was perceived earlier, and (d) change in the
rate of discount (i.e. interest rate/cost of capital to the firm) used for
discounting future earnings into the present. During a bubble, expectations
about future earnings may be revised upwards or the earnings may be viewed
as less risky in relation to the past. But beyond a point, it is pure mob
psychology which takes over. As pointed out by Ashley (2003), “it is not just
our own judgments that finally decide whether we make an investment
decision; we need to cluster around others’ opinions for confirmation. In fact
we are very much influenced by those around us. It is easier to join the crowd
than fight it.”
Despite the practical significance of Keynesian mob psychology in relation to
fundamental value analysis, Keynes has often been viewed, as noted by
Raines and Leathers (2000) as a “bubble theorist who saw all stock markets as
simply gambling casinos”. In modern day capitalism, stock markets are rather
seen as the key vehicle for mobilization and allocation of resources.
Enhancing the efficiency of the markets, thus, continues to dominate the
policy thinking all over the world.
Since generation and processing of
information could be costly, prices need not necessarily always reflect all
available information, because that would leave little incentive to invest
resources on acquisition of information and their analyses. Informed market
players, who compete to acquire and analyze new information, hold the key to
develop an efficient market because despite the presence of profit
opportunities arising from mob behavior, it is only these players in the market
who tend to correctly process and price information. Investors relying on such
analyses, however, must recognize the distinction between “knowledge
power” and an impressive “power point” presentation. This is because
identifying the intrinsic value of a stock, and hence the undervaluation or
overvaluation of a stock, is an extremely difficult task. There may be either
too much or too little information, but more than that, there may be too little
knowledge to use the available information appropriately. As per the efficient
market hypothesis (EMH), however, the current price of a stock itself is the
fair valuation of the stock.
Hence, the old Wall Street adage suggests that the value of any stock is only
what someone is willing to pay for it (i.e. its current price). The bigger-fool
concept also reckons that as long as a stock can be sold at a higher price to
another, that would represent the intrinsic value of the stock at that point of
time, and no high price could be seen as an overvaluation. In practice, in every
market, one also comes across assessments of overheating and corrections,
with reference to perceptions about fair value. In the search for correct
valuation, one often comes across the debate between fundamental value
analysis and technical analysis, both of which aim at identifying stocks that
may be overvalued or undervalued. Under technical analysis, there is no
search for any elusive intrinsic value of the stock. The search is only for
trends/patterns in evolution of stock prices, which could be picked from past
price behaviour, and which could be expected to recur in future. Investors who
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are active in trading and frequently change positions over short time horizons,
picking of trends through charting may help. At times, even when the trends
may not recur, and accordingly predictions may go wrong, with cut-loss
strategy such investors can exit their positions. Even though in an efficient
market trend analysis through charting should not leave any scope for excess
returns, use of technical analysis is quite common in markets, which suggests
that imperfections identified by chartists may be helping in enhancing the
efficiency of the market. In that sense, the fair value of a stock is rediscovered
again and again, with corrections taking place to the valuation at every stage.
Unlike technical analysis, fundamental analysis aims at identifying the
intrinsic value of a stock so as to be able to pick stocks on the basis of
overvaluation or undervaluation in relation to the intrinsic value. As per this
analysis, a company is worth the sum of all its future cash flows discounted to
the present. If the present value exceeds prevailing market capitalization of
the company, then the stock could be a good buy. In such analyses, “expected
future earnings/cash flows” and the “discount rates” could change from time
to time, causing the intrinsic value of stocks to also change. Investors
interested in value stocks, growth stocks, or income stocks (depending on
individual risk appetite and investment horizon) could also supplement the
value analysis with assessment of indicators such as price to earnings ratio,
price to book ratio, dividend payout ratio, dividend yield, projected earnings
growth, etc. As per the top-down approach, the fundamental analysis often
may start with the performance and prospects of the economy, followed by the
industry group, and finally the firm within the group. Such three level analyses
necessary to assess the prospects of any single stock could be resource and
time intensive, and the return on such investments on information gathering
and analyses should be positive, even in an efficient market. There is no
apparent contradiction here, since one may not benefit from any new public
information as per the efficient market hypothesis, but money spent on
acquisition and analysis of information must be recovered in the form of
higher return. Thus, those who try to remain informed and in that process
spend resources must be adequately compensated in the form of higher return
than those who do not spend on information and tend to free ride. A market in
fact can become increasingly efficient only because of the costs incurred on
acquisition and analysis of information. This signifies the importance of equity
research in enhancing the efficiency of a market. In a competitive information
collection system no excess returns could be earned from new information per
se, but higher information gathering and processing costs must be exactly
compensated by higher return. In competitive equilibrium, thus, the marginal
return from additional information should equate marginal cost of information
acquisition. If the information collection and analysis system in a country is
not competitive, free riders can benefit at the expense of those who invest on
information acquisition and analysis. In such systems there may be little
incentive to invest on market research, and as a result, speculation and mob
psychology could dominate the markets.
Supporters of efficient market hypothesis may recognize the importance of
market research for enhancing efficiency of the markets, but superior analysis
and research need not be a source for yielding consistently higher returns. As
per this view, those reaping higher returns through superior processing of all
available past information may actually be exposing them to higher risk and,
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as a result, the higher return must be a compensation for the extra risk they
bear unknowingly. The risk-return tradeoff is a fundamental factor in an
efficient market. The required rate of return (RRR) on equity is much higher
than other financial instruments because of the higher risks associated with
equities. Thus, higher return on equity could be viewed as compensation to the
investors for assuming higher risk. But the key question here is by how much
the required rate of return on a particular stock should exceed the return on
risk free instruments like Government Bonds and Treasury Bills?
As per the Capital Asset Pricing Model (CAPM) framework, total risk of any
project could be decomposed into systematic and unsystematic risks, so that
[total risk = unsystematic risk (or idiosyncratic or diversifiable or firmspecific risk) +
systematic risk (or non-diversifiable or market risk)].
