Baltik Stock Market

Literature review

Baltic Countries Stock Exchange Market efficiency level is expected to increase constanlty as Baltic States were experiencing transition process. Eventhough Baltik Stock Market has developed for almost a decade and capitalization and number of market pariticpants had increased significanty it could be still treated as a small market. And beying a small market could be treated as a negative factor as it could be expected that market pariticpants sophistication level is lower and less value-relevant information is available in the market. From other point of view, the small size of stock market could be treated as positive factor and higher level of efficiency as information could spread and be reflected in stock prices more quickly.

As the studies show, the key sources of information on companies' stability and performance are official interim and annual financial reports announcements. When unexpected information is revealed, company's share price might change due to adjustments of investors' behavior, formed of their future expectations on company performance and their investment strategies. Investors, according to their pursued investment strategies, are interested in different aspects of information announced in financial statements therefore the movements in share price also depend on content of financial announcements. In cases share price deviates from its expected value abnormal returns could be earned by investors, where outperforming the market or seeking gain from market inefficiencies is in most investors' interest. However in case of semi-strong form of market efficiency no deviations in share price are expected after any public announcement, as share prices reflect the new information immediately.

So, here the question rises – How efficient Baltic stock exchange market is? This problem question leads to a further questions: Can investors earn abnormal returns? Are shares priced correctly?

The importance and significance of proposed research for theoretical and practical implications is apparent – no researches in Baltic states have been conducted to analyze the quarterly announcements effect on stock market prices moves, with respect to analysis of unexpected changes in financial indicators of company performance. In addition, no previous research was conducted concerning the size of abnormal returns and gap by fundamental and market price of the share in Baltic states exchange markets. Understanding investors' reaction to different financial news help to understand in what investors are most interested and were companies should put most stress while planning their activities. Results of the research will allow comparing performance of Baltic countries from the perspective of market efficiency, helping for regulators to focus on identified areas of unexpected information.

The proposed research aims to analyze the reaction of Baltic stock exchange market to quarterly financial statement announcements in the period of 2004 - 2009, with respect to announcement contents and to determine whether the market share price represented the true share value.

The specific aims of the thesis are:

* To analyze theory related with analyzed problem and identify market efficiency criteria;

* To identify, set criteria for companies to be analyzed;

* To identify the magnitude of unanticipated information in quarterly financial announcements;

H0: The abnormal returns in Baltic stock exchange market are significantly different form zero.

* To identify financial announcements content information sub-categories generating significant stock prices reactions.

* To identify the attributes, sources of misspricing;

* To name the reasons for market inefficiencies and state the recommendations to increase the efficiency of analyzed market.

For testing Baltic Stock Market efficiency evaluation the events of interest are quarterly financial announcements.

For the quarterly announcements effects on Baltic Countries stock exchange market estimation short horizon event study methodology will be used as it is mos suitable for market efficiency evaluation as indicates Fama (1991). For estimation of the real share value Discounted Free Cash Flow (DCF) valuation will be conducted. It should be noted, that even though for similar purposes usually Discounted Dividend cash flow valuation is used as more accurate valuation model Penman and Sougiannis (1996), but in case of Baltic countries it is intended to use Discounted free cash flow valuation as there Baltic Countries' companies do not implement the consistent dividend payout policies.
The sample: approximately 15 companies on Vilnius, Riga, and Tallinn stock exchanges will be analyzed (~5 from each marker, depending on compliance with sample selection criteria). Criteria for sample selection: high liquidity level, companies should be listed on the Baltic states stock exchange at least in year 2003.
For analyzing the announcement content impact on share price movement in event windows variety of financial ratios representing different company performance areas (Profitability, Efficiency, Liquidity, Leverage, Market ratios) will be analyzed (ratios to be calculated will be selected based on selection criteria such as usage in other researches, representativenes, suitability).
Data: secondary quantitative data will be used for conducting the research. Data required for the research such as daily share prices statistics, companies' quarterly announcements (financial statements), and dates of official announcements will be taken from Baltic Stock exchange NASDAQ OMX Baltic website and/or Bloomberg data base.

