B u s i n e s s, Ma n ag e M e n t a n d e d u c at i o n
ISSN 2029-7491 print / ISSN 2029-6169 online

2012, 10(1): 110–127
doi:10.3846/bme.2012.09

Copyright © 2012 Vilniaus Gediminas Technical University (VGTU) Press Technika
www.bme.vgtu.lt

MARKET BEHAVIOuR: CASE STuDIES OF NASDAQ OMX BALTIC

Jelena Stankevičienė1, Natalija Gembickaja2

Vilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, Lithuania
E-mails: 1jelena.stankeviciene@vgtu.lt (corresponding author);  

2natalija.gembickaja@vgtu.lt;
Received 10 May 2011; accepted 15 April 2012

Abstract. The paper examines market behaviour, defines the concept of behaviour-
al finance and exhaustively analyzes the varying behaviour of market participants 
and occurring examples. The article deals with the issues of possible anomalies 
describing their main features. The conducted research is aimed at investigating 
two anomalies in the Baltic Stock Exchanges, including branches in Tallinn, Riga 
and Vilnius. The publication selects specific stocks listed in the equity market and 
analyzes their features. The obtained results are compared to discuss differences 
and characteristics of the markets. The paper also presents an original examination 
of the practical aspects of momentum and contrarian anomalies, underlies recom-
mendations and helps financial market participants with a better understanding of 
the influence of anomalies from an economic perspective and with improving their 
competitiveness thus helping them to make appropriate decisions.

Keywords: market behaviour, behavioural finance, financial market anomalies, 
momentum and contrarian anomalies.

Reference to this paper should be made as follows: Stankevičienė, J.; 
Gembickaja, N. 2012. Market behaviour: case studies from NaSdaq oMx 
Baltic, Business, Management and Education 10(1): 110–127. 
http://dx.doi.org/10.3846/bme.2012.09
JEL classification: d53, G02, G11, o16. 

1. Introduction

over the past few years, equity markets have been characterized by a rise in volatility 
and fluctuations. The ever more integrated financial markets are increasingly exposed 
to macroeconomic shocks affecting the markets on a global scale. From the investor’s 
point of view, the vulnerability of the markets has lead to increased uncertainty and 
unpredictability, as market conditions cannot always be judged with the help of standard 
financial measures and tools. For a long time, when making financial decisions, market 
participants have relied on the notion of efficient markets and the rational behaviour of 
the investor. However, the idea of fully rational investors always maximizing their utility 
and demonstrating perfect self-control is becoming inadequate. despite strong evidence 
that the stock market is highly efficient, i.e. one cannot earn abnormal profits by trading 
on publicly available information, there have been a number of studies documenting 



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long-term historical anomalies in the stock market that seem to contradict the efficient 
market hypothesis. during the recent years, the examples of market inefficiency in the 
form of anomalies and the irrational behaviour of the investor have been observed more 
frequently (Johnsson et al. 2002). The existing phenomenon can in part be attributed to 
the less-than-rational aspects of investor behaviour and human judgment. 

due to a growth in uncertainty in financial markets, the approaches based on perfect 
predictions, completely flexible prices and a complete knowledge of investment decisions 
made by other players in the market are increasingly unrealistic in today’s global financial 
markets. Behavioural finance is a new paradigm of the finance theory that seeks to under-
stand and predict systematic financial market implications of psychological decision-mak-
ing (abarbanell, Bernard 1992). By understanding human behaviour and a psychological 
mechanism involved in financial decision-making, standard finance models may be im-
proved to better reflect and explain the reality faced in today’s evolving markets. Moreover, 
this understanding should help with avoiding the occurrence of an anomaly phenomenon 
and enhance the efficiency of the present global financial markets (Johnsson et al. 2002).

The goal of research is to examine and analyze two anomalies in NaSdaq oMx 
Baltic stock exchanges in Tallinn, Riga and Vilnius forming the Baltic Market.

Market efficiency, in the sense that market prices reflect fundamental market char-
acteristics and that excess returns on the average are levelled out in the long run, has 
been challenged by behavioural finance. There have been a number of studies pointing 
to market anomalies that cannot be explained with the help of a standard financial theory 
such as abnormal price movements in connection with IPos, mergers, stock splits and 
spin-offs. This contradicts the efficient market hypothesis and implies that investors 
believe they can beat the market and overestimate their talents while underestimating 
the likelihood of bad outcomes. Throughout the years, statistical anomalies have been 
continued to appear which suggests that the existing models of standard finance are, if 
not wrong, probably, incomplete. Investors have been shown not to react “logically” to 
new information but to be overconfident and to alter their choices when given superfi-
cial changes in the presentation of investment information (olsen 1998). The existing 
anomalies suggest that the fundamental principles of rational behaviour underlying the 
efficient market hypothesis are not entirely correct and that we need to look, as well, 
at other models of human behaviour, as studied in other social sciences (Shiller 1998).

The presence of regularly occurring anomalies in the conventional economic theory 
was a big contributor to the formation of behavioural finance. These so-called anoma-
lies, and their continued existence, directly violate modern financial and economic theo-
ries, which assume rational and logical behaviour. 