Unsystematic risks can virtually be eliminated through diversification, and
investors who do not hold a diversified portfolio of stocks must not expect to
be compensated in the form of higher return on equity for assuming nonsystematic risk of a firm. As per the portfolio selection models of Markowitz,
Sharpe and Lintner, diversification can compress the risk levels of portfolios
(measured as variance-covariance of returns) for specific return levels. In the
CAPM framework, investors care only about mean return and the variance of
the return. Firm specific unsystematic risk could be contained through
diversification, and for given degree of risk aversion, efficient portfolios
could be constructed using the portfolio selection models, so that risk is
minimized for given levels of return, or returns are maximized for given levels
of risk. Investors, however, must have to be compensated for assuming
systematic risks when they invest in stocks. An appropriate risk premium,
representing additional return over the risk free rate, must be offered to induce
risk averse investors to take equity stakes in riskier projects. CAPM beta helps
in offering an appropriate estimate of risk premium in relation to a project's
exposure to systematic risk. The tradeoff between systematic risk (β) and
expected return is generally captured through the upward sloping security
market line (SML). Any stock with a higher beta must fetch higher return than
the return on the broad market portfolio. The beta (β) of a firm could be
estimated through linear regressions (i.e. regression of individual equity
returns over the returns on overall market index, both adjusted for risk free
rates). According to CAPM, the only relevant measure of systematic risk of a
project/asset class is (β). In efficient markets, thus, higher returns could be
possible only because of exposure to higher risks.
Thus, an extremely rigid interpretation of market efficiency would suggest that
return to investment on equity research could be zero, since in such markets
there is no scope for value addition by portfolio managers and investment
analysts/strategists. A more practical interpretation, however, would suggest
that market efficiency is achieved and continuously enhanced only through
investment by investors on information collection and their analyses. Only
such informed investors contribute to market efficiency who recognize
potential undervaluation and overvaluation of stocks, reap excess returns till
others also recognize it, and keep investing till the inefficiency in valuation
disappears. One could infer, therefore, that return to equity research is positive
till the market remains inefficient, and at every level of efficiency of the
market, equity research further enhances efficiency. Market efficiency, thus, is
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an evolutionary process, where every incremental progress is made possible
through better collection and analysis of information.
Section-II: The Past Performance of the MSM
The performance of a stock market from the stand point of a lay man’s
perspective often relates only to the return it can generate on investments. A
friendly chat with most investors in the MSM would reveal their excessive
emphasis on return, and clear neglect of many other important aspects about
the stocks they hold in their investment portfolios. The years in which returns
are good, the market is viewed as performing well, and the moment returns
turn negative or remain below high levels of expectations, the market is seen
as a source of misery. This single dimensional focus on return clearly
overlooks the long-term performance and prospects of the firm, the industry
group and the overall economy. Such short-term earnings centric market
perception is fraught with the risk of corporates also targeting primarily
“quarterly earnings” figures, which could be achieved at times by resorting to
creative accounting. Even in advanced markets this tendency has triggered
greater attention of regulators, including Acts such as the Sarbanes-Oxley in
the US.
The investors need to recognize that the value of a firm may change from
time to time due to several firm specific, industry specific or economy specific
developments, and at times there could be transmission of shocks from
regional and global stock markets. The performance of a stock market at the
macro level, thus, could be appropriately assessed in a multidimensional
framework, focusing on market size, degree of market concentration (in
stocks), liquidity, volatility, transaction costs, level of integration with world
markets, etc.. These performance indicators must also be seen in the context of
market driving factors like the increases in real income, domestic saving,
capital inflows, domestic liquidity positions, market deregulation and
supervision, etc. At the micro level, firm specific indicators like net present
value (NPV) of the firm, price to earnings (P/E) ratio, earnings per share
(EPS), price-to-book value of the share, dividend yield and dividend payout
ratios, etc. are also often seen for identifying undervaluation and overvaluation
of stocks. Certain empirical analyses suggest that small company stocks can
earn higher return than large company stocks, and value stocks with low
market-to-book and low P/E ratios can outperform growth stocks with high
market-to-book and high P/E ratios. Advocates of efficient market hypothesis,
however, would argue that those who pick stocks on the basis of such firm
specific factors actually expose themselves to higher risks, and the higher
returns that they may reap could in fact be a compensation for the extra risk
they bear.
In Oman, the Muscat Stock Market (MSM) has a short history of less than two
decades, and during this short history also there was one major confidence
shattering fall in the market in 1998, which continues to reverberate in the
market memory even today, not dissuading the investors though from joining
the strong rally in the market that was witnessed till the mid of 2005. The
strong rally in the market received the push from the overall brighter
macroeconomic conditions made possible by surge in oil prices and the
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associated easy liquidity conditions, better performance of the non-oil sectors,
further progress on diversification and privatization, improved profitability of
corporates and banks, as well as self-fulfilling investor expectations of even
better return prospects in future on account of every likelihood of the
economic boom being sustained in the future. The initial enthusiasm, which
may be driven by fundamental factors, often ends up in exuberance, and as a
result, as noted by Shiller, investors do not just turn irrational, but turn
irrational in predictable ways, overreacting to any positive information by
buying in herds. The bubbles, thus, though start with a rally driven by
fundamental factors, soon get taken over by mob psychology and herd
behaviour of investors, and the more the bubble grows in size, the extent of
market correction that follows may also become equally sharp. This market
driven process of overheating and subsequent correction ensures eventual
alignment of market value of stocks with their respective fair values.
In Oman, the macroeconomic conditions continued to remain robust in the
second half of 2005 as well as the first half of 2006, as was the case during
2003-05 when the MSM witnessed strong rally. The fall in the index since
mid-2005, despite strong macro fundamentals, could be viewed as a correction
for the overshooting that had occurred during the rally period. As could be
noted from Table-1, the annual growth in the MSM index exceeded the
nominal GDP growth by a wide margin during the 2002-2005 period. The
growth in the index even exceeded the rate of increase in prices of Omani
crude during this period. Such a high rate of return (capital appreciation plus
annual dividend yield) clearly reflected the growing influence of irrational
exuberance on the market up to mid 2005. Any rational assessment of
expected return on stocks would suggest that given a risk free return of less
than 5 percent in the system (say a long-term deposit or investment in
Government bonds), even if one assumes a risk premium of 15 percent, any
annual return in excess of 20 percent on stocks on a sustained basis must be
looked with suspicion by rational investors. How can potentially a firm
generate such high returns on any type of business activity, unless it is
exposed to high risk. In terms of CAPM beta, a single firm with high risk
(beta) in relation to the market may yield higher return, but the market as a
whole (as represented by the MSM index) cannot be expected to yield high
returns (capital appreciation plus dividend yield) when the overall economic
performance, despite being strong, cannot justify that. This begs the question
as to whether informational inefficiency (i.e. market not reflecting the
available information about fundamentals correctly) is a major reason for such
large swings in market prices in the face of a stable behaviour of both the
economy and the firms whose shares are listed on the market. Most advanced
stock markets in the world have witnessed phases of strong boom-bust cycles
in the past, and most recently the entire GCC region witnessed a phase of
strong rally followed by sharp corrections. The empirical assessment of
informational inefficiency of a market, thus, is a very daunting challenge,
since for every staunch supporter of market efficiency, every prevailing price
is a fair price. One has to see, therefore, first whether a market meets the
requirements of a competitive market place, and second, whether a market can
mature to that stage only over time.
