Testing weak-form efficiency of emerging economies: a critical review of literature/Kritine kylancios ekonomikos mazo rinkos efektyvumo literaturos apzvalga.
Nurunnabi, Mohammad
1. Introduction
The concept of EMH came from Fama (1970, 1991) based on the
argument of Samuelson (1965) who found that the anticipated price of an
asset fluctuate randomly. During the past decades, the efficient market
hypothesis (EMH) has been a debatable issue in empirical finance
literature because of its significance and implications. The study
consists four sections including the introduction. The next section
provides an overview of random walk model and its implication on
weak-form efficiency test. The section three contains the critical
review of literature on weak-form efficiency in developed countries,
emerging markets and South Asian perspective. The final section
summarizes the conclusions.
"The primary role of the capital market is allocation of
ownership of the economy's capital stock. In general terms, the
ideal is a market in which prices provide accurate signals for resource
allocation: that is, a market in which firms can make
production-investment decisions, and investors can choose among the
securities that represent ownership of firms' activities under the
assumption that security prices at any time "fully reflect"
all available information. A market in which prices always "fully
reflect" available information is called 'efficient'
(Fama 1970: 383)".
Fama (1970) suggested three applicable models of EMH including Fair
Game model, the Submartingale model, and the Random Walk model. The EMH
can be classified into three forms: weak-form, semi-strong form and
strong form (Roberts 1959). Weak-form of efficiency claims that the
current share prices reflect all the information that is contained in
the historical sequence of prices and technical analysis cannot be used
to predict and beat market; Semi Strong-form of efficiency implies that
current share prices not only reflect all information content of
historical prices but also reflect all the publicly available
information; Strong-form of efficiency states that current share prices
reflect all information whether it is publicly available or private
information (insiders information) (Fama 1970). Later, Malkiel (1992)
extended Fama's definition following the two arguments: the
security prices would be unaffected by revealing the information and it
is impossible to make profit based on the revealed information.
Therefore, EMH can be measured by the profits based on the information
(Jensen 1978; Campbell et al. 1997; Timmermann, Granger 2004). However,
their definitions were based on the information and transaction costs,
not involving joint hypothesis (Pesaran 2005).
Nowadays, the concept of EMH in emerging market is becoming more
important because of the globalization, free movement of investments
across national boundaries and the huge capital inflows from developed
economies. Traditionally, the markets of developed economies are more
efficient compare to emerging markets (Gupta 2006). The fundamental
reason is that the development of capital markets is lower which which
results in less regulations and control in the weak markets (Gupta
2006). Among the emerging countries in South Asia, the capital markets
of Bangladesh are enormously growing very vastly, however not like
India, but in an impressive way (See Table 1).
At this stage, it is useful to assess the level of efficiency in
Bangladeshi stock market. However, very few research focus on the
Bangladesh and they are dated and inconclusive. The empirical research
found that emerging markets are not efficient in semi-strong form or
strong form. So, it is justifiable to review the weak-form studies
rather than semi-strong form or strong form. Wong and Kwong (1984)
suggest that if the evidence fails to support weak-form efficiency, it
is unnecessary to test the semi-strong form or strong form efficiency at
the stricter levels. There are other reasons which might be affected to
test the semi-strong form or strong form efficiency in emerging
economies, including the unavailability of sufficient data, structural
profile, inadequate regulations, lack of supervision, companies'
information circulation before the officially availability of annual
reports, dramatic movement of the markets and the rumours of information
(Worthington, Higgs 2003).
2. Random walk model
Traditionally, the lower the market efficiency, the greater the
predictability of stock price changes. According to Fama (1970), the
efficient market exists if the share prices are reflected by all
available information. In other words, in an efficient market, price
changes must be a response only to new information. As the information
arrives randomly in market, the share prices fluctuate unpredictably. In
weak-form efficient, the price movements fluctuate and the changes of
price are independent. In that case, the investors cannot predict the
insights of the future prices based on the past information and cannot
earn abnormal returns.
The random walk idea of the asset price was introduced by Bachelier
in 1900 (Poshakwale 1996). The random walk model sates that the price
changes cannot be predicted from earlier changes, the successive price
changes of any stock are independent and the price changes occur without
any significant trends. The random walk will be consistent with equity
being appropriately priced at an equilibrium level, whereas the absence
of a random walk will follow the inappropriate of pricing of capital and
risk. This has important implications for the allocation of capital
development of overall economy. The random walk model can be stated as
follows:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (1)
where [P.sub.t+1] = Price of share at time t+1; n = Expected price
change; [P.sub.t] = Price of share at time t; [[epsilon].sub.t+1] =
Random error with zero mean and finite variance
Ko and Lee (1991) argued that "if the random walk hypothesis
holds, the weak-form of the efficient market hypothesis must hold, but
not vice versa. Thus, evidence supporting the random walk model is the
evidence of market efficiency. But violation of the random walk model
need not be evidence of market inefficiency in the weak-form". Fama
(1970) strongly support the random walk model in testing the efficiency
and pointed out that this model is more powerful than the fair game
model. However, Jensen (1978) found that anomalous price behaviour where
certain series appeared to follow predictable paths. In later study,
Fama (1998) suggests that new behavioural based theories are required
because of the apparent anomalies. The most of the previous empirical
literature has focused on the random model to test the weak-form
efficiency (Groenewold; Kang 1993; Huang 1995; Groenewold, Ariff 1998;
Lee et al. 2001; Smith, Ryoo 2002; Fama, French 1988; Osborne 1959;
Cootner 1962, 1964; Fama 1965; Fama, Blume 1966; Dimson, Mussavian 1998;
Cowles, Jones 1937; Poterba, Summers 1988; Fama et al. 1969, 1993; Fama
1995; Groenewold et al. 1993). Hence, the present study signifies the
prior literature on examining the random walk behaviour to test
weak-form efficiency in emerging stock market.