The paper describes and analyzes the momentum and contrarian anomaly, i.e. size ef-
fect, momentum and contrarian anomalies. These anomalies were not randomly selected 
as by some extent they could cause or be related.

Some researchers argue that large positive abnormal returns generated by the con-
trarian strategy can be attributable to this well known size effect (Zarowin 1990; Clare, 



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J. Stankevičienė, N. Gembickaja. Market behaviour: case studies of NaSdaq OMx Baltic

Thomas 1995 respectively for U.S. and U.K. evidence). For this reason, there is a 
tendency among many momentum/contrarian studies to examine whether the returns 
earned are attenuated by small firm effect.

However, Gunasekarage, Wan Kot (2007) published their empirical findings provid-
ing some evidence that momentum profits were available across all liquidity groups but 
excluding possibilities that these returns were influenced by the well known size effect 
or January effect. Moreover, Chopra et al. (1992) shows that having controlled size or 
beta, overreaction in momentum and contrarian anomalies though gets reduced but still 
remains. on the basis of evidence reported in these studies, it is important to examine if 
profits generated by contrarian and momentum anomalies are also driven by size effects.

2. Momentum and contrarian anomaly

Two recent approaches to investment that have challenged the weak form of the EMH 
are the contrarian strategy and the momentum strategy. The contrarian strategy, sug-
gested by the overreaction hypothesis, ranks shares on the basis of their past perfor-
mance and recommends buying past losers and selling past winners. In contrast, the 
momentum strategy also ranks shares according to their prior performance but recom-
mends the purchase of the past winners and the sale of the past losers. Haj Youssef et 
al. (2010) pointed that the best (poorly) performing stocks would continue their upward 
(downward) trend, momentum strategies, to be profitable in the medium run. In the 
long run, the trend will reverse and the contrarian strategy, implying a long position in 
the past losers and a short position in the winners, will be profitable. Prior findings of 
Jegadeesh and Titman (1993) suggest that the length of the holding period is relevant. 
Momentum strategies were found to generate significant positive abnormal returns in 
three-to-twelve month holding periods, but not for very short (weekly or monthly) or 
very long (in excess of one year) holding periods. 

Many studies provide evidence for the profitability of both above introduced strate-
gies. Table 1 provides information on researchers investigating a certain investment 
strategy at certain markets. 

The first formal investigation into the momentum effect was conducted by Jegadeesh 
and Titman (1993). They measured the performance of the strategy for buying the win-
ner’s portfolio and shorting the loser portfolio over various holding periods. The mo-
mentum strategy has also been examined in the markets outside the US. For example, 
the UK market has been investigated by Liu et al. (1999) and Hon and Tonks (2003). 
Chan et al. (2000) has examined the momentum effect based on individual stock market 
indices in 23 countries. They have also found statistically significant evidence of mo-
mentum profits. drew et al. (2007) investigated the profitability of momentum strategies 
in australian setting and discovered a substantial momentum in monthly stock returns 
for the period 1988–2002. Gunasekarage and Wan Kot (2007) studied the profitability 
of such strategy in the New Zealand stock market and proved the existence of the 



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momentum effect in the New Zealand market. Their empirical findings provide some 
evidence that momentum profits are available across all liquidity groups but exclude 
possibilities that these returns were influenced by the well known size effect or January 
effect. Rastogi et al. (2009) found strong support for the existence of momentum strat-
egy profits in Indian markets, while evidence for overreaction was present only in stocks 
referred to be mid-size.

Table 1. Investigation into momentum and contrarian strategies in international markets. 
(Source: created by authors)

Momentum effect

Jegadeesh and Titman (1993) USa

Liu et al. (1999) UK

Hon and Tonks (2003) UK

Chan et al. (2000)

23 countries (australia; austria; 
Belgium; Canada; denmark; France; 
Germany; Hong Kong; S. Korea; 
Italy; Japan; Netherlands; Norway; S. 
africa; Spain; Singapore; Switzerland; 
U.K.; U.S.; Thailand; Taiwan; 
Malaysia; Indonesia

drew et al. (2007) australia
Gunasekarage and Wan Kot 
(2007) New Zealand

Rastogi et al. (2009) India

Contrarian effect

de Bondt and Thaler (1984) USa

Power et al. (1991) UK

Wang et al. (1999) Japan, Hong Kong, Taiwan 

Zamri and Hussain (2001) Malaysia

alonso and Rubio (1990) Spain 

da Costa (1994) Brazil 

Gunasekarage and Power (2005) Sri Lanka 

No evidence of 
either effect

Kryzanowski and Zhang (1992) Canada

Brailsford (1992) australia

Hameed and Kusnadi (2002) asia

de Bondt and Thaler (1984) were the first to prove the contrarian effect in the USa; 
they performed research using data on New York Exchange (NYSE) common stocks, 
which resulted in loser portfolios outperforming the market, while winner portfolios, on 
the other hand, earned less than the market. Moreover, it was found that “the overreac-
tion effect was asymmetric; it is much larger for losers than for winners.” de Bondt and 
Thaler’s proposition is based on evidence that individuals tend to overweight recent in-
formation and underweight prior information when revising beliefs. Market overreaction 