For efficient market conditions to prevail, several preconditions may have to
be fulfilled, such as: (a) large number of rational, profit maximizing investors
9
CBO Occasional Paper No. 2006-2
who actively participate in the markets based on informed analysis and
valuation, (b) flow of information is symmetric and random and unrelated over
time, and (c) market agents react quickly and accurately to any new
information, causing the prices to instantly reflect any new information.
Whether MSM fulfills these requirements is again difficult to assess. What is
learnt from experience of other advanced stock markets, however, is that
markets mature over time and preconditions to efficiency are attained only
gradually, and possibly never attained fully, leaving scope for detection of
market anomalies as a source of excess returns in every market.
Since it first started its operations on May 20, 1989, the MSM has come a long
way, with notable growth in market turnover, market capitalization, number of
market players, and number of issues (Table-1)†. In the context of an
assessment of the informational efficiency of the market, each specific aspect
of the progress achieved in the MSM could count. Market liquidity (which is
different from monetary liquidity conditions managed by the CBO) has been
one such important aspect. A stock can be termed as illiquid, if it is difficult to
sell it at unchanged price, or if it can be sold only at a lower price. Illiquidity
of a stock market depends on: (a) width of the market, (b) depth of the market,
and (c) resilience of the market. Width implies the extent to which prices may
change in response to any purchase/sale of stocks (i.e. higher the change in
price for any given buy/sell order, the more illiquid is the market). Depth of
the market implies trading volumes that can settle without altering the price
(i.e. if large volumes of the same stock can be sold at unchanged price, then
the stock can be termed as liquid). Resilience refers to the speed at which price
volatility resulting from trading activities settles down (i.e. in more liquid
markets large volumes of trade may affect prices only very temporarily). In
general, thus, a stock market can be termed as liquid if stocks can be
bought/sold in any quantity without little impact on market prices. In that
sense, can the MSM be viewed as illiquid (despite easy monetary liquidity
conditions maintained by the CBO)?
The answer could be in the affirmative, since the MSM lacks depth, width, as
well as resilience. The low depth of the MSM is evidenced from the sharp
decline in the turnover for MSM-30 since August 2005 (as against the
turnover of RO 170 million in August and a little more than that in July, the
turnover in Sept and Oct. were much lower at RO 103 million and RO 99
million respectively). Moreover, the average daily turnover is yet to reach the
peak attained way back in 1997 (Table-1). The low width of the market is
evidenced by the fact that the decline in turnover since August 2005 has
clearly pulled the MSM index down substantially, from a peak of 5699 on
June 20, 2005 driven by Omantel frenzy, to below 4800 in December 2005.
(Despite subsequent recovery to above 5500 in early 2006, the market
generally remained subdued and fell below 4700 in July 2006. Since then the
market has picked up, and gone above 5500 again in October 2006). The
evidence of decline in volume affecting the index, thus, is clearly visible (even
though falling index itself may also cause the turnover to decline). The MSM
also lacks resilience because the fall in the MSM index resulting from the drop
†
Various publications of MSM/CMA document the historical evolution of the market with
relevant facts and figures, including new initiatives launched by both CMA and MSM every
year during this evolutionary process. To avoid repetition, and to retain focus on the subject of
market efficiency, this paper does not reproduce those aspects of the market here.
10
CBO Occasional Paper No. 2006-2
in turnover does not seem to be temporary. This illiquidity problem of the
MSM could be a structural problem of the stock market itself. To deal with
the structural illiquidity problem of the MSM, what may be required is the
presence of large number of institutional market makers and hedge funds.
Unlike brokers (who only deal on behalf of customers by charging
commissions), market makers trade on their own books with large buy/sell
orders offering frequent quotes in the market. Absence of institutional market
makers in the face of a generally bearish market sentiment can only further
aggravate the problem of illiquidity in the MSM. On a comparative basis also,
the MSM market capitalization remains the lowest among the markets of six
GCC countries, with a share of just about 1 percent in total GCC market
capitalization of USD 1.1 trillion in 2005. Strong cumulative rally during
2003-05 was a major economic event in all the six GCC countries, as was the
case with subsequent market corrections during 2005-06 (Table-2). Excluding
only the pattern of movements in stock prices, there have been wide
differences in the depth and width of markets across GCC countries. The
depth, width and resilience of the MSM, however, need to improve
considerably, which as mentioned earlier, could happen only over time.
The existing market structure of the market reveals that there are large
differences in the performance of individual firms listed on the MSM. Based
on the available information on about 130 such firms for 2005, the distribution
patterns of price to earnings (P/E) ratios, earnings per share (EPS), price-tobook ratios, annual dividend yield and extent of appreciation in stock prices
during 2005 are presented in Chart-1 to Chart-5. Stock evaluation for many
investors often revolves around the company’s earnings. Earnings represent
the company’s profit, i.e. how much money it makes in any given period.
Current earnings may contain leading information about how much the
company can pay as dividend in the near term, and how much scope could be
there for capital appreciation in the form of higher stock prices. The more
useful indicator, however, is “earnings per share” or EPS (i.e. total earnings
divided by the number of outstanding shares). A company may have large
absolute earnings but at the same time the number of shares could also be
large, as a result of which the EPS may not by high, whereas another company
with lower absolute earnings may have higher EPS because of lower number
of shares. Price-to-Earnings (P/E) Ratio is another useful indicator for stock
picking as it shows the relationship between the stock price and the company’s
earnings (P/E = Stock Price / EPS). For example, a company with a share price
of RO 4 and an EPS of 0.400 (or 400 baisa), the P/E would be 10 (i.e. 4 /
0.400 = 10). Even though there is no thumb rule, a high P/E may mean that the
stock is overpriced, while a low P/E may mean that the stock is under priced.