On the contrary, the economic theory suggests a number of sources
of nonlinearity in the financial data. One of the most frequently citied
reasons of nonlinear adjustment is presence of market frictions and
transaction costs. Existence of bid-ask spread, short selling and
borrowing constraint and other transaction costs render arbitrage
unprofitable for small deviations from the fundamental equilibrium.
Subsequent reversion to the equilibrium, therefore, takes place only
when the deviations from the equilibrium price are large, and thus
arbitrage activities are profitable (He, Modest 1995). Consequently, the
dynamic behaviour of returns will differ according to the size of the
deviation from equilibrium, irrespective of the sign of disequilibrium,
giving rise to asymmetric dynamics for returns of differing size (Dumas
1992, 1994; Kragler, Krugler 1993; Obstfeld, Taylor 1997; Shleifer 2000;
Coakley, Fuertes 2001; Taylor 2008). In addition to transaction costs
and market frictions, interaction of heterogeneous agents (Hong, Stein
1999; Shleifer 2000), diversity in agents' beliefs (Brock, LeBaron
1996; Brock, Hommes 1998) also may lead to persistent deviations from
the fundamental equilibrium. On the other hand, heterogeneity in
investors' objectives arising from varying investment horizons and
risk profiles (Peters 1994), herd behaviour or momentum trading (Lux
1995) may give rise to different dynamics according to the state of the
market, i.e., whether the market is rising or falling.
3. Critical review of literature
There are two schools of thoughts on the market efficiency. The
first one argues that the markets are efficient and the future returns
are unpredictable (Fama 1970). On the other hand, the second ones argue
that the EMH theory is contradictory because of the empirical evidence
of 'anomalies' (Summers 1986; Keim 1988; Fama, French 198; Lo,
MacKinlay 1988; Poterba, Summers 1988). The weak-form efficient market
hypothesis states that the current returns are considered to contain all
information that is incorporated in historic data and the future returns
cannot be forecasted from past returns data. Fama (1991) has extended
the predictability power of past returns including the seasonal in
returns and the predicting ability of variables (dividends, firm size
and interest rates). Following by Fama's theory, there were
enormous studies conducted on the weak-form test. The summary of
selected studies on developed markets, emerging markets and south Asian
markets are given in Table 2. The prior researches are discussed on the
arguments surrounding three categories to simplify the research
objectives:
3.1. Empirical evidence of developed markets
The earlier study on the weak-form efficiency mostly focused on the
developed markets (Working 1934; Kendall 1943, 1953; Cootner 1962;
Osborne 1962). Kendall (1953) examined the 19 indices of British
industrial share prices and commodity prices in New York and Chicago.
Based on the zero serial correlation, the study supports the random walk
model. Kendall's findings were supported by the previous study of
Working (1934). However, the studies did not provide the economic
rationale for the hypothesis because their justifications were based on
small sample (Working 1934; Kendall 1953; Roberts 1959). Kendall (1954)
argued that the small sample bias equals -1/(T-1), where T is the number
of time-series observations. Bias-adjusted first-order serial
correlation coefficients for annual earnings changes are close to zero
(Kothari 2001).
Consistent with the previous work of random walk model, Osborne
(1959, 1962) suggested that the market conditions would lead to random
walk model. He also concluded that the transaction varies on individual
securities because of the investors' decisions, so the economic
justification for the random walk is not important and the arguments
were based on the fair game model. Alexander (1961) was somewhat
supportive to the conclusion of Osborne (1959, 1962) and stated that it
would be well on speculating prices as a random walk. The criticism is
that Alexander (1961) did not expand 'fair game' assumption is
not sufficient to lead to a random walk. Later, Alexander (1964) used
the daily data on price indices from 1897 to 1959 and found the evidence
against random walk model. He also mentioned that from the view of
submartingale model, the market efficiency did not require the random
walk concept. Niederhoffer and Osborne (1966) investigated the NYSE and
indicated that the existence of market inefficiency because the analysts
or the specialists hold important information which are monopoly in
nature and this information might be used to turn a profit with respect
to strong form EMH.