The sequence of the thesis is as follows: in the first section critical overview and evaluation of the theory in analyzed area will be stated. This section will lead to the explicit problem definition. The third section will provide a methodological approach (including methods employed, sample analyzed and used data. The fourth part is empirical research report, there conducted research results will be stated and analyzed with respect to raised questions and hypothesis. Afterwards in fifth part, conducted research findings will be integrated with the theory given theory in the field. And lastly, the conclusions will be drawn. And lastly, the implication for the relevant parties will be outlined and suggestion for further research given.

1.1. Stock market efficiency

The term of stock market efficiency was firstly introduced by Fama (1965). The term “efficient market”, was described as “a market where prices at every point in time represent best estimates of intrinsic values. This implies in turn that, when an intrinsic value changes, the actual price will adjust „instantaneously[1]”(p. 94). Till then by scholars it was assumed and identified, as states Fama that “the past behavior of a security‘s price is rich in information concerning its future behavior“(p. 34)., thus the understanding of the stock prices past movements could be used to predict future share prices and “in this way increase expected gains”. Other group of scholars, the theory of random walk followers argued, that “future path of the price level of a security is no more predictable than the path of a series of cumulated random numbers”. (p. 34), meaning that the stock prices changes are independent and random, thus they are not useful for predicting future share price movements. This paper and primary definition of efficient stock market was initial point for further studies of information impact on stock prices movements.

Fama further developed the notion of stock market efficiency and presented it fully revised in paper “Efficient capital markets: A review of theory and empirical work” Fama (1970). Scholar in his paper comprehensively analyses the previous stock market efficiency theories in literature and moves further to empirical researches on this theme. He starts form analysis and review of early works of random walk theory which is followed by empirical studies in this and related areas of random stock price movements. The major conclusion for testing weak form of market efficiency was indicated, as “it seems fair to say that the results are strongly in support“ (p. 414), meaning that the random walk is valid theory in practice, but it does not mean that markets are inefficient. It should be noted, that the random walk theory analysis parts is basically based on Samuelson (1965) paper on prices random fluctuation model staiting that stock prices in the market withought bias in observing and reflecting information in stock prices are randomly fluctuating.

Further more, Fama analyses and develops theory and empirical evidence on semi-strong and strong form of market efficiency. This part appeared to be basically deduced, from Roberts (1967) paper on systematic of weak and strong efficiency forms of stock markets. The conclusion Fama indicates, is that “the evidence in support of the efficient markets model is extensive, and (somewhat uniquely in economics) contradictory evidence is sparse (p. 416). It should be noted, that author indicates, that this does not mean, that “all issues are closed“. Also he notes, that the major base of work on market efficiency evidence was conducted prior the development of theoretical models.

Revised Efficient Market Hypothesis, the efficient stock market according to Fama (1970) is “a market in which prices always “fully reflect” available information” (p. 383). Also three levels of market efficiency were identified: weak, semi-strong and strong forms of market efficiency. The level of efficiency depended on the different subset of information of interest: historical stock prices, publicly available information or private information.

p. 388 The weak form of market efficiency – is defined as a market which “fully reflect” particular subsets of available information” it is expected that stock prices moves independently. Thus for this form of stock market efficiency random walk literature (the correlation between different returns in time on the same stock) and technical analysis generated gains are used.

The semi-strong form of market efficiency - is a market where are publicly available information is reflected in the stock prices. Such definition implies that investors can't expect to generate abnormal return basing their investment decisions on public information. As Fama states (1970) “semi-strong form tests on which the concern is the speed of price adjustment to other obviously publicly available information (e.g. announcements of stock splits, annual reports, new securities issues, etc.)”(p. 388). For testing this form of stock market efficiency event study methodology is used 1577 Instead of semi-strong-form tests of the adjustment of prices to public announcements, I use the now common title, event studies. (For further analysis of event studies look xx).