This type of stratification of stocks is too simplistic, since a high P/E may also
reflect the market perception of strong future earnings growth (and hence
could be a good buy), and similarly, a low P/E may mean weak earnings
prospects for which the stock is generally not viewed positively in the market
(as opposed to being viewed as under priced). The “right” P/E, thus, could be
person specific, based on his analysis of earnings prospects, and may depend
on his willingness to pay for earnings. The more you are willing to pay for the
stock, it implies that you believe the company has good long term prospects.
Some other investors, however, may not see the same value in the stock and
may consider the same P/E level as high enough and thereby avoid a buy
recommendation. In the case of use of indicators like EPS and P/E, the other
11
CBO Occasional Paper No. 2006-2
Chart-1: Price to Earnings (P/E) Ratios (2005)
60
40
20
0
1
9
17 25 33 41 49 57 65 73 81 89 97 105 113 121
-20
Firms Listed on MSM
Chart-2: Earnings Per Share (EPS) in 2005
2
1
0
1
9
17
25 33
41 49 57
65 73 81
89 97 105 113 121
-1
Firms Listed on MSM
Chart-3: Price to Book Ratios 2005
5
4
3
2
1
0
1
9
17
25 33
41 49
57
65 73
81
Firms Listed on MSM
12
89 97 105 113 121
CBO Occasional Paper No. 2006-2
Chart-4: Dividend Yield (2005)
(Dividend paid as % of Market Price of the Stock)
15.00
10.00
5.00
0.00
1
9
17 25 33 41 49 57 65 73 81 89 97 105 113 121
Firms Listed on MSM
Chart-5: Capital Appreciation
(% Increase in Market Price of Stocks during 2005)
100.00
75.00
50.00
25.00
0.00
-25.00 1
9
17 25 33 41 49 57 65 73 81 89 97 105 113 121
-50.00
Firms Listed on MSM
Chart-6: Dividend Payout Ratios for 2005
100.00
80.00
60.00
40.00
20.00
0.00
1
9
17 25 33 41 49 57 65 73 81 89 97 105 113 121
Firms Listed on MSM
13
Table-1: Performance Indicators of the MSM over the Past Years
1997
Amount Mobilsed through the capital 373
market*( RO million)
Market Capitalization (RO million)
3339
Ratio of market capitalization to
0.55
GDP (%)
Average Daily Turnover (RO
6.6
million)
The turnover ratio (i.e. turnover as % 0.48
of market capitalization)
MSM 30 Index**
4805.8
Annual growth in index
141.0***
Nominal GDP growth in Oman
3.7
Average price of Omani Crude($/bbl) 18.62
1998
440
1999
189
2000
77
2001
155
2002
211
2003
385
2004
340
2005
678
2266
0.42
2262
0.37
1948
0.26
1722
0.22
1984
0.25
2790
0.33
3587.5
0.38
5878.5
0.50
3.7
1.0
0.9
0.7
1.3
2.4
3.1
5.5
0.40
0.11
0.11
0.10
0.17
0.21
0.21
0.24
2248.7
-53.2
-11.1
11.92
2502.6
11.3
11.5
17.35
2012.0
19.6
26.5
26.71
1520.8
-24.4
0.4
23.00
1918.6
26.2
1.9
24.29
2726.7
42.1
7.2
27.84
3375.1
23.8
13.7
34.42
4875.1
44.4
24.0
50.26
* Include mobilization through IPOs/bonds, new listings, rights issues, private placement, bonus issues, as well as GDRs.
** The MSM Indices are presented in 1000 points scale with effect from June 01, 2004 as against the earlier 100 points scale. The past indices have been adjusted for
the scale effect to maintain consistent comparability in the time series data for stock prices.
***This high rate of increase was over and above the 26 percent growth seen in 1996. The Index peaked at 5028.7 (502.87 in old scale) in January 1998 (on daily
basis the peak was at 5098.4 on February 03, 1998), and fell to as low as 2091.6 (209.16 in old scale) by March 1999, representing a fall by as high as 58.4 percent
over little more than one year period. But for some recovery up to 2922.7 by July 1999, the bearish market sentiments generally persisted, leading to further steady
decline in the index up to 1520.8 in December 2001. Since then, however, there has been a strong recovery, with annual appreciation in the index exceeding the
nominal GDP growth in each year. Driven by the Omantel optimism, the index peaked again at 5699.3 on June 20, 2005, to be followed by notable correction
dragging the index to about 4741 by mid-December 2005. The index staged a sharp recovery to above 5500 in January 2006, but generally remained subdued
thereafter and fell below 4700 by July 2006. Since then the index has again witnessed a major recovery, crossing 5500 mark by mid of October 2006.
14
Table-2: Comparative Performance of the GCC Stock Markets
Percentage gain/loss in the market index
High/Low of the Index
during the last one Year*
2004
2005
2006*
High
Low
Oman
23.8%
44.4%
14.1%
5,563.85
Muscat Securities Market (MSM-30)
(09/10/06)
Bahrain
32.8%
23.8%
1.6%
2,401.66
Bahrain Stock Exchange (BSE)
(17/11/05)
Kuwait
33.6%
78.6%
-9.6%
12,106.20
Kuwait Stock Exchange (KSE)
(06/02/06)
Qatar
64.5%
70.2%
-32.2%
12,673.10
Doha Securities Market (DSM)
(12/10/05)
U.A.E.
74.8%
69.4%
-33.0%
5,797.07
Abu Dhabi Securities Market (ADSM)
(12/11/05)
Saudi Arabia
84.9%
103.7%
-34.1%
20,966.58
Tadawul All Shares Index (TASI)
(25/02/06)
U.A.E.
186.4%
119.9%
-57.3%
1,267.32
Dubai Financial Market (DFM)
(9/11/05)
*: Up to mid October 2006.
Figures in the parentheses/brackets are the respective dates on which indices reached yearly high and low.
Sources: GulfBase and MEBC.