The pioneering work, Lo and MacKinlay (1988) examined the US
security prices based on the 1216 weekly observations for the period 6th
September 1962 to 26th December 1985. They first introduced the variance
ratio to test the weak-form. They found that significant positive serial
correlation for weekly and monthly holding-period returns and therefore,
the study revealed that the rejection of random walk hypothesis for the
sample period. On the other hand, Fama and French (1988) found that
negative serial correlation for longer period and the 25% and 40% of the
variation of longer-period return was predictable from the past returns.
Poterba and Summers (1986) also concluded the rejection of random walk
hypothesis and hence found the evidence against EMH. They also argued
that the rejection of random walk could not be explained because of the
infrequent trading or time varying volatilities.
On the other hand, Lee (1992) investigated the US and ten other
industrialized countries, namely Australia, Belgium, Canada, France,
Italy, Japan, Netherlands, Switzerland, United Kingdom, and Germany to
test whether the weekly stock returns follow random walk model or not.
Using the variance ratio test, he pointed out that the random model on
weekly returns did exist for those countries. Consistent with Lee (1992)
study, Choudhry (1994) examined the individual stock indices in seven
OECD countries (US, United Kingdom, Canada, France, Germany, Japan and
Italy) from the period 1953 to 1989. Applying Augmented Dickey-Fuller
and KPSS unit root tests, and Johansen's co integration tests, he
concluded that the markets of the seven OECD countries were efficient
for the sample period.
Chan et al. (1997) tested 18 international stock markets
(Australia, Belgium, Canada, Denmark, Finland, France, Germany, India,
Italy, Japan, Netherlands, Norway, Pakistan, Spain, Sweden, Switzerland,
the United Kingdom, and the United States) for justifying the weak-form
efficiency using Phillips-Perron (PP) unit root and cointegration tests
from 1962 to 1992 with 384 monthly observations. They concluded all the
sampled stock markets were weak-form efficient. However, the result was
very much contradictory especially in India and Pakistan.
Al-Loughani and Chappel (1997) examined the weak-form efficiency in
UK (Daily observations of FTSE 30 Index) for the period June 1983 to
November 1989 using Lagrange multiplier (LM) serial correlation, unit
root and non-linear tests. They rejected the random walk model during
the sample period and concluded that FTSE 30 was not efficient in
weak-form.
Groenewold (1997) investigated the weak-form efficiency in
Australia (Statex Actuaries' Index) and New Zealand (NZSE-40 Index)
from 1975 to 1992 based on the daily observations. The conclusion was
contradictory because the unit root tests were supportive to weak-form
in both countries, whereas Granger causality test rejected the EMH and
the both countries' were not cointigrated. Lee and Mathur (1999)
concluded the Spanish future markets followed the random walk hypothesis
and weak-form efficient based on the serial correlations, unit root
tests, and variance ratio tests.
With regard to Groenewold (1997) and Lee and Mathur (1999)
conclusions, Worthington and Higgs (2004) tested the random walk
hypothesis in 16 developed markets (Austria, Belgium, Denmark, Finland,
France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Portugal,
Spain, Sweden, Switzerland, and the United Kingdom) from December 1987
to May 2003 using serial correlation, runs, unit root and multiple
variance ratio tests. They used the daily returns of share indices in
US$. The evidence showed that the most of the EU markets were weak-form
efficient except France, Finland and Netherlands. The different test
provided the mix result which was inconclusive in nature and they did
not comment on that.
Gan et al. (2005) tested the market efficiency in New Zealand,
Australia, US and Japan Stock Indices from 1990-2003 and based on the
Augmented-Dickey Fuller (ADF) and Phillips-Perron unit root tests (PP)
they concluded that the weak-form efficiency did exist in all the
sampled countries. This result was supported by Groenewold (1997) study.
Torun and Kurt (2008) examined the weak-form efficiency of 11 EMU
(European Monetary Union) countries for the period 1999-2006 using stock
market price index, consumer price index and purchasing power of euro
variables. They employed the panel unit root tests. The study revealed
that the markets of all 11 countries were weak-form efficient.
Hasanov (2009a) re-examined the efficiency of the Australia's
and New Zealand's stock markets, using the work of Narayan (2005).
He applied the nonlinear unit root test procedure following Kapetanios
et al. (2003) and concluded that both Australia's and New
Zealand's stock stock markets were not weak form efficient,
contrary to the findings of Narayan (2005).
3.2. Empirical evidence of emerging markets
The emerging stock markets have been highly focused by both
researchers and investors. Due to the globalization and the inflow of
FDI, the emerging markets have opened up their economy which attracted
global investors. Therefore, various studies have concentrated on the
return behaviour and the predictability, but the majority of them
examine the random walk behaviour in emerging markets.
Laurence (1986) studied on the KLSE stock exchange in Malaysia and
SES stock exchange in Singapore to find out the random walk hypothesis
for the period 1973 to 1978. Using the runs and autocorrelation test, he
concluded that both KLSE and SSE did not follow the random walk and they
are not weak-form efficient. In contrast to Laurence (1986) study,
Barnes (1986) found that the KLSE stock markets were weak-form efficient
for sample period 1975 to 1980. He used the same test of Laurence (1986)
and implied to 30 companies and sis sector indices.