The strong form of market efficiency – The concern in this type of efficiency is put of “whether any investor or groups (e.g., managements of mutual funds) have monopolistic access to any information” (p. 388) which could help to generate abnormal returns. tests of whether specific investors have information not in market prices, I suggest the more descriptive title, tests for private information.

This could be interpreted, as efficient market is one, there investor can not gain abnormal return on the publicly available information.

Also it should be noted, that in this paper it was noted, that measurement of efficiency is not a testable unilaterally, as the efficiency of the market depends on the way how returns on the securities are calculated. Following such idea, later on testing the efficiency became joint tests of stock market behavior and asset pricing.

Fama (1991 ) pp. 1576 The joint-hypothesis problem is more serious. Thus, market efficiency per se is not testable. It must be tested jointly with some model of equilibrium, an asset-pricing model. This point, the theme of the 1970 review (Fama (1970b)), says that we can only test whether information is properly reflected in prices in the context of a pricing model that defines the meaning of "properly." As a result, when we find anomalous evidence on the behavior of returns, the way it should be split between market inefficiency or a bad model of market equilibrium is ambiguous.

The further development of market efficiency theory was made by Grossman (1976). In this paper informed and uninformed traders were analyzed, and it was assumed that there are different types of informed traders. The major implication of this study is that prices of the securities “perfectly aggregates their (informed) information ” (p.582) and reveal it to uninformed traders. It was proved, that uniformed investors, which just observes the stock prices in the market and do not invest anything to gain additional information can gain equally as informed traders who invest to get addition knowledge about the market.

Other valuable input to development of stock market efficiency, was done by Grossman and Stiglitz (1980). This paper could be identified as the continuation and supplementation of previously stated Grossman (1976) work. In this paper again informed and uninformed traders were analyzed and 7 conjunctures were verified. The most valuable conclusion was regarding the conjecture 3: “The higher the cost of information, the smaller percentage of informed individuals” (p. 394). This conjecture was not confirmed and it was concluded that only costless information could be revealed by the stock prices. stipulate that prices incorporate new information immediately only if transaction costs are zero.

Variety of efficiency empirical tests were done in the period of twenty years, and those researches encouraged Fama (1991) to revise Efficient Market Hypothesis. In this paper scholar analyzed most significant researches on market efficiency and added his implications. As an outcome two versions of market condition were defined (strong and weak forms of Efficient Market Hypothesis). The strong version of EMH - “security prices fully reflect all available information“ (p. 1575) was initiated by Grossman et al. (1980) major insight of zero information and trading costs. And the weaker form is stated as “prices reflect information to the point where the marginal benefits of acting on information (the profits to be made) do not exceed the marginal costs” (p.1575) (Jensen (1978)). Such definition appears to be more economically valid and as it is evidential that information and trading costs are not equal to zero thus the strong version of EMH should be false. But it should be noted, that scholar notes, that still strong version of EMH is a “clean benchmark” to evaluate the proper information and trading costs.

Even though majority of empirical studies supported EMH, but also variety of limitations of the theory was analyzed: Ball (1994) stresses the imperfection of stock markets and indicates three major anomalies. First group is “Empirical Anomalies: problems in fitting the Theory to the Data” related with excessive volatility in prices and in trading volumes, overreactions of traders and other. The second group of anomalies are “Defects in “Efficiency” as a Model of Stock Markets” concerning the assumptions of the EMH (zero trading costs, unsuccessful empirical works, exceptions and other). And the third group is “Problems in Testing Efficiency as a Model of Stock Markets” related with joint hypothesis testing (as was also noted by Fama 1970, 1991), changes in risk premiums and risk free rates.

Kothari (2001) analyzing also indicates some anomalies, such as the post announcement drift e.g. the post announcement drift, which concerns the tendency for stock prices to continue to drift after information disclosures.

Above reviewed papers do not provide information on the major determinants of the variation in stock prices, thus following consideration of market efficiency empirical studies involving information release studies is provided.