15
4,643.41
(25/07/06)
1,966.68
(27/06/06)
9,227.80
(02/08/06)
7,110.11
(24/05/06)
3,277.61
(11/05/06)
9,741.43
(11/05/06)
391.54
(30/07/06)
% fall in
Yearly Low
in relation to
High
-16.5%
-18.1%
-23.8%
-43.9%
-43.5%
-53.5%
-69.1%
CBO Occasional Paper No. 2006-2
important information in stock analyses is Projected Earnings Growth (PEG),
since stratification of stocks into undervalued and overvalued could be based
on ex-ante PEG, for given ex-post EPS and P/E. In respect of firms listed in
the MSM, as could be seen form Chart-1 and Chart-2, most of the P/E ratios
are within 20 (excluding stocks of exceptionally high P/E ratios, and also
those with negative earnings) and the EPS for most stocks are less than 0.5
(excluding few stocks with exceptionally high EPS, and also those with
negative earnings). The extent of variation across firms also suggests that for
any given projected PEG by any analyst, the stocks can be stratified into
undervalued and overvalued categories.
It may be noted that in the case of young start-up companies, there may not be
any earnings history, even though their future growth prospects could be high
(as was the case during the early phase of the IT boom of the 1990s for IT
stocks). Price to Sales (P/S) ratio could be more appropriate in such cases, as a
low P/S may indicate good value for a new company (i.e. current high sales
volume may suggest the prospects for market price of the stock to increase in
future). Price-to-Book ratio is another useful indicator which suggests the
value that the market places on the book value of a company (calculated by
dividing the current price per share by the book value per share). Like the
P/E, a low P/B may mean a preferred buy option. As could be seen from
Chart-3, for most of the firms listed on the MSM the Price-to-Book ratios
hover around or are less than 2, and in rare exceptional cases only P/B ratios
of more than 4 could be observed. The macro and micro level information
could complicate further the assessment of the performance of the MSM,
because based on the strong rally in MSM index in general during 2003-2005,
at the macro level the inferences could suggest overheating, whereas based on
firm specific low values of P/E and P/B, it may appear that most stocks may
still have scope for further growth. This again underscores the importance of
greater focus on equity research, so that the investment decisions could be
based on analyses of developments in the economy, industry group, as well as
the individual firm, and such informed investment decisions can add to the
efficiency of the market.
Most stock prices respond significantly to announcement of dividends. Hence,
Dividend Payout Ratio (DPR) and Dividend Yield represent two other
performance indicators which are often monitored by the stock investors. The
DPR could be calculated by dividing the annual dividends per share by the
Earnings Per Share (or simply, total dividends paid by a firm divided by its
total profits). For firms with good growth prospects, they may retain a larger
part of total earnings (or profits) for reinvestment, and hence DPR may be
low. In turn, for matured companies with not much growth prospects, a higher
part of the earnings may be paid out as dividends, yielding a high DPR. Even
though according to Modigliani-Miller (MM) proposition-2 “dividend policy
does not matter for value of a firm”, in practice declaration of dividend
significantly influences the price of stocks, creating competitive pressure on
all companies to announce high dividend, despite their varied future growth
prospects and the associated varied needs for retaining parts of current profits
for reinvestment. Dividend yield could be calculated by dividing the “annual
dividend per share” with the “current stock price” (depending on the price at
which a stock is bought, dividend yield could vary from person to person, but
for analytical comparison purpose prevailing market price could be used to
16
CBO Occasional Paper No. 2006-2
derive the respective dividend yield rates). A low current dividend yield has
to be seen in the context of future growth prospects; if a major part of profit is
retained by the company for reinvestment so as to be able to fully exploit the
future growth opportunities, its stock could still be considered as a good buy
despite low current dividend yield. Under a competitive dividend payout
policy of firms in a market, however, low current dividend yield has to be
assessed more carefully. As could be seen from Chart-4 and Chart-5, the
dividend yields of firms listed on MSM have mostly been around 5 percent or
less in majority of the cases, barring few exceptions with higher dividend
yields, but price appreciation fetched much better return to the investors in
2005, exceeding even 50 percent for several firms. The dividend payout ratios
varied widely (Chart-6), ranging from very low to very high, but the
combined return in terms of both dividend yield and price appreciation of the
stocks generally turned out to be quite high in 2005. In respect of each and
every firm specific indicator, the investors need to keep one major caveat in
perspective is that there is no thumb rule or benchmark against which stocks
can be assessed as undervalued or overvalued.
Section-III: Empirical Assessment of the Market Efficiency Hypothesis
for the MSM
The most common test of weak form of market efficiency is the random walk
hypothesis, which states that successive price or return changes are
independent over time, and that the actual price hovers around a fundamental
value. In a random walk framework, any market price pt = pt-1 + εt , so that
∆pt = εt is an independent and identically distributed sequence. In other
words, if prices fluctuate randomly, then they are not predictable. Lack of
predictability as a test of weak form efficiency has generally spawned a
number of empirical literature based on tests of random walk properties of the
stock prices. The efficient market hypothesis does not require the market
price of a stock to equal the true value of the stock, but the errors must be
unbiased so that deviations in market prices from the true value are random
and unpredictable. Market price, thus, is an unbiased estimate of the true value
of the stock. Since it would be difficult to say at any point of time whether a
stock is overvalued or undervalued, no profitable investment strategy can be
formulated based on analysis of past historical data.
It is important to recognize the very important differences between
“martingale”, “random walk”, and “efficient market hypothesis”.
In the case of a martingale, pt = pt-1 + εt, so that
rt = (pt - pt-1) = εt ………………………….(a)
As per a martingale process, return (rt ) varies around zero, with εt having
zero mean.
In the case of a random walk with drift, pt = µ + pt-1 + εt, so that
rt = (pt - pt-1) = µ + εt
………………….(b)
17
CBO Occasional Paper No. 2006-2
As per this random walk process, thus, returns (rt) vary around an equilibrium
return (µ), and the equilibrium return may be decided by standard asset
valuation theories like the CAPM (Capital Asset Pricing Model) or the APT
(Arbitrage Pricing Theory). Instead of return (rt), if risk-adjusted returns are
used (i.e. rt –µ), then the random walk process also represents a martingale. In
other words, if µ = 0, then the random walk process is the same as a
martingale. (Thus, every random walk process is not a martingale, and
similarly, every martingale process is not a random walk.)