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J. Stankevičienė, N. Gembickaja. Market behaviour: case studies of NaSdaq OMx Baltic

has also been examined outside the US market. For example, Power et al. (1991) tested 
mean-reverting tendencies towards share returns of ‘excellent’ and ‘non-excellent’ UK 
companies for the period from 1973 to 1987 and documented results consistent with 
the winner-loser effect; during the five-year period following portfolio formation, the 
loser portfolio yielded a cumulative abnormal return of 86 per cent, while the winners 
generated a cumulative abnormal return of 47 per cent. Further evidence for the profit-
ability of the contrarian strategy has been documented for the markets in Japan, Hong 
Kong and Taiwan (Wang et al. 1999), Malaysia (Zamri, Hussain 2001), Spain (alonso, 
Rubio 1990), Brazil (da Costa 1994) and Sri Lanka (Gunasekarage, Power 2005). all 
these studies report a long-run reversal of fortune for the winner and loser portfolios; an 
investment strategy of buying past losers and selling past winners generates statistically 
significant returns to investors. 

There are some studies that have failed to find evidence of either overreaction or 
momentum. Kryzanowski and Zhang (1992) found no evidence of mean reversion be-
haviour in the Canadian market; over the 24-month post-ranking period, the winner’s 
portfolio outperformed the loser portfolio by 7.42 per cent. Brailsford (1992) analyzed 
australian data and discovered that, even though the winner’s portfolio in his study 
experienced a price reversal during the 36-month testing period, the loser portfolio con-
tinued to accumulate negative abnormal returns; at the end of the post-ranking period, 
both the winner and loser portfolios realized negative abnormal returns of 69.58 per cent 
and 52.59 per cent respectively. Hameed and Kusnadi (2002), who analyzed monthly 
returns of 1,008 securities, traded on six asian markets and found no evidence of this 
anomaly. on the other hand, Chan et al. (2000) proved that in 23 countries, including 
Canada, australia and some asian countries, the momentum strategy could be applied 
in stock markets. Moreover, other researchers such as drew et al. (2007) and Wang et 
al. (1999) made investigations into australian and asian countries respectively and got 
reverse results. The only reasons for such contrary findings could be the time period 
analyzed or different methods of methodology and interpretation. 

Haj Youssef et al. suggests the behavioural approach as the advanced one to explain 
the profitability of these trading strategies. This approach explains strategy profits by 
means of judgment biases inducing investors’ over-reaction or under-reaction to infor-
mation and as a result producing the continuation and reversals of stock returns. one 
of the earliest observations about overreaction in markets was made by J. M. Keynes 
(1964): “…day to day fluctuations in profits in the existing investments, which are obvi-
ously of an ephemeral and non-significant character, tend to have altogether excessive, 
and even an absurd, influence on the market”.

advocates for the behavioural approach propose a number of theoretical models 
of investor behaviour to explain these serial correlation properties in stock prices. The 
underpinning of daniel et al. (1998) is investor overconfidence. They consider that 
stock prices are determined by the informed investors who are subject to two biases: 
overconfidence and self-attribution. overconfidence in their signals causes overreaction 
to their private information, and self-attribution causes under-reaction to public infor-



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Business, Management and Education, 2012, 10(1): 110–127

mation. over-reaction to private information leads them to push up the prices of the 
winners above their fundamental values. This trend will be reversed, in the long run, 
when public information is confirmed. Specifically, when a positive earnings surprise 
is followed by another positive (negative) surprise, the investor raises the likelihood 
that he is in the trending regime and tends to become too optimistic (pessimistic) about 
the future profitability of the firm. as a result, the firms realizing a rapid growth in 
earnings tend to become overvalued, and those realizing a slow growth in earnings 
tend to become undervalued. (Barberis et al. 1998, 2003) The behavioural models 
also suggest that such anomaly is affected by information asymmetry. Specifically, 
they argue that the momentum (and contrarian) effect is attributed to inefficient stock 
price reaction to the specific information about the firm. Empirical evidence supports 
it is related to various proxies for the quality and type of information about the firm, 
the relative amounts of information disclosed publicly and being generated privately 
(Haj Youssef et al. 2010).

3. Momentum and contrarian strategy in NASDAQ OMX Baltic Market

Momentum strategies will be profitable if stock returns display a positive serial correla-
tion, whereas contrarian strategies will be profitable in case of a negative serial correla-
tion of stock returns. In order to examine the profits of these trading strategies, the stocks 
listed on NaSdaq oMx Baltic were classified into four quintiles based on average 
returns (sorted from the lowest to the highest) in the one month period. The lowest and 
highest quintiles of stocks are termed as the loser and the winner portfolio respectively, 
while the second and third quintiles are not considered in investigation. This paper pro-
vides data on the market collected from three Baltic regions – NaSdaq oMx Vilnius, 
NaSdaq oMx Tallinn and NaSdaq oMx Riga for the period 2000.01–2009.12. 
Thereafter, the results of the Lithuanian market will be compared with those obtained 
in Estonia and Latvia, as these countries are more or less similar in respect of economy 
and financial situation. However, the speed of the strategy reversal in Lithuania is much 
slower than that in the USa or other developed countries, and as a result, would be a 
disparate comparison. Further empirical evidences from NaSdaq oMx Baltic show a 
graphical representation of winners and losers’ performance in Vilnius, Tallinn and Riga 
thereafter. as a result, it will provide a better view on comparing results. 