On the other hand, Parkinson (1987) tested the weak-form efficiency
in Kenya (NSE) from 1974 to 1978 based on the monthly prices of 50
individual companies. He used the single run test only. The result
showed that the NSE did not exhibit the weak-form efficiency. On the
continuation of Parkinson (1987) work, Dickinson and Muragu (1994) also
investigated NSE for the period 1979 to 1989 using the weekly prices of
30 most actively traded stocks. They revealed that the weak-form
efficiency exist in NSE. So, the result is contradictory to the earlier
study in Kenya. The reason might be the use of a different test.
Urrutia (1995) examined the random walk behaviour in four Latin
American emerging markets (Argentina, Brazil, Chile, and Mexico) from
1975 to 1991 based on the variance ratio and runs tests. The result was
mixed, because the variance ratio rejected the random walk hypothesis in
four countries whereas the run tests did support for weak-form
efficiency in all four countries. Similar with the study, Ojah and
Karemera (1999) tested the weak-form efficiency in the same four Latin
American countries applying the multiple variance ratios and run tests
from 1987 to 1997 and concluded based on the multiple variance ratio
test that the all for countries did follow weak-form efficiency.
Karemera et al. (1999) studied the weak-form efficiency test in 15
emerging stock from 1986 to 1997 markets using Ojah and Karemera (1999)
methods. They concluded that 10 out of 15 emerging markets followed the
random walk hypothesis based on the multiple variance ratios, but only 5
out of the 15 were consistent the random walk hypothesis under the run
tests. So, the result was very much controversy in nature because of the
different conclusion.
Chang et al. (1996) investigated the weak-form efficiency in Taiwan
(TSE) from 1967 to 1993 applying Ljung-Box Q, the runs and the unit root
tests. The study stated that that TSE was weak-form efficient.
Consistent with the study, Chang and Ting (2000) also examined the TSE
using a single test (variance ratio test) for the period 1971 to1996.
They also confirmed that TSE was weak-form efficient based on monthly,
quarterly and yearly returns. However, the result based on the weekly
data showed that the TSE was not weak-form efficient. Tas and Dursonoglu
(2005) used the DF unit root test and run test to examine the weak-form
efficiency in Turkey (ISE-30 indices) from 1995 to 2004. They revealed
that both of the tests rejected random walk hypothesis in ISE.
Hasanov (2009b) re-investigated the efficiency of the South
Korea's stock market, extending work of Narayan and Smyth (2004).
He used the nonlinear unit root test developed by Kapetanios et al.
(2003). The study rejected the null hypothesis of unit root and
therefore South Korea's stock market was not weak form efficient,
contrary to the findings of Narayan and Smyth (2004).
In the Middle East, Butler and Malaikah (1992) tested the random
walk model in Kuwait and Saudi Arabian stock markets from 1985 to 1989
using autocorrelation test. The data comprised the daily returns of two
stock markets. The study revealed that the Saudi Arabian stock market
was weak-form efficient but the Kuwaiti stock market was not weak-form
efficient. In a similar study, Abraham et al. (2002) confirmed that
Kuwait, Saudi Arabia, and Bahrain stock markets did not follow random
walk hypothesis. They used the variance ratio and runs tests for the
period 1992 to 1998. Again, Hassan et al. (2003) used the GARCH-M and
EGARCH models to test the weak-form efficiency in Kuwait (KSE) stock
market. The study found the evidence of inefficiency market. They also
mentioned that the reason of inefficiency were various regulatory
reforms carried out in the sample period.
Moustafa (2004) investigated the weak-form efficiency in UAE stock
market from 2001 to 2003 using the daily price indices. They applied the
run test and found that 40 stocks out of the 43 were random at 5% level
of significance which was considered to be weak-form efficient. They
pointed out that UAE was one of the fastest growing countries and the
new structural development of stock market was happening.
In African emerging markets study, Appiah-Kusi and Menyah (2003)
examined the weak-form efficiency in 11 African stock markets (Botswana,
Egypt, Ghana, Ivory Coast, Kenya, Mauritius, Morocco, Nigeria, South
Africa, Swaziland, and Zimbabwe) from 1989 to 1995 using weekly data
indices. Employing a logistic map and EGARCHM model, they provided the
evidence of five countries (Egypt, Kenya, Mauritius, Morocco, and
Zimbabwe) out of eleven were consistent with the weak-form efficiency.
They also mentioned that inappropriate models could provide the risk
premiums in EMH. In a similar study, Akinkugbe (2005) concluded that the
Botswana stock markets were weak-form and semi-strong-form efficient. He
used Autocorrelation, Augmented Dickey-Fuller (ADF) and Phillips-Perron
(PP) unit root tests for the period 1989-2003 based on the 738 weekly
observations.