The efficient market hypothesis, in turn, can be presented as:
rt = (pt - pt-1) = Et-1 (rt )+ εt …………………….(c)
This suggests that the true returns vary around the expected return Et-1 (rt)
(as against around εt in case of a martingale process, and around µ in a
random walk process). In most empirical tests of efficient market hypothesis,
it is assumed that Et-1 (rt ) = µ (implying estimation of a random walk
process). Since µ is derived through some asset pricing model (say like CAPM
or APT), empirical test of EMH is always a joint test; first, the efficiency of
the market, and second, appropriateness of the models in generating
equilibrium (or fair level of) returns represented by µ. A rejection of EMH
alone, therefore, may not indicate inefficiency, because it is possible that the
markets may be efficient but the models used for generating the equilibrium
returns may be wrong.
Often, the EMH is difficult to study empirically because of the “equilibrium
rate of return” concept around which the return in any single year is expected
to hover around, and the scope for mis-measurement of the equilibrium return
through a model (be it CAPM or APT). A more convenient, though still
meaningful, option to empirically assess the EMH is through a random walk
of the form
k
rt = β0 + Σ (βi) rt-i + εt …………………….(d)
i=1
where βi = 0, for i =1….k, which suggests that today’s expected returns are not
determined by past returns (i.e. information on past returns are not relevant for
arriving at future expected returns). The EMH also assumes homoscedasticity
(i.e. time invariant variance of the error term), which may not often hold due
to the generally observed presence of heteroscedasticity (or time variant
variance) in financial market data. A rejection of EMH as specified in
equation (d), therefore, is not a rejection of weak form efficient market
conditions, particularly in the presence of heteroscedasticity. High frequency
market data (like stock prices and stock returns) often exhibit time dependent
conditional variance, which can be studied through Autoregressive
Conditional Heteroscedasiticy (ARCH) of Engle (1982) and Generalized
Autoregressive Conditional Heteroscedasiticy (GARCH) of Bollerslev (1986).
In the presence of time dependent conditional variance, correct specification
of the conditional mean and conditional variance equations become crucial.
The mean equation could generally look like:
18
CBO Occasional Paper No. 2006-2
rt = β0 + Σ (βi) rt-i + φht + εt …………………….(e)
where (ht) is the conditional variance in the mean return equation, and the
variance equation may look like:
ht = α0 + α1 (εt-12 ) …. αq (εt-q2 ) + δ1(ht-1 ) …..δp(ht-p) ……………..(f)
Appropriate specification of the conditional variance equation depends on
proper choice of p and q (i.e. lags in the conditional variance equation) of the
underlying GARCH (p,q) process. In equation (f), α0>0, αi >= 0 and δj >= 0
represent sufficient condition for ht to be positive in the mean return equation
(e). It is necessary, however, that the specification of the conditional mean
equation is appropriate. Misspecification in the linear mean equation could
arise from omitted shifts in trends, incorrect choice of lag lengths in the autoregression process, presence of parameter instability, residual autocorrelation,
as well as omitted variables from the mean equation. Incorrectly specified
conditional mean equations could give rise to incorrectly specified conditional
variance equation. In such cases, rejections of EMH may actually represent
errors in specification of the test rather than the efficient market condition
itself. The conditional mean equation (e) suggests that stock returns could
increase if conditional variance ht increases‡. If (ht) can be predicted from
historical data on stock returns, then that could tantamount to rejection of
EMH.
For the empirical assessment of the EMH in respect of MSM based on the
approach outlined above, data on daily MSM 30 index (scaled uniformly to
scale 1000) for the period February 1997 to July 2006 have been used (Chart 7). This period includes the phase of the market crash of 1998 as well as the
strong rally seen during 2005, and such wide swings are difficult to explain in
any empirical analyses in terms of pure fundamentals. The weak form of the
EMH only can indicate whether based on information embodied in the past
behaviour of the MSM data series, the behaviour of the series could have been
predicated to some extent for profitable use in any investment strategy. As
could be seen from Table-3, Augmented Dickey-Fuller (ADF) and PhilipsPerron (PP) tests of stationarity suggest that while (log) of the MSM price
series is I(1), the daily return series on MSM is I(0). As could be seen from
‡
As per standard empirical finance, higher return could be a compensation for bearing higher
risk, and hence, return data must exhibit increasing trend in relation to risk represented by
variance (irrespective of whether unconditional variance or conditional variance is used in the
analysis). As per French et al , however, empirically stock returns may fail to exhibit
statistically positive co-movement with unconditional variance, but returns generally tend to
increase in relation to conditional variance captured through ARCH and GARCH
specifications. Unlike Markowitz type analyses where risk of a portfolio is captured by
variance-covariance, as per CAPM the risk of a stock can be captured correctly only through
CAPM beta, even though multifactor models also can explain the return behaviour (and
predict return to some extent as well) on the basis of behaviour of factors such as P/E ratio,
market to book ratio, small firm versus large firm, etc. Other market anomalies like month of
the year, day of the month/week, etc. as well as event studies (to capture the price behaviour
before and after the announcement of any relevant information) and runs test (which is the
non-parametric version of the serial correlation test) have also been studied in empirical
finance to question the relevance of EMH.
19
CBO Occasional Paper No. 2006-2
Chart-8, the distribution of daily (annualised) returns§ on MSM (February
1997 to June 2006) is symmetric. But the Skewness, Kurtosis and Jarque-Bera
test statistics reject the null of normality, indicating the presence of fatter tails.
Chart-9 also shows the presence of volatility clustering. The distribution
characteristics of MSM stock returns are, therefore, typical of most emerging
market economies. The autocorrelation functions of the daily return series
presented in Chart-10 also suggest that the null hypothesis of noautocorrelation is rejected by the Ljung Box Q statistics for each of the 12 lags
(in a stationary return data series, presence of autocorrelations could be an
indication against EMH, but the extent of autocorrelation may not be enough
to emerge as a source of excess profits, particularly if the transaction costs are
high in a market. The autocorrelation coefficients have to be large enough to
be a source for generating excess returns.)
Table-3; Tests of Stationarity
Log (MSM)
Return (rt)
ADF
-0.550743
-10.95505
SIC lag-14
SIC-lag13
PP
-0.477474
-44.75293
Newey West
Newey West
bandwidth 20
bandwidth 18
Based on optimal lag/bandwidth, both ADF and PP test statistics suggest that
Return (rt) series is stationary.