3.1. Evidence of the momentum and contrarian strategy in NASDAQ OMX Vilnius

The performance of the winner and loser portfolios is evaluated in the next 24 months, 
i.e. for the period from 2000.01 to 2009.12. The study has looked at the momentum 
results by getting these portfolios with reference to the performance at the intervals of 
1, 3, 6 and 12 months. We also evaluate the over-reaction phenomenon in the Lithuanian 
market looking at the intervals of 15 and 18 and 24 months. The difference between the 
average winner and the average loser portfolio was also computed testing its signifi-
cance. This is done to evaluate whether the momentum strategy of buying winners and 



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J. Stankevičienė, N. Gembickaja. Market behaviour: case studies of NaSdaq OMx Baltic

selling losers (or vice versa) would earn a positive difference in return for investors. 
Table 2 below shows the returns and standard deviation (risk taken) of the winner and 
loser portfolios in NaSdaq oMx Vilnius. 

Table 2. Returns of the winner-loser and winner minus loser portfolios received from NaSdaq 
oMx Vilnius (2000 – end of 2009 end). (Source: created by authors using data obtained from 
NaSdaq oMx Vilnius)
 Interval 

(in 
months)

Winner Loser Winner-loser

Returns Standard deviation Returns
Standard 
deviation Returns

Standard 
deviation

2000–
2001 

1 8.81% 44.73% –1.21% 1.65% 10.02% 43.08%
3 –2.66% 12.51% 0.18% 2.79% –2.84% 9.72%
6 –8.19% 15.44% –0.02% 2.02% –8.17% 13.42%
12 –9.39% 16.85% 0.15% 2.75% –9.54% 14.10%
15 –6.05% 13.57% 0.03% 3.48% –6.08% 10.09%
18 –16.15% 17.53% 1.53% 14.49% –17.68% 3.04%
24 –19.09% 12.18% 0.09% 1.64% –19.18% 10.54%

2002–
2003 

1 1.11% 3.38% –0.32% 3.17% 1.43% 0.21%
3 0.17% 2.33% 0.22% 2.79% –0.05% –0.46%
6 0.13% 2.40% –0.23% 2.50% 0.36% –0.10%
12 0.21% 2.34% 0.03% 1.83% 0.18% 0.51%
15 0.14% 1.72% 0.16% 2.55% –0.02% –0.83%
18 0.59% 2.35% 0.09% 1.85% 0.50% 0.50%
24 0.29% 2.29% 0.00% 2.76% 0.29% –0.47%

2004–
2005 

1 0.47% 1.73% 0.13% 1.33% 0.34% 0.40%
3 0.51% 2.17% 0.29% 1.95% 0.22% 0.22%
6 0.00% 1.57% 0.07% 2.22% –0.07% –0.65%
12 0.06% 2.27% 0.27% 2.43% –0.21% –0.16%
15 0.04% 2.18% 0.60% 2.99% –0.56% –0.81%
18 –0.21% 1.65% 0.14% 2.55% –0.35% –0.90%
24 0.00% 1.73% 0.09% 3.08% –0.09% –1.35%

2006–
2007

1 –0.03% 5.93% –0.43% 1.61% 0.40% 4.32%
3 –1.89% 6.58% –0.31% 3.18% –1.58% 3.40%
6 –6.55% 7.40% –0.24% 2.32% –6.31% 5.08%
12 –4.68% 8.63% 0.18% 2.09% –4.86% 6.54%
15 –4.21% 8.06% –0.13% 3.39% –4.08% 4.67%
18 –3.22% 7.58% 0.02% 1.88% –3.24% 5.70%
24 –4.56% 7.65% –0.07% 2.21% –4.49% 5.44%



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 Interval 
(in 
months)

Winner Loser Winner-loser

Returns Standard deviation Returns
Standard 
deviation Returns

Standard 
deviation

2008–
2009

1 –0.09% 2.60% –0.92% 2.82% 0.83% –0.22%
3 –0.31% 3.21% 0.07% 2.59% –0.38% 0.62%
6 –0.16% 2.99% –0.22% 2.56% 0.06% 0.43%
12 –0.49% 4.41% –0.84% 4.94% 0.35% –0.53%
15 –0.13% 3.73% 0.13% 4.60% –0.26% –0.87%
18 0.28% 3.55% 0.13% 3.87% 0.15% –0.32%
24 0.21% 3.81% 0.35% 3.67% –0.14% 0.14%

Several results arise from our experimental analysis. Considering the obtained em-
pirical evidences, we can make a conclusion that the momentum strategy of buying past 
winners and selling past losers in NaSdaq oMx Vilnius would result in significant 
positive return for the investor only in the first month considered in this study. The 
strategy for buying losers and selling winners would result in positive significant returns 
at the interval of 3 to 24 months. The momentum strategy could be used by the investor 
in the first month and within the period from 18 to 24 months. Moreover, the contrar-
ian strategy takes place in the period from 3 to 15 months. The results of analysis have 
suggested that the momentum strategy of buying past winners and selling past losers 
in NaSdaq oMx Vilnius in the specified period would result in significant positive 
return for the investor only for the first three months considered in this study.