In European emerging markets study, Gilmore and McManus (2003)
examined the random walk hypothesis in Czech Republic, Hungary and
Poland for the period 1995 to 2000 based on the weekly comprehensive
indices. They used the various methods including unit root, variance
ratio, autocorrelation, Johansen and Granger causality, Naive, ARIMA and
GARCH. The result was mixed: All the tests except Granger-causality
provided the evidence against weak-form efficiency in Czech Republic,
Hungary and Poland.
In another study, Smith and Ryoo (2003) tested the weak-form
efficiency in five European emerging markets (Greece, Hungary, Poland,
Turkey and Portugal) from 1991 to 1998 using the weekly data indices.
They found that Greece, Hungary, Poland and Portugal did not follow the
weak-form efficiency while Turkey was found to be weak-form efficient.
They mentioned that Turkey stock markets were weak-form efficient
because they were larger and liquid compare to other four markets.
However, the result was controversial with the previous studies, because
the larger markets in some cases did not follow random walk model (Hong
Kong and Korea- Huang 1995; Mexico- Urrutia 1995) whereas the small
markets did follow the random walks (Indonesia- Huang 1995; Argentina-
Urrutia 1995; Ojah, Karemera 1999).
Abrosimova et al. (2005) investigated the random walk hypothesis in
Russian stock market using daily, weekly, monthly RTS indices from 1995
to 2001 and concluded that Russian market was weak-form efficient. On
the other hand, Hassan et al. (2006) found that Czech Republic, Hungary,
Poland and Russia were not weak-form efficient, but Greece, Slovakia,
and Turkey followed the random walks. The similar findings were
conducted by Aktan et al. (2010) based on Baltic stock markets.
Hasanov and Omay (2007) addressed efficiency of eight transition
stock markets, including Bulgarian, Chinese, Czech, Hungarian, Polish,
Romanian, Russian and Slovakian stock markets by testing whether the
price series of these markets contain unit root. The results of
nonlinear unit root tests indicated that only Bulgarian, Czech,
Hungarian and Slovakian price series contain unit root, consistent with
weak form efficiency.
In a similar study, Hasanov and Omay (2008: 2645) argued that
"time series analysis allow proper modelling of nonlinearities in
economic and financial variables. A growing body of research was
dedicated to investigation of potential nonlinearities in conditional
mean of many economic and financial variables, mainly concentrating in
developed economies. However, nonlinearities in financial variables in
developing economies have not been fully examined yet". They
investigated Europe's two largest emerging stock markets, namely,
the Greek and Turkish stock markets using STAR family models. They did
not find nonlinearity in conditional variance, but found strong evidence
in favour of nonlinear adjustment of stock returns. They concluded that
"allowing for nonlinearity in conditional mean results in a
superior model and provides good out-of-sample forecasts, which
contradicts to efficient market hypothesis" (p. 2645).
Recently, Omay and Karadagli (2010) investigated efficiency of
Bulgarian, Greek, Hungarian, Polish, Romanian, Russian, Slovenian and
Turkish stock markets. They employed the nonlinear unit root test
proposed by Kapetanios et al. (2003) and nonlinear panel unit root test
by Ucar and Omay (2009). The ADF and PP indicated Bulgarian, Greek,
Hungarian, Polish, Romanian, Russian, Slovenian and Turkish stock
markets were weak form efficient, while the results of nonlinear unit
root test implied that Russian, Romanian and Polish stock markets were
not weak form efficient. The findings questioned the traditional
literature of EMH literature arguing: 'the linear panel unit root
test suggest that this group as all efficient where as nonlinear panel
unit root test suggest as a group they are not efficient' (Omay,
Karadagli 2010: 1).
3.3. Empirical evidence of South Asian stock markets
In South Asian emerging markets study, Poshakwale (1996) tested the
weak-form efficiency in India (BSE) based on the day of the week effect
from 1987 to 1994. He found that the prices did not follow normal
distribution and runs and serial correlation tests showed that the non
random behaviour. Therefore, he concluded that the Indian stock market
(BSE) was not weak-form efficient. However, the conclusion was
contradictory with previous study of Sharma and Kennedy (1977) who found
that BSE was weak-form efficient. In another South Asian study,
Abeysekera (2001) provided the evidence of inefficiency weak-form in Sri
Lanka (CSE). He used the daily, weekly and monthly returns of the
Sensitive Share Index from 1991 to 1996. Gupta and Basu (2007) tested
the weak-form efficiency in Indian two major stock markets (BSE and NSE)
from 1991 to 2006. They concluded that the both stock exchanges in India
did not follow the weak-form efficiency.
Siddiqui and Gupta (2009) investigated the random walk hypothesis
in the Indian stock market (NSE) using daily stock indices from 1
January 2000 to 31 October 2008. They employed both non-parametric
(Kolmogorov-Smirnov normality test and run test) test and parametric
test (Autocorrelation test, Autoregression, ARIMA model). They found
that the Indian stock market did not follow weak-form of market
efficiency. They also mentioned that various macro economic factors were
important to justify the efficiency or inefficiency in emerging markets.
There are few studies conducted on the DSE weak-form efficiency
(Dhaka Stock Exchange), but not on the CSE (Chittagong Stock Exchange).