Chart-7
6000
5000
4000
3000
2000
1000
Daily MSM General Index (Feb. 1997 to July 2006)
.
r
Daily return is calculated as (log Pt ) – (log P t-1 ). This is so because, Pt = P t-1 * e
r
In other words, Pt / P t-1 = e . Taking log on both sides, we get (log Pt ) – (log P t-1 ) = r.
§
20
CBO Occasional Paper No. 2006-2
Chart-8
1000
nr
ut
e
R
e
m
a
S
ht
i
W
s
y
a
D
f
o
r
e
b
m
u
N
Series: DAILY RETURN
Sample Feb.1997- July2006
Observations 2347
800
600
400
200
Mean
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
0.000328
0.152225
-0.128705
0.010466
0.863051
45.79506
Jarque-Bera
Probability
179388.7
0.000000
0
-0.10
-0.05
-0.00
0.05
0.10
0.15
Distribution of Daily Return on MSM General Index
Chart-9
.20
.15
.10
n
r
u
t
e
R
f
o
e
t
a
R
y
li
a
D
Daily Return Data Showing Volatility Clustering
.05
.00
-.05
-.10
-.15
February 1997 to July 2006
Chart-10
Autocorrelation Functions of Daily MSM Return Series
Autocorrelation
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Partial Correlation
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Lags
1
2
3
4
5
6
7
8
9
10
11
12
21
AC
0.117
0.058
0.058
0.071
0.017
0.019
0.036
0.032
0.038
0.025
0.048
0.095
PAC
Q-Stat
Prob
0.117
0.045
0.047
0.057
-0.002
0.009
0.027
0.020
0.029
0.012
0.036
0.080
32.295
40.324
48.193
59.934
60.642
61.509
64.575
66.945
70.434
71.899
77.249
98.540
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
CBO Occasional Paper No. 2006-2
Empirical estimation of equation (d) [ i.e. rt = β0 + Σ (βi) rt-i + εt ] for
testing the EMH suggests that there could be many specifications for MSM
return data as reported in Table-2 for which ( βi) are non-zero, and statistically
significant. The first two equations in Table-4 indicate that daily MSM return
series at time (t) exhibits statistically significant relationship with lagged
returns (for lags 1,2,3,4 12 and 13). Under conditions of EMH, the estimated
(βi) coefficients should have been either zero, or statistically insignificant.
Table-4 estimated serial correlation coefficients in return data is suggestive of
rejection of EMH. Since the drift parameter in the first two equations are
statistically insignificant (whereas as per equation-b type specifications the
drift parameter µ should be positive and significant, since our return data are
not adjusted for risk free rate of interest), in the last two equations in Table-4
the constant has been dropped and the equations have been re-estimated. The
estimated coefficients, however, continue to reject EMH. Such rejection could
be on account of incorrect specification of the mean equations, particularly in
the presence of time varying conditional variance of the error term. As per
ARCH-LM test of the errors of all specifications presented in Table-4, there is
clear evidence of heteroscedasticity in the return data, and hence, the return
equations have been estimated in ARCH and GARCH specifications (Table5).
Table-4: Linear Random Walk Equations of the MSM Return
rt = 0.0002 + 0.11( rt-1) + 0.04( rt-2) +0.04 ( rt-3) +0.06( rt-4)
(1.12)
(5.18)*
(1.81)*** (1.96)** (2.79)*
rt = 0.0002 + 0.11( rt-1) + 0.04( rt-2) +0.04 ( rt-3) +0.06( rt-4) +
(1.04)
(5.41)*
(1.94)*** (1.87)*** (2.90)*
+0.10( rt-12) - 0.13( rt-13)
(4.94)*
(-6.23)*
rt = 0.11( rt-1) + 0.04( rt-2) +0.04 ( rt-3) +0.06( rt-4)
(5.21)*
(1.84)*** (1.99)** (2.81)*
rt = 0.11( rt-1) + 0.04( rt-2) +0.04 ( rt-3) +0.06( rt-4) +
(5.44)*
(1.96)** (1.89)*** (2.92)*
+0.10( rt-12) - 0.13( rt-13)
(4.97)*
(-6.26)*
*, **, *** represent statistical significance at 1%, 5% and 10 % levels, respectively.
As we know, corrections for heteroscedastic errors could improve the
efficiency of the estimated parameters. When variance of the error term varies
directly with one or more independent variables in the regression equation, use
of weighted least squares technique could transform errors into a
homoscedastic process, and thereby OLS could still throw efficient parameter
estimates. One could also use White's correction for heteroscedasticity. In
turn, however, when the error term is not a function of one or more
independent variables in the regression equation, but instead varies over time
in a manner so that large errors are followed by large errors and small errors
22
CBO Occasional Paper No. 2006-2
are followed by small errors (i.e. current errors depend on how large or small
were the past errors), it becomes useful to apply ARCH and GARCH
techniques. As per the estimated equations presented in Table-5, the
coefficients of the ARCH and GARCH parameters in the mean equations as
well as all coefficients of the variance equations are statistically significant.
The sum of the ARCH and GARCH coefficients is not greater than 1,
signifying the volatility process to be stationary. Moreover, the sum of ARCH
and GARCH coefficients are almost equal to 1, indicating that volatility
shocks are quite persistent. The efficient market hypothesis, as we know,
assumes homoscedatstic errors in the random walk specifications of returns,
whereas errors, as we see in the case of MSM return data, could be
heteroscedastic, which in itself could be a factor contributing to the rejection
of EMH. In respect of MSM data, thus, the standard tests of EMH indicate
that not only MSM returns are highly correlated, but they also exhibit the
presence of conditional variance. There could, thus, be scope for use of serial
correlation coefficients and the predictable conditional variances for
generating excess returns, implying rejection of the weak form efficient
market hypothesis for the MSM.
Table-5: ARCH and GARCH Mean and Variance Equations
The GARCH in Mean Equation
rt = 0.07( rt-2) +0.07 ( rt-3) +0.04( rt-4)+ 4.85 (ht)
(3.20)*
(3.07)*
(1.86)*** (2.79)*
The GARCH(1,1) Conditional Variance Equation
ht = -0.0003 + 0.25(εt-12 ) + 0.75(ht-1 )
(14.41)* (18.51)* (83.9)*
The ARCH(M=3) Mean Equation
rt = -0.0009 + 0.39( rt-1)- 0.07( rt-2) +0.09 ( rt-3)
(-2.87)* (17.18)* (-3.86)* (4.15)*
+0.09( rt-4)+ 0.18 (ht)½
(6.55)*
(3.90)*
The ARCH (M=3) Conditional Variance Equation
ht = -0.0002 + 0.53(εt-12 ) + 0.35(εt-22 ) + 0.13(εt-32 )
(24.47)* (20.05)* (14.10)*
(5.85)*
*, **, *** represent statistical significance at 1%, 5% and 10 % levels, respectively.