The strategy for buying losers and selling winners would result in positive significant 
returns at the interval of 6 to 24 months. The investor will get profit from buying win-
ners and selling loosing shares only in the first months. However, in the next months, 
while losers are stable in their returns, winners represent a spiral drop. This completely 
contradicts the scientific findings of this particular strategy.

The momentum strategy of buying past winners and selling past losers would result 
in significant positive return for the investor for the first months at the intervals of 6 to 12 
and for 18 months. Moreover, the strategy for buying losers and selling winners would 
result in positive significant returns for the remaining third, 15 and 24 months. Therefore, 
it could be concluded that those strategies do not take place in the Lithuanian stock mar-
ket as stated in the strategy statement, because at least in the period from the beginning 
of 2000 to the end of 2009, no precious tendency for this anomaly was noticed. In the 
period from the beginning of 2000 to the end of 2001 and for the period 2006–2007, 
losers started earning higher returns from the third month. Later, it was hard to envisage 
any consistency, as both losers and winners slogged on for the returns. However, the pe-
riod of 2004–2005 could definitely show some momentum and contrarian strategy in the 
Lithuanian stock market. Still, we can conclude that though this strategy could take place 
in the market in the short term period, it disappears in the long term. 

End of Table 2



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J. Stankevičienė, N. Gembickaja. Market behaviour: case studies of NaSdaq OMx Baltic

Fig. 1. Graphical representation of returns received from NaSdaq oMx Vilnius using mo-
mentum and contrarian strategies (2000–end of 2009). (Source: created by authors using data 

obtained from NaSdaq oMx Vilnius)

3.2. Evidence of the momentum and contrarian strategy  
in NASDAQ OMX Tallinn 

The momentum strategy of buying past winners and selling past losers in NaSdaq 
oMx Tallinn would result in significant positive return for the investor for the first and 
24 months at the intervals of 6 to 12 months considered in this study (Table 3). The 
strategy of buying losers and selling winners would result in positive significant returns 
in the third month and in the period of 15 to 18 months.

–30.00%

–20.00%

–10.00%

0.00%

10.00%

20.00%

1 3 6 12 15 18 24R
et

ur
ns

Intervals (in months)

2000 – 2001 end 

– 0.50%

0.00%

0.50%

1.00%

1.50%

1 3 6 12 15 18 24

2002 –2003 end 

– 0.40%
– 0.20%

0.00%
0.20%
0.40%
0.60%
0.80%

1 3 6 12 15 18 24

2004 –2005 end 

– 8.00%
– 6.00%
– 4.00%
– 2.00%

0.00%
2.00%

1 3 6 12 15 18 24

2006–2007 end 

– 1.00%

– 0.50%

0.00%

0.50%

1 3 6 12 15 18 24

2008–2009 end 



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Business, Management and Education, 2012, 10(1): 110–127

Table 3. Returns of the winner-loser and winner minus loser portfolios received from NaSdaq 
oMx Tallinn (2000–end of 2009). (Source: made by authors using data obtained from 
NaSdaq oMx Tallinn)

 
Interval 
(in 
months)

Winner Loser Winner-loser

Returns Standard deviation Returns
Standard 
deviation Returns

Standard 
deviation

2000–
2001 

1 2.33% 8.59% –0.15% 0.85% 2.48% 7.74%

3 0.41% 5.72% 0.84% 2.71% –0.43% 3.01%

6 –0.26% 4.97% –0.40% 4.90% 0.14% 0.07%

12 0.42% 6.36% 0.17% 4.97% 0.25% 1.39%

15 –0.07% 3.72% 0.15% 4.53% –0.22% –0.81%

18 0.09% 2.58% 1.44% 4.90% –1.35% –2.32%

24 0.16% 4.58% 0.11% 3.29% 0.05% 1.29%

2002–
2003 

1 0.63% 2.03% –8.70% 16.11% 9.33% –14.08%

3 –2.24% 15.20% –4.62% 22.86% 2.38% –7.66%

6 –0.45% 4.34% –10.15% 17.86% 9.70% –13.52%

12 0.05% 1.24% –12.14% 17.92% 12.19% –16.68%

15 0.04% 0.97% –9.80% 17.27% 9.84% –16.30%

18 0.06% 1.80% –16.12% 19.32% 16.18% –17.52%

24 –0.11% 4.44% –16.81% 18.49% 16.70% –14.05%

2004–
2005 

1 0.69% 2.71% –0.30% 5.15% 0.99% –2.44%

3 0.23% 2.12% 0.12% 3.21% 0.11% –1.09%

6 –0.08% 2.20% 0.06% 3.19% –0.14% –0.99%

12 0.08% 1.19% 0.02% 4.21% 0.06% –3.02%

15 0.76% 2.86% 0.54% 3.54% 0.22% –0.68%

18 –0.11% 2.26% 0.29% 4.09% –0.40% –1.83%

24 0.16% 1.77% 0.39% 3.26% –0.23% –1.49%

2006–
2007

1 0.06% 1.14% –0.07% 3.60% 0.13% –2.46%

3 0.04% 1.37% –0.14% 2.35% 0.18% –0.98%

6 –0.23% 1.39% –0.05% 2.54% –0.18% –1.15%

12 0.25% 1.34% 0.38% 3.23% –0.13% –1.89%

15 0.09% 2.13% 0.16% 1.62% –0.07% 0.51%

18 –0.27% 3.31% 0.54% 3.41% –0.81% –0.10%

24 –0.29% 1.57% –0.43% 4.50% 0.14% –2.93%



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J. Stankevičienė, N. Gembickaja. Market behaviour: case studies of NaSdaq OMx Baltic