The first attempt was done by Alam et al. (1999). They examined the
weak-form efficiency of DSE for the period 1986 to 1995 based on the
monthly stock price indices. Applying variance ratio test, they revealed
that the DSE followed random walk model and the DSE was weak-form
efficient.
Hassan, Islam and Basher (2000) examined the weak-form efficiency
in DSE for the period September 1986--November 1999. They found that the
equity return of the DSE were the positive skewness of 0.11 and 22.93,
excess of kurtosis of 49.66 and 992.65 and the deviation from the
normality. They also revealed that there was a significant negative
serial correlation (-0.07) which implied that the DSE market was not
weak-form efficient. They further found that there were a significant
relationship between the conditional volatility and the stock returns.
Mobarek and Keasey (2002) investigated to test weak-form efficiency
based on the daily price indices of all listed DSE securities for the
period 1988 to 1997. The sample covered 2638 daily observations. They
used various tests including Autocorrelation test, Autoregression and
run tests. They concluded that the significant autocorrelation
coefficient at different lags which did not support the weak-form
efficiency or random walk model of DSE market.
Ahmed (2002) examined the random walk in DSE from January 1990 to
April 2001 and for two sub-periods. Using Ljung-Box statistic, he found
that the first sub period had positive autocorrelation compare to the
second sub period but the full period had dominant negative
autocorrelation and therefore, the result rejected the null hypothesis
of weak-form efficiency in DSE. He also mentioned that the new
information took nearly a month to fully reflect the share prices in
DSE. Based on the filter rule, Kader and Rahman (2004) found that the
abnormal profit was possible on a regular basis using specific trading
patterns. They concluded the DSE did not follow weak-form efficiency and
it violated the random walk hypothesis.
Khaled and Islam (2005) tested the weak-form efficiency of the DSE
market. They used the daily, weekly and monthly market prices for the
period 1990 to 2001. They applied the unit root and variance ratio.
Further, they investigated the structural changes based on the variance
ratio for the period before the July 1996 when the market was boomed and
after the March when the market crashed. They mentioned that the EMH
could not be rejected on the monthly data. They concluded that market
inefficiency was for the pre-boomed time not for the post-crash time of
market. They also revealed that the DSE market was in favour of
predicting share price before the July 1996 pre-boomed time using the
heteroscedasticity of variance ratio test. The study criticized the work
of Mobarek and Keasey (2002) who found that the market inefficiency
during the market crash time. Khaled and Islam (2005) argued that the
possibility of getting the inefficiency result (Mobarek, Keasey (2002))
might be the use of Box-Pierce Q test which was considered the less
powerful test of autocorrelation in the presences of heteroskedastic
errors.
Mollah et al. (2005) examined the weak-form efficiency in DSE-20
using daily price indices for the period 2001 to 2003. The stationarity
of time series were used in their study. They found that the coefficient
was not significant which did not support the weak-form efficiency of
the DSE-20 market. They also pointed out the past prices could be used
to forecast and predict the future prices in DSE-20. Although, the study
was based on the top 20 companies in Dhaka Stock Exchange, the sample
period was relatively low compare to other empirical studies in both
developed and emerging markets. The findings are supported by the prior
studies (Mobarek 2000; Chowdhury et al. 2001) on the Bangladeshi stock
markets. Table 2 shows summary of the selective empirical studies on
weak-form efficiency in different stock markets.
4. Conclusion
The prior empirical studies show that there are contradictory
evidences of weak-form efficiency in both developed and emerging
markets. Traditionally, the developed markets are weak-form efficient
(Lee 1992; Choudhry 1994; Chan et al. 1997). However, this is not
consistent because the recent evidence shows the mixed evidence compared
to the earlier studies (Groenewold 1997; Abraham et al. 2002;
Appiah-Kusi, Menyah 2003; Smith, Ryoo 2003). On the other hand,
generally the emerging markets do not follow random walks (i.e. other
factors may be relevant, cultural factors in Baltic, Luptakova et al.
2005; Tvaronaviciene, Michailova 2006; and political factors, Sepper,
Alas 2008). Again, the mixed evidence exists. The emerging markets
differ from the developed countries because of the poor level of
liquidity and trading activity, weak institutional infrastructure and
more information asymmetry (Khaled, Islam 2005). Khaled and Islam (2005)
also mentioned that not all of the emerging markets are necessarily
entirely inefficient and in fact, some researchers have found some of
the larger and even smaller stock markets in emerging countries to be
weak-from efficient. The debate still remains on theoretical
implications of the EMH across the world. For example, there is
extensive literature which is claimed that many economic variables,
including financial ones, follow nonlinear processes (see, for example,
Granger, Terasvirta 1993; Campbell et al. 1997; McMillan 2003). In
recent years, although, predictability and efficiency of emerging
markets have attracted interest of financial economists (e.g., Emerson
et al. 1997; Dockery, Vergari 1997; Liu et al. 1997; Zalewska-Mitura,
Hall 1999; Rockinger, Urga 2001; Harrison, Paton 2004; Cajueiro, Tabak
2006), no consensus on whether or not efficient market hypothesis holds
for these markets is attained yet. A common feature of these studies is
that possible nonlinearities in conditional mean of the series have not
been taken into account in testing efficiency of these markets.