1.2. Event study methodology

Generally all analyzed studies uses the short term event studies methodology analyzing the differences between expected normal performance of the stock prices (and/or) trading volatility and actual performance of stock market surrounding the financial, economical news announcement date. If abnormal returns or trading volumes are found they are attributed to the analyzed event and abnormal performance magnitude is used as a measure for analyzed event generated information content. Usually this content is separated to good, bad and irrelevant news depending on onduced market reaction.

Event studies enable researcher to study and evaluate the effects of particular anticipated or unanticipated event on securities prices.

It should be noted that in this part reviewed papers had employed the standard classic event study scenario, which could be defined as follows: firstly the events of interest are identified then normal performance of selected variable is obtained, thirdly the abnormal component is calculated and lastly statistical significance of analyzed events is determined. The alternative way of conducting event study was proposed by Ryan and Taffler (2002). It was proposed to conduct the event study backwards: starting with identification of statistically significant variations in stock prices volatility and trading volume (having normal and abnormal performances identified) and just then move to the identification of events that generated statistically significant share price or trading volume movements. Such backward event study conduction has a benefit of capturing all value-relevant information releases are captured, as opposed to the classical procedure where not all relevant events could be selected for consideration. For conduction of proposed research both methods will be used to verify the value-relevance of quarterly reports announcements. (For more detailed explanation of event study methodology see XX section).

Event studies let to measure “the magnitude of abnormal performance” (p. 4) Kothari at al. (2006) generated by some events (corporate information announcements, stock splits, ..). The ability to identify nonzero abnormal returns after some information releases let to evaluate stock market efficiency and makes event study methodology the major tool in investigating efficiency level of the market. The superiority of event study was also highlighted by Fama (1991), ho indicated “cleanest evidence on market-efficiency comes from event studies” p. 1607. If systematic abnormal returns are identified it is concluded, that the market is inefficient, but as it was noted, the test of stock market efficiency is treated as a joint test of market efficiency and correct asset pricing. Meaning that inefficiency could be caused either by inefficiency of the market or by incorrect definition of intrinsic asset value. As a major toll to increase the credibility of stock market efficiency evaluation event studies are used to reduce possibility of deceptive conclusions. In regard to the same issue Fama (1991) argues for event studies as the best tool for testing market efficiency: “they (event studies) come closest to allowing a break between market efficiency and equilibrium pricing issues, event studies give the most direct evidence on efficiency” (p. 1577).

The relation of event studies to tests of market efficiency receives considerable attention in Fama (1991), and in recent summaries of long-horizon tests in Kothari and Warner (1997) and Fama (1998). Smith (1986) presents reviews of event studies of financing decisions. Recently, Kothari (2001) reviews event studies in the accounting literature. Kothari and Warner (2004)

The first event study (analysis of nominal price changes at the time stock split) was conducted by Dolley (1933) . But the first event study having the same methodological structure as it is used in nowadays was conducted by Fama, Fisher, Jensen and Roll (1969). It should be noted, that Ball and Brown (1968) in fact were the first to publish it. Fama et al. (1969) paper was also concerned with stock splits as Dolley (1993), but the difference is …. . Fama et al. (1969) in particular were analyzing the stock prices reaction to stock splits and research to what extend stock splits and other variables influences changes in returns. It should be noted, that monthly stock prices data was used. As indicates Fama et al (1969) it was assumed by scholars that stock splits should be treated as good news for investors, as dramatic increase in expected dividend payment arises before the announcement of the stock split. But the results showed otherwise - the abnormal returns at the time of stock split were almost zero. It should be noted, that abnormal returns were captured few before the actual stock split, but this could be explained by the fact that the stocks splits were performed at the periods of “boom” Fama eta al. (1969) periods (p. 11). After the information on the split and dividend changes were observed and properly considered by the market at the stock split by it self do not initiate any value-relevant stock price movements. This result of prices aggregating stock split and further dividend performance information quickly was with accordance with efficient market hypothesis.