As per the ARCH-LM test statistics, the errors in both mean equations turn out to be
homoscedastic (i.e. with no further time varying variance). While the first mean
equation has variance (ht), the second mean equation has standard deviation, i.e. (ht)½
.
Section-IV: Concluding Observations
Excess volatility in stock prices in relation to the volatility in the underlying
fundamentals has been a common feature of most of the stock markets, and the
search for fair value of a stock has almost always been illusory, leading to
sustained interest of the practitioners in the empirical debate on the efficiency
of the markets. Believers in the efficient market hypothesis may argue that
stock picking on the basis of identification of overvaluation or undervaluation
23
CBO Occasional Paper No. 2006-2
of a stock cannot fetch higher return on a consistent basis, unless such
strategies also mean corresponding higher exposure to risks. There have been
empirical evidences to suggest, however, that excess returns can be made
without exposure to higher risk, and such excess returns could accrue to both
uninformed investors as a matter of pure chance and to the informed investors
as a compensation for the cost they incur in acquiring and processing
information. As per the well known Grossman Stiglitz paradox, if all
information were reflected in market prices, then there wont be any incentive
for anybody to acquire and process information, and hence, the information
could never get reflected in the market prices. In this debate, the reality may
lie somewhere in between, so that stock price movements could be viewed to
have both a rational component as well as an irrational “fads and fashion”
component. While rational informed investors may trade (or even speculate)
on the basis of information, noise traders may trade and speculate on the basis
of incomplete or no information. It is the informed rational investors who add
efficiency to the market, though gradually, and during this process noise
traders may also help the market by adding depth and liquidity. Despite the
informed investment decisions of rational investors, and their growing
importance in a market, there will always be some anomalies in the market,
caused by the actions of noise traders and uninformed “fads and fashion”
driven speculation, which some investors can exploit to reap higher return.
Every time such anomalies are detected, however, due to competitive search
for excess returns, better information gets priced in the market. As rightly
noted by Campbell, Lo and MacKinlay (1997), “recent econometric advances
and empirical evidence seem to suggest that financial asset returns are
predictable to some degree. Thirty years ago this would have been tantamount
to an outright rejection of market efficiency. However, modern financial
economics teaches us that other, perfectly rational, factors may account for
such predictability.”
The empirical assessment of the MSM general index suggests that it has been
much more volatile in relation to the more stable underlying fundamentals,
and individual firm level performance in terms of price-to-earnings ratio,
dividend yield, price-to-book ratio, dividend payout ratio, etc. has been quite
divergent. Based on firm specific anomalies in relation to individual specific
perceptions about undervaluation or overvaluation, there could be potential
for excess return, even though it is difficult to establish as to whether such
potential for excess return results from associated exposure to higher risk.
When one looks at the recent strong rally in the MSM till mid- 2005 and the
subsequent correction and recovery, one could infer that higher return
stemming from the rally could be temporary and must be associated with
higher risk. Without any information on individual investor specific
performance, it is difficult to infer as to whether anyone could consistently
beat the market in both phases of strong rally and subsequent correction. Most
importantly, it is even more difficult to establish whether any investor could
predict both the rally and the subsequent correction, and as a result could make
excess returns during both phases of the market in relation to the average
expected market performance. Unlike micro level firm specific or investor
specific assessment, a broad assessment at the macro level based on the MSM
general index suggests that analysis of information contained in the past data
can make the return as well as volatility of return somewhat predictable. While
the random walk type tests suggest presence of correlation in returns, ARCH
24
CBO Occasional Paper No. 2006-2
and GRACH specifications of the testable equations indicate that the variance
of MSM returns are time variant, and conditional variance can be predicated
as well.
Even though tests based on random walk and ARCH/GARCH could suggest
rejection of the weak form efficient market hypothesis for the MSM, in view
of the age old challenge of correctly estimating the expected return, it is
extremely difficult to establish whether predictable information identified
from the past data can be used to generate excess returns in relation to
expected return in Oman. Expected returns based on both CAPM beta (i.e.
higher the risk explained by stock specific beta, higher must be the expected
return), and multifactor models (i.e. expected higher returns associated with
stocks having low P/E, low price-to-book value, and small size of a firm, etc.)
may be widely recognized by the investors in general in the market, leaving
little scope for any extra information that could be used by any investor to reap
additional return in excess of the expected return. In the absence of correct
estimation of expected returns in relation to risk, empirical assessment of
efficient market hypothesis can potentially yield erroneous conclusions. In
Oman, it may be necessary that investment decisions in the MSM are
increasingly made on the basis of quality equity research, so that investors
become aware beforehand about the higher risk associated with higher
expected returns from a stock, and the chance factor associated with any
excess return that may occasionally arise in relation to expected return.
Greater informational efficiency can bring greater clarity to the expected
empirical relationship between return and risk, and till greater informational
efficiency is attained, the return on equity research may consistently exceed
the normal risk-specific expected return of a stock. This is evident from the
return track record of certain investment firms/funds even in advanced and
more efficient markets.
In the absence of adequate equity research, pricing of stocks in the market may
continue to be dominated by investors’ search for quick and high returns, quite
unrelated to the underlying information and risk. In such a market, instead of
long-term investors, it is the investors with short investment horizon only will
dominate, who will buy a stock with the clear intention to sell sooner at a
higher price. Thus, there will be a continuous search for a bigger fool, and the
price formation process in the market would get continuously distorted –
devoid of any regard for underlying information or risk. Mis-pricing of stocks
would also entail the macroeconomic cost in terms of inadequate mobilization
of savings for long term investment as well as inefficient allocation of saving
among competing investment needs. It is important to note, however, is that
no single empirical paper like this one can yield any conclusive evidence on
the validity of the EMH for the MSM, even though more of similar research
undertaken by market participants to back their investment decisions can help
over time, not only in gradual empirical validation of the EMH but also in
enhancing the efficiency of the MSM through better pricing of information in
the market.
25
CBO Occasional Paper No. 2006-2
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