Therefore, possible nonlinearities in data generating process should
explicitly be taken into account in analysing financial time series in
order to avoid spurious results. There are only few studies on South
Asian stock markets on an individual country basis, but the results are
mixed and conflicting: The majority of the studies reject the weak-form
efficiency in DSE, NSE and CSE (Mobarek, Keasey 2002; Hassan et al.
2000; Ahmed 2002; Kader, Rahman 2004; Khaled, Islam 2005; Mollah et al.
2005), except Alam et al. (1999) who support the weak-form efficiency in
DSE. So, consistent with the previous literature, the study identifies
the gap and urging further research on behavioural explanation to answer
those reasons. Most importantly, how it deviates from the developed
market and what are the practical reasons behind this? No studies have
been conducted to examine the weak-form efficiency of the overall stock
markets of South Asian context. Paradoxically, the present study is
considered to be the first study to provide the overall pictures of the
South Asian market efficiency comparisons based on the evidence of prior
literatures. Besides making a contribution to the literature on the
weak-form efficiency of emerging stock market like Bangladesh, India and
Sri Lanka with more recent EMH literature information and
categorisation, the findings of the study may be equally relevant in
other emerging countries' stock markets. The study also calls for
further research on the reasons for market efficiency using qualitative
aspects to enlighten the behavioural issues of the markets.
doi: 10.3846/16111699.2011.620140
Received 26 January 2011; accepted 09 August 2011
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Mohammad NURUNNABI is a Senior Lecturer in Accounting at Edge Hill
University, Lancashire, UK and pursuing PhD at University of Edinburgh,
UK. He has presented papers in British Accounting Association (BAA),
Irish Accounting and Finance Association (IAFA) and the Institute of
Chartered Accountants of Scotland (ICAS). His current research focuses
on Corporate Governance, Critical Accounting and IFRSs Implementation
Issues. He has published in academic journals including the
International Journal of Managerial and Financial Accounting,
International Journal of Critical Accounting, Journal of Human Resource
Costing & Accounting, Journal of Asia Business Studies and
PROSHIKHYAN, A Journal of Training and Development.
Mohammad Nurunnabi Business School, Edge Hill University, St Helens
Road, Ormskirk, Lancashire, L39 4QP, UK E-mail:
mohammad.nurunnabi@edgehill.ac.uk
Table 1. Comparison of stock markets performance in South Asia
(2008-2009 and 2007-2008)
Country Market Name 2008-2009 2007-2008 % Change
Bangladesh Dhaka
(DSE-GEN) 3000.50 2149.32 39.60
India Mumbai
(BSE-SENSEX) 13461.60 14650.50 -8.12
Pakistan Karachi
(KSE-100) 12289.00 13772.50 -10.77
Sri Lanka Colombo
(CSE-SELECTED) 2457.84 2572.20 -4.45
Table 2. Summary of the selective empirical studies on weak-form
efficiency in developed, emerging and South Asian stock markets
The plus (+) sign denotes that the weak-form efficiency or random walk
hypothesis is not rejected; the negative (-) sign indicates that the
weak-form efficiency or random walk hypothesis is rejected; and the
plus-minus signs together (+/-) indicates the mixed results of
rejecting the random walk hypothesis. The studies are divided into
three categories: Developed Markets, Emerging Markets and South Asian
markets
Study Country/Market Period
Developed Markets:
Lo and MacKinlay US 1962-1985
(1988)
Lee (1992) US and other 1967-1988
ten
industrialized
countries
Choudhry (1994) Seven OECD 1953-1989
Countries (US,
UK, Canada,
France,
Germany, Japan
and Italy)
Chan et al. (1997) 18 1961-1992
international
stock markets
Al-Loughani and UK 1983-1989
Chappel (1997)
Groenewold (1997) Australia and 1975-1992
New Zealand
Lee and Mathur Spain 1989-1998
(1999)
Worthington and 16 European 1987-2003
Higgs (2004) developed
markets
Gan et al. (2005) New Zealand, 1990-2003
Australia, US
and Japan
Torun and Kurt 11 EMU 1999-2006
(2008) (European
Monetary Union)
countries
Emerging Markets:
Laurence (1986) Singapore and 1973-1978
Malaysia
Barnes (1986) Malaysia 1975-1980
Parkinson (1987) Kenya 1974-1978