Further more analysis of short time horizon effects surrounding corporate information release is very valuable for understanding market participants' behavior and expectations related with particular company. Also, evaluation of reaction magnitude to particular news is helpful to managers for understanding corporate decisions role.

Event studies in accounting field were started by Ball et al. (1968) analysis of Earnings announcements content and timing. For the analysis only net annual earnings were taken, event study was employed two models of expected earnings forecasting (regression and naïve models) and then mismatching real and forecasted earnings expectations generated reactions were analyzed. Scholars find out that “accounting income numbers capture about half of the net effect of all information available thought 12 months preceding their release” (p. 176). And only around 20 per cent of annual earning announcement month abnormal stock price performance could by explained annual earning announcement. This could be explained by the fact that final annual earning number contains previously released quarterly earnings announcements and analysts provided earnings expectations. The valuable insight of the research is not all information is valuable, and not all new information is value-relevant - only new and different then forecasted or known annual earnings information is valuable. As the weak part of this work narrow scope of analysis, monthly data employed and other assumptions used.

The information content of public disclosures could be observed through stock market reactions and trading volume changes around the date of announcement. Beaver (1968), Ball and Brown (1968), Morse (1981) - MORSE, D.H., (1981), Price and trading volume reaction surrounding earnings announcements: A closer examination, Journal of Accounting Research, 19, (Autumn), 247-258, and Bamber and Cheon (1995) BAMBER, L.S. and CHEON, Y.S. (1995), Differential price and volume reactions to accounting earnings announcements, The accounting review, 70, 3, 417-441 argue that earnings announcements accompanied by high trading volumes and abnormal returns around the announcement window convey more information to investors than announcements which generate low trading volumes and insignificant stock returns.

Empirical studies in accounting field were also enriched by Barber and Lyon (1996) by analysis of accounting-based methods used for abnormal operational performance determination employed in event. It should be noted that they already used daily stock return as proposed by Brown and Warner (1985). The major contribution to event studies literature was that scholars indicated that while constructing sample of companies to be researched “unusually well or poorly” performing companies should not be included in the sample as such companies lead to miss specified tests' statistics.

Already mentioned Brown et al. (1985) researched what effect has daily stock returns on the firm specific events studies' methodologies compared to monthly returns as it was commonly used by scholars. The major focus was on type I error (falls rejection of null hypothesis of zero abnormal performance) and the power of different tests. This paper had also made valuable input to empirical event studies by detailed analysis and suggestions how to overcome problems related with daily returns. For estimation stock return performance on event window 3 procedures were used: mean adjusted returns, Market adjusted returns, OLS. And the major conclusions derived were that „little difference in the power of alternative procedures“ (p.12) were identified between the methods, also tests power is larger using daily data. It could be noted, that OLS and market adjusted returns methods are superior than mean adjusted returns model in cases of event-date clustering. Sensitivity analysis also showed that no significant difference were identified and specifications of tests are not altered significantly (p.14). Scholars also showed, that longer than (-5, +5) event widows lead to decrease.

Other group of studies employing event studies was concerned with stock returns variances and trading volume volatility generated by some events. First one to show the statistically significant fluctuations of returns and trading volume during event widows by analyzing quarterly earnings announcements was Beaver (1968). Later his results were verified by Patell (1976).

Harrington and Shrider (2002) analyses the variances induced by event and biases of using inappropriate test procedures to show that non-zero mean abnormal returns could be generated for analysis of different companies.

The event study methodology literature does not provide one right methodological approach to conduct event study. But varieties of studies are performed to identify the most reliable and powerful attributes of event study and provides event studies history, methods valuation and explanations on usage. MacKinlay (1997) paper provides explicit but concise explanation of event studies methodology procedure, overviews models used for normal stock performance on event windows, provides, guidelines of usage of statistical test by providing an example of event study on quarterly earnings announcements.

Cambel, Lo and MacKinlay (1997) provides a detailed and precise graduate-level book on econometrics of financial modeling.