 
Interval 
(in 
months)

Winner Loser Winner-loser

Returns Standard deviation Returns
Standard 
deviation Returns

Standard 
deviation

2008–
2009

1 –0.98% 2.72% –0.52% 2.17% –0.46% 0.55%

3 –0.27% 1.97% 0.07% 2.78% –0.34% –0.81%

6 –0.45% 1.90% –0.17% 2.76% –0.28% –0.86%

12 –0.73% 4.69% –0.54% 4.44% –0.19% 0.25%

15 –0.56% 5.62% 0.05% 4.80% –0.61% 0.82%

18 0.20% 4.38% 0.04% 3.38% 0.16% 1.00%

24 0.42% 4.60% 0.32% 3.41% 0.10% 1.19%

Based on the obtained results and aforementioned conclusions, the strategy could not 
be used within the period of two years. Fig. 2 shows that winners all along the analyzed 
intervals are operating better than losers. The momentum strategy of buying past win-
ners and selling past losers in NaSdaq oMx Tallinn in the specified period would 
result in significant positive return for the investor over the period of 1 to 3 months and 
for 12 to 15 months considered in this study. The strategy of buying losers and selling 
winners would result in positive significant returns at the interval of 6 months and at the 
interval of 18 to 24 months. For the interval analyzed, the conclusion that the investor 
will get profit from buying winners and selling loosing shares only in the first three 
months and at the end of the two-year period could be made. However, in the remaining 
months, losers were stable in their returns while winners represented a spiral drop. This 
completely confirms the scientific findings of this particular strategy.

In addition to the previous results, analysis showed that the momentum strategy of 
buying past winners and selling past losers would result in significant positive return 
for the investor at the interval of 1 to 15 months. The strategy of buying losers and 
selling winners would result in positive significant returns for the remaining period of 
18 to 24 months. as a result, momentum and contrarian strategies do not take place 
in the Estonian stock market as stated in the strategy statement because at least in the 
period from the beginning of 2000 to the end of 2009, no precious tendency for this 
anomaly was noticed. In the period from the beginning of 2002 to the end of 2003, 
winners were operating better than losers at the interval of two years. However, for 
the period 2008-2009, losers started earning higher returns than winners at the interval 
of 15 months, which totally contradicts specific strategy peculiarities. In the following 
periods, it was hard to envisage any consistency as both losers and winners slogged on 
for returns, as can be seen from the periods 2000–2001 and 2004–2005. However, the 
period of 2006–2007 could definitely show some momentum and contrarian strategy in 
the Estonian stock market. Still, we can conclude that though this strategy could take 
place in the market in the short term period, it disappears in the long term

End of Table 3



121

Business, Management and Education, 2012, 10(1): 110–127

Fig. 2. Graphical representation of returns received from NaSdaq oMx Tallinn using mo-
mentum and contrarian strategies (2000–end of 2009). (Source: created by authors using data 

obtained from NaSdaq oMx Tallinn)

3.3. Evidence of the momentum and contrarian strategy  
in NASDAQ OMX Riga 

In respect of a more in-depth analysis of data obtained from NaSdaq oMx Riga, it 
should be concluded that the momentum strategy of buying past winners and selling past 
losers in NaSdaq oMx Riga would result in significant higher return for the investor 
at the interval of 24 months considered in this study (Table 4). The strategy of buying 
losers and selling winners would result in higher significant returns almost during the 
whole analyzed period, to be more precise, during first 18 months.

–1.00%

0.00%

1.00%

2.00%

3.00%

1 3 6 12 15 18 24

R
et

ur
ns

Interval (in months)

2000 –2001 end

Winner

Loser

– 0.50%

0.00%

0.50%

1.00%

1.50%

1 3 6 12 15 18 24

2002 –2003 end 

– 0.40%
– 0.20%

0.00%
0.20%
0.40%
0.60%
0.80%
1.00%

1 3 6 12 15 18 24

2004 – 2005 end 

– 0.60%
– 0.40%
– 0.20%

0.00%
0.20%
0.40%
0.60%

1 3 6 12 15 18 24

2006 – 2007 end

–1.50%

–1.00%

–0.50%

0.00%

0.50%

1 3 6 12 15 18 24

2008 –2009 end



122

J. Stankevičienė, N. Gembickaja. Market behaviour: case studies of NaSdaq OMx Baltic

Table 4. Returns of the winner-loser and winner minus loser portfolios received from  
NaSdaq oMx Riga (2000–end of 2001). (Source: made by the authors using data obtained 
from NaSdaq oMx Riga)

 
Interval 
(in 
months)