Dickinson and Muragu Kenya 1979-1988
(1994)
Urrutia (1995) Argentina, 1975-1991
Brazil, Chile
and Mexico
Ojah and Karemera Argentina, 1987-1997
(1999) Brazil, Chile
and Mexico
Karemera et al. 15 emerging 1986-1997
(1999) markets
Chang et al. (1996) Taiwan 1967-1993
Chang and Ting Taiwan 1971-1996
(2000)
Tas and Dursonoglu Turkey 1995-2004
(2005)
Butler and Malaikah Kuwait and 1985-1989
(1992) Saudi Arabia
Abraham et al. Kuwait, Saudi 1992-1998
(2002) Arabia and
Bahrain
Hassan et al. (2003) Kuwait 1995-2000
Moustafa (2004) The United Arab 2001-2003
Emirates (UAE)
Appiah-Kusi and 11 African 1989-1995
Menyah (2003) stock markets
Akinkugbe (2005) Botswana 1989-2003
Gilmore and McManus Czech Republic, 1995-2000
(2003) Hungary and
Poland
Smith and Ryoo Greece, 1991-1998
(2003) Hungary,
Poland,
Portugal and
Turkey
Abrosimova et al. Russia 1995-2000
(2005)
Hassan et al. (2006) Seven European 1988-2002
emerging stock
markets
South Asian Markets:
Poshakwale (1996) India (BSE) 1987-1994
Sharma and Kennedy India (BSE) 1963-1973
(1977)
Abeysekera (2001) Sri Lanka (CSE) 1991-1996
Gupta and Basu India (BSE and 1991-2006
(2007) NSE)
Siddiqui and Gupta India (NSE) 2000-2008
(2009)
Alam et al. (1999) Bangladesh 1986-1995
(DSE)
Hassan et al. (2000) Bangladesh 1986-1999
(DSE)
Mobarek and Keasey Bangladesh 1988-1997
(2002) (DSE)
Ahmed (2002) Bangladesh 1990-2001
(DSE)
Khaled and Islam Bangladesh 1990-2001
(2005) (DSE)
Mollah, Rahman and Bangladesh 2001-2003
Islam (2005) (DSE-20)
Study Methodology Findings
Developed Markets:
Lo and MacKinlay Variance ratio test -
(1988)
Lee (1992) Variance ratio test +
Choudhry (1994) ADF unit root test +
KPSS unit root tests
Johansen
cointegration tests
Chan et al. (1997) Phillips-Perron (PP) +
unit root test and
Cointegration tests
Al-Loughani and LM serial -
Chappel (1997) correlation, Unit
root test and
Non-linear tests
Groenewold (1997) Granger causality +/-
test and Unit root
test
Lee and Mathur Serial correlations, +
(1999) Unit root, and
Variance ratio test
Worthington and Serial correlation +
Higgs (2004) test, Runs test,
Unit root test and
Multiple variance
ratio test
Gan et al. (2005) ADF unit root tests +
and Phillips-Perron
(PP) unit root test
Torun and Kurt Panel unit root +
(2008) tests
Emerging Markets:
Laurence (1986) Runs test and -
Autocorrelation test
Barnes (1986) Run test and +
Autocorrelation test
Parkinson (1987) Single run test -
Dickinson and Muragu Run test and +
(1994) Autocorrelation test
Urrutia (1995) Variance ratio test +
and Run test
Ojah and Karemera Multiple variance +
(1999) ratios test and Run
test
Karemera et al. Multiple variance +
(1999) ratios test and Run
test
Chang et al. (1996) Ljung-Box Q, Run +
test and Unit root
tests
Chang and Ting Variance ratio test +
(2000)
Tas and Dursonoglu DF unit root test -
(2005) and Run test
Butler and Malaikah Autocorrelation test -
(1992)
Abraham et al. Variance ratio test +/-
(2002) Run test
Hassan et al. (2003) GARCH-M model and -
EGARCH model
Moustafa (2004) Run test +
Appiah-Kusi and Logistic map and +/-
Menyah (2003) EGARCH-M model
Akinkugbe (2005) Autocorrelation test +
ADF unit root test
and Phillips-Perron
(PP) unit root test
Gilmore and McManus Unit root test -
(2003) Variance ratio test
Autocorrelation,
Johansen and Granger
causality, ARIMA and
GARCH model
Smith and Ryoo Variance ratio test +/-
(2003) and Autocorrelation
test
Abrosimova et al. Unit root test +
(2005) Variance ratio test
and Autocorrelation
test
Hassan et al. (2006) Ljung-Box +/-
Q-statistic Run test
and Variance ratio
test
South Asian Markets:
Poshakwale (1996) Serial correlation -
test and Run test
Sharma and Kennedy Run test Spectral +
(1977) analysis test
Abeysekera (2001) Run test -
Autocorrelation test
and Unit root test
Gupta and Basu ADF test, PP test -
(2007) and KPSS test
Siddiqui and Gupta Kolmogorov-Smirnov -
(2009) test Run test
Autocorrelation test
Autoregression and
ARIMA model
Alam et al. (1999) Variance ratio test +
Hassan et al. (2000) Variance ratio test -
Mobarek and Keasey Autocorrelation -
(2002) test, Autoregression
and Run test
Ahmed (2002) Ljung-Box statistic -
test
Khaled and Islam Unit root test and -
(2005) Variance ratio test
Mollah, Rahman and Stationarity of time -
Islam (2005) series