Johnson (1998) contributes to the event studies' methodology by providing graphical illustration of for selecting length and position of event window (“announcement period”), length of estimation window (“comparison period”) and the size of the sample.

It should be mentioned, that major part of event studies are performed and analyzed in US or other big and well developed stock markets. This raised the question gow efective and suitable is this method in small (thinly traded[2]) stock markets. This issue was analyzed by Bartholdy, Olson and Peare (2006) in paper „Conducting event studies on a small stock exchange“. In this paper Bartholdy et al. analyze Copenhagen stock exchange and conclude, that event studies can be performed in the small stock markets, and results generated are meaningful. Also it was identified, that adjustments should me made to the thinly traded stocks to obtain abnormal returns and also it should not be expected to detect abnormal return lower that 1 - 2% . In addition it was also identified, than non parametric test in non-normal stock return market are more suitable for abnormal performance detection than parametric (“except in the cases of event induced variance or unknown event date” p. 18).

Trading volume was researched by Campbell and Wasley (1996).

1.3. Researches in Baltics

Market efficiency, in particular information disclosure and abnormal returns are widely discussed worldwide, however research in Baltic states it could be conducted in more depth as in Baltic Countries analysis of market efficiency started only in 2002.

Kvedaras and Basdevant (2002), Levisauskaite, and Juras (2002), Milieska (2004) were the main researchers in the field of market efficiency in Baltic states indicating that Lithuanian stock market is of a inefficient or weak efficiency form.

Analysis of market efficiency started with Kvedaras at al. (2002) paper “Testing the Efficiency of Emerging markets: the case of Baltic States”. To identify weather Baltic stock market is of weak form of efficiency or inefficient time varying autocorrelations analysis for the period of 1996 – 2002 was used. Baltic countries indexes were analyzed and the results of the tests indicated “weak-form efficiency in the Estonian and Lithuanian capital markets“ and Latvian market was found to be „not developed enough to ensure even the nearly weak-form efficiency”( p. 14).

In compliance with mentioned previous work Levisauskaite at al. (2002) papers purpose was to verify weak-form of Baltic stock markets' efficiency. For this purpose the autocorrelation of daily prices log changes of the stocks were used. All stocks included in the Baltic market indexes were employed and the results of this research indicated, that “signs of weak-form efficiency can be detected in all 3 Baltic States stock markets”( p. 7). but authors conclude, that hypothesis of weak for of efficiency can not be accepted.

Later on Milieska (2004) was also verifying the weak for of Lithuanian market efficiency using Lithuanian stock market indexes. The results indicate that Lithuanian stock market in the period of 2001 – 2004 year is of a strengthening weak-efficiency form.

Only few studies concerning public announcements influence on Baltic countries market as indicator of market's efficiency were conducted. Kiete and Uloza (2005), Laidrroo (2006), Laidroo (2008) and Stasiulis (2009) employ short-horizon event studies methodology.

Kiete and Uloza (2005) [3]analyzed Lithuanian and Latvian stock market efficiency for period of 2001 – 2004 by analyzing earnings announcement. The improvement of Lithuanian stock market efficiency was identified, the market was concluded to be of semi-strong form of market efficiency. Latvian stock market was concluded to be inefficient. The results of researches indicates, that that there is space for abnormal returns to be earned. And issue related with abnormal returns and difference between real and market prices of the stock are the attributes, which explain the deviations or let to predict them.

Laidroo (2008) analyzed Baltic stock market returns and trading volumes changes generated by public announcements for the period of 2001 – 2005. As the sample of companies to analyze all companies listed on the Baltic stock market were chosen. Scholar used reversed event study methodology Ryan and Tafler (2002) in this all statistically significant deviations from normal returns of trading volume were analyzed and matched with public announcements. For the normal performance of returns during the event windows the constant mean return, market adjusted and market models were used and the real returns were calculated as lumped returns. The research led to the conclusion of abnormal returns is explained by official announcement by 22-37% (as most significant financial announcements were excluded). The implications from L. Laidroo paper for the further analysis: financial announcements are the most significant sources of information with respect to other public announcements, therefore the effects of financial announcements content on changes in share prices should be analyzed in more depth.