Winner Loser Winner-loser

Returns
Standard 
deviation Returns

Standard 
deviation Returns

Standard 
deviation

2000–
2001 

1 2.33% 8.59% –0.15% 0.85% 2.48% 7.74%

3 0.41% 5.72% 0.84% 2.71% –0.43% 3.01%

6 –0.26% 4.97% –0.40% 4.90% 0.14% 0.07%

12 0.42% 6.36% 0.17% 4.97% 0.25% 1.39%

15 –0.07% 3.72% 0.15% 4.53% –0.22% –0.81%

18 0.09% 2.58% 1.44% 4.90% –1.35% –2.32%

24 0.16% 4.58% 0.11% 3.29% 0.05% 1.29%

2002–
2003 

1 0.63% 2.03% –8.70% 16.11% 9.33% –14.08%

3 –2.24% 15.20% –4.62% 22.86% 2.38% –7.66%

6 –0.45% 4.34% –10.15% 17.86% 9.70% –13.52%

12 0.05% 1.24% –12.14% 17.92% 12.19% –16.68%

15 0.04% 0.97% –9.80% 17.27% 9.84% –16.30%

18 0.06% 1.80% –16.12% 19.32% 16.18% –17.52%

24 –0.11% 4.44% –16.81% 18.49% 16.70% –14.05%

2004–
2005 

1 0.69% 2.71% –0.30% 5.15% 0.99% –2.44%

3 0.23% 2.12% 0.12% 3.21% 0.11% –1.09%

6 –0.08% 2.20% 0.06% 3.19% –0.14% –0.99%

12 0.08% 1.19% 0.02% 4.21% 0.06% –3.02%

15 0.76% 2.86% 0.54% 3.54% 0.22% –0.68%

18 –0.11% 2.26% 0.29% 4.09% –0.40% –1.83%

24 0.16% 1.77% 0.39% 3.26% –0.23% –1.49%

2006–
2007

1 0.06% 1.14% –0.07% 3.60% 0.13% –2.46%

3 0.04% 1.37% –0.14% 2.35% 0.18% –0.98%

6 –0.23% 1.39% –0.05% 2.54% –0.18% –1.15%

12 0.25% 1.34% 0.38% 3.23% –0.13% –1.89%

15 0.09% 2.13% 0.16% 1.62% –0.07% 0.51%

18 –0.27% 3.31% 0.54% 3.41% –0.81% –0.10%

24 –0.29% 1.57% –0.43% 4.50% 0.14% –2.93%



123

Business, Management and Education, 2012, 10(1): 110–127

 
Interval 
(in 
months)

Winner Loser Winner-loser

Returns
Standard 
deviation Returns

Standard 
deviation Returns

Standard 
deviation

2008–
2009

1 –0.98% 2.72% –0.52% 2.17% –0.46% 0.55%

3 –0.27% 1.97% 0.07% 2.78% –0.34% –0.81%

6 –0.45% 1.90% –0.17% 2.76% –0.28% –0.86%

12 –0.73% 4.69% –0.54% 4.44% –0.19% 0.25%

15 –0.56% 5.62% 0.05% 4.80% –0.61% 0.82%

18 0.20% 4.38% 0.04% 3.38% 0.16% 1.00%

24 0.42% 4.60% 0.32% 3.41% 0.10% 1.19%

analysis shows that the contrarian strategy should be used within this two-year 
period so that not to lose a higher amount of the invested money. The table shows 
that all along the analyzed intervals losers are operating better than winners. The prior 
results indicate that the momentum strategy of buying past winners and selling past 
losers in NaSdaq oMx Riga within the specified period would result in significant 
higher return for the investor in the period of 1 to 6 months at the interval of 15 months 
considered in this study. 

The strategy of buying losers and selling winners would result in significantly higher 
returns at the interval of 12 months and at the interval of 18 to 24 months. For the 
interval analyzed, the investor will get profit from buying winners and selling loosing 
shares only in the first three months. However, in the remaining months, losers were 
stable in their returns while winners represented a spiral drop. This completely confirms 
the scientific findings of this particular strategy. The momentum strategy of buying 
past winners and selling past losers would result in significant positive return for the 
investor at the first and 18–24 month interval. The strategy of buying losers and selling 
winners would also result in positive significant returns for the remaining interval of 3 
to 15 months. 

In general, the findings have revealed that those strategies do not take place in the 
Latvian stock market as stated in the strategy statement, because at least in the period 
from the beginning of 2000 to the end of 2009, no precious tendency for this anomaly 
was noticed. In the first four years, losers were operating better than winners all the 
time; therefore, no evidence for momentum features to emerge was found. Thus, this 
totally contradicts specific strategy peculiarities. Later, in the next period (2004–end of 
2005), it was hard to investigate any consistency, as both losers and winners slogged on 
for the returns. However, there are two periods (2006–2007 and 2008–2009) that could 
definitely or likewise show some momentum and contrarian strategy in the Latvian 
stock market. Still, we can conclude that though this strategy could take place in the 
market in the short term period, it disappears in the long term. 