Other significant study for market efficiency level evaluation was conducted by Stasiulis (2009). The paper researched market participants' reaction to corporate earnings announcements in 9 CEE markets with respect to earnings announcements in the period 2005 – 2008. The sample of the companies analyzed was selected from primary and secondary companies' listings (major selection criteria was active trading and data availability). For the calculation of normal returns on the event windows market model (employing Ordinary Least Square OLS method) and for the estimation of market returns capitalization weighted and equally weighted portfolios were calculated for different countries. OLS method is usually used if normality of the returns data could be assumed but it appeared otherwise (p. 20) thus variety of adjustments needed to be made. Even though reasonable adjustments were made (logarithms) but..

For the abnormal returns significance evaluation Pattell's standardized test were used, but such a method do not distinguish between good or bad news. In order to distinguish the content of the announcement 1 per cent deviation form estimated normal return was used[4]. It should be noted, that such approach do not let to “make the inferences about the event day cannot be made and the causal effect between the announced information and the price change cannot be established” (p.16). In addition, the Z-test is used for the same purpose of abnormal return evaluation which is applied separately on good and bad news, but this method underperforms compared to other. In the paper also it is analyzed weather it is possible to earn abnormal returns by employing some trading strategies.

The results of the study captured statistically significant abnormal returns surrounding the event and proved that „earnings announcements in all of the markets do convey information“ p. 24 emphasizing importance of earning announcements for abnormal returns. But the major conclusion of the paper was that no trading strategy analyzed could generated abnormal gains after the announcement indicating of the semi-strong form of market efficiency in CEE countries (except Slovenia and Latvia).

It should be noted, that in this paper where no proper distinction between good and band news of analyzed events were. Also no distinction were made concerning the differences of the companies.

Jarmalaite Pritchard (2002) conducted an accounting data and stock market returns relationship analysis in the Baltic States stock market for the period of 1995 – 2000. To evaluate the accounting numbers relevance for predicting the stock market returns long-term association studies were used to evaluate all companies stocks listed on primary and secondary listings of securities. The implications from this association study are that it was empirically proved, that “stock prices lead accounting earnings in Baltic States” (p.27) and share prices contain value-relevant information on future earnings of the company. Also the lowest relation between accounting numbers and returns was found in Lithuania market, then – Latvian market and the highest value-adding relation was found in Estonia. It could be also concluded, that Lithuanian stock market was the most efficient as accounting numbers carried the least value-relevant information compared to Latvia and Estonia.

Mihailov and Linowski (2002) analyzed Latvian stock market in the period of 1996-2000 using technical analysis techniques and concluded that stock market „might be (partially) inefficient“ (p.7).

Bistrova and Lace (2009) enriched Baltic Stock Market empirical work by analysis of usefulness of fundamental analysis in analyzed market for the period of 2000 – 2008. The results showed that neither of analyzed ratios[5] were adding value - fundamental analysis do not help to improve the performance of the portfolio. These results also signal that Baltic Stock Market was higher than weak-form of market efficiency.

Januskevicius M. (2003) verified the weak form of market efficiency for the Lithuanian Stock Market for the period of 1999-2000. The distinction of this study was used methodology of Neural Networks application for trading simulations. As some abnormal returns were gained it was concluded, that the stock market was inefficient.

M. Dubnikovas, V. Moskaliova and S.Girdzijauskas (2009) analysis of share price bubbles in Baltic countries for the period of 2000 – 2009. They indicate thatm the Baltic countries stock markets experienced stock market creations and bursts in the year of 2007. They indicate that for the share prices bubble formation two conditions were required: fundamental (the lack of capital to grow) and psychological (the propensity to generate money). The fact that the bubble created, means that the share prices were overvalued, due to psychological factors of the investors.

Less attention in Baltic stock market were given to different announcements content analysis.Literature

2. RESEARCH PROBLEM DEFINITION

A problem definition should be functional so that research questions and research methods can be easily deducted. Students should describe the previous approaches to the problem in the literature, identify the missing “gaps” in the current state of knowledge and explain why their approach in solving the problem is more effective. The problem definition should be relevant to the Thesis topic discussed. The research question(s) and/or research hypotheses should be formulated clearly and precisely.

From theoretical point of view Fama (1970)[6], indicates three levels of market efficiency: weak, semi-strong and strong form of market efficiency. Market efficiency, in particular information disclosure and abnormal returns are widely discussed worldwide, however research in Baltic states could be conducted in more depth.

The importance and significance of proposed research for theoretical and practical implications is apparent – no researches in Baltic states have been conducted to analyze the quarterly announcements effect on stock market prices moves, with respect to analysis of unexpected changes in financial indicators of company performance. In addition, no previous research was conducted concerning the size of abnormal returns and gap by fundamental and market price of the share in Baltic states exchange markets. Understanding investors' reaction to different financial news help to understand in what investors are most interested and were companies should put most stress while planning their activities. Results of the research will allow comparing performance of Baltic countries from the perspective of market efficiency, helping for regulators to focus on identified areas of unexpected information.

This study contributes to the existing literature in two respects. First, we analize the information content of EAs in a small stock market where the accounting standards are congruent with the International Accounting Standards (IAS). The manner in which small stock markets react to earnings announcements is interesting, since there are several aspects where it is likely that small and large stock markets differ with respect to their information environment.

Grossman and Sshilits? pp. 403 -404 In general the price system does not reveal all the information about “the true value” of a risky asset.

With regard to pre-announcement

information it can be argued that the smaller size leads to a less developed market with less investor sophistication and therefore less pre-announcement information. On the other hand, one could argue that the smaller size leads to a more transparent market with more pre-announcement information. Additionally, it is possible that the speed with which the new information is incorporated into prices is affected by the size of the stock market.

Louhichi W. (2008) Adjustment of stock prices to earnings announcements: evidence from Euronext Paris, Review of Accounting and Finance Vol. 7 No. 1, p. 102- 115

Huang X. (2004) China Stock Price Reactions to Financial Announcements: Evidence from Segmented Markets, Managerial Finance Vol. 30 Number 3 2004 p. 62 – 73

Ryan P. and Taffler R. J. (2002) What firm-specific news releases drive economically significant stock returns and trading volumes? Paper read at the European Financial Management Association 2002 Annual Meeting June 26-29 Retreived on 2010 01 10 form http://papers.ssrn.com/sol3/papers.cfm?abstract_id=314880

Sponholtz C. (2008) The information content of earnings announcements in Denmark, Internationa,l Journal of Managerial Finance Vol. 4 No. 1, pp. 4-36

Fama E. F. (1965)The Behavior of Stock-Market Prices, The Journal of Business, Vol. 38, No. 1. (Jan., 1965), pp. 34-105. Retreived on 2010 february 02 from http://links.jstor.org/sici?sici=0021-9398%28196501%2938%3A1%3C34%3ATBOSP%3E2.0.CO%3B2-6

Samuelson, P. A. (1965). Proof that Properly Anticipated Prices Fluctuate Randomly. Industrial Management Review, 6,pp 41–49. Roberts, H. (1967). Statistical versus clinical prediction of the stock market. Unpublished manuscript.

Grossman S. J. And Stiglitz J. E. (1980) On the imposibility of the efficient markets, The American Economic review, Volume 70, Issue 3, pp 393- 408

Fama, E. F. (1991). Efficient capital markets: II. The Journal of Finance, 46(5), 1575–1617.

Ball R. and Brown P. (1968), An empirical evaluation of accounting income numbers, Journal of Accounting Research, Vol. 6 No. 2, pp. 159-78.

Kothari, S., & Warner, J. B. (2004). The Econometrics of Event Studies. Retrieved December 9, 2008, from SSRN database