End of Table 4



124

J. Stankevičienė, N. Gembickaja. Market behaviour: case studies of NaSdaq OMx Baltic

Fig. 3. Graphical representation of returns received from NaSdaq oMx Riga using mo-
mentum and contrarian strategies (2000–2009 end). (Source: created by authors using data 
obtained from NaSdaq oMx Riga)

4. Conclusions

For a long time, when making financial decisions, market participants have relied on the 
notion of efficient markets and the behaviour of a rational investor. However, academ-
ics in both finance and economics gradually started discovering anomalies and types 
of behaviour that could not be explained by the theories available at the time. While 
these theories could explain certain “idealized” events, the real world proved to be a 
very messy place where market participants often behaved very unpredictably. as a 
result, the notion that such irrational behaviour exists has become controversial. There 
is extensive literature on psychology documenting that people make systematic errors 
in a way they think: they are overconfident, put too much weight on recent experience, 
etc. Their preferences may also distort reality. 

– 1.00%

0.00%

1.00%

2.00%

3.00%

1 3 6 12 15 18 24

R
et

ur
ns

Interval (in months)

2000 –2001 end

Winner

Loser

– 20.00%

– 15.00%

– 10.00%

– 5.00%

0.00%

5.00%

1 3 6 12 15 18 24

2002 –2003 end

– 0.40%
– 0.20%

0.00%
0.20%
0.40%
0.60%
0.80%
1.00%

1 3 6 12 15 18 24

2004–2005 end 

– 0.60%
– 0.40%
– 0.20%

0.00%
0.20%
0.40%
0.60%

1 3 6 12 15 18 24

2006– 2007 end

–1.50%

–1.00%

–0.50%

0.00%

0.50%

1
3

6 12 15 18 24

2008–2009 end



125

Business, Management and Education, 2012, 10(1): 110–127

The prospect theory and heuristics may further help with explaining other psycho-
logical factors affecting the process of investment decision-making and how such 
processes can lead to speculative bubbles. The prospect theory offers an alternative 
to the theory of the expected utility maximization according to which investors are 
risk averse at all levels of wealth. Heuristics, a process by which people find things 
out for themselves usually by trial and error, may help with an explanation why the 
market sometimes acts in an irrational manner, which is opposite to the model of per-
fectly informed markets. The prospect theory and heuristics help with understanding 
some of the possible factors underlying the phenomenon of speculative bubbles, 
even though they cannot alone give exhaustive answers to all the matters surround-
ing the anomaly of this market (Johnsson et al. 2002). However, a more common 
understanding of these factors and the way psychological factors may affect our 
decision-making should help with avoiding the occurrence of such anomalies and 
assist in better understanding of the periodic unpredictability of the markets.

Momentum strategies will be profitable if stock returns display a positive serial corre-
lation, whereas contrarian strategies will be profitable in case of a negative serial correla-
tion of stock returns. according to the obtained results, it could be concluded that those 
strategies do not take place in NaSdaq oMx Baltic as stated in the strategy statement, 
because at least in the period from the beginning of 2000 to the end of 2009, no precious 
tendency for this anomaly was noticed. The studies on Lithuanian, Estonian and Latvian 
markets show that though these strategies could take place in the short term period, they 
disappear in the long term. an important point is that at some intervals it was hard to 
investigate any consistency, as both losers and winners slogged on for the returns.

Many researchers have uncovered empirical regularities in the returns of the stock 
market. The strategy might benefit from the theory. Then again, the tests on the strategy 
do not always confirm the theory. If these regularities persist, investors can expect to 
achieve superior performance. Unfortunately, nature can be perverse. once an apparent 
anomaly is published, often it disappears or goes into reverse.

Empirical studies are required for testing the model regarding a large representative 
sample. We limit our conclusions to those firms and exchanges studied and the time 
period covered. Future research could extend this work thus investigating other types 
of anomalies. 

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RINKOS ELGSENA: NASDAQ OMX BALTIC ATVEJŲ TYRIMAI 

J. Stankevičienė, N. Gembickaja

Santrauka

Straipsnyje nagrinėjama rinkos elgsena. Išsamiai analizuojama rinkos dalyvių elgesio įvairovė bei 
pasireiškiantys pavyzdžiai, pasirinktos anomalijos klasifikuojamos, pateikiami pagrindiniai jų ypatumai. 
Straipsnio tikslas – ištirti ir išanalizuoti dvi anomalijų strategijas Baltijos vertybinių popierių biržoje: 
NaSdaq oMx Taline, Rygoje ir Vilniuje. Tyrimo metu atrenkamos analizei tinkamos akcijos listin-
guojamos vertybinių popierių biržoje ir tiriami akcijų prekybos rezultatai. Gauti rezultatai yra lyginami ir 
aptariami rinkų skirtumai bei ypatumai. Išnagrinėjus teorinius ir praktinius anomalijų aspektus, pateikia-
mos išvados ir siūlymai.

Reikšminiai žodžiai: rinkos elgsena, finansų psichologija, finansų rinkų anomalijos.

Jelena STANKEVIČIENĖ. Phd in Social Sciences (economics), assoc. Prof., the dean of the Faculty 
of Business Management at Vilnius Gediminas Technical University. Research interests: integrated as-
sets and liability management, decision making under risk and uncertainty, balanced scorecard systems, 
risk, liquidity and value management of financial institutions, value creation strategies.

Natalija GEMBICKAJA. MSc in Business, the Faculty of Business Management at Vilnius Gediminas 
Technical University (Lithuania). Research interests: market behaviour, behavioural finance, anomalies 
in financial markets.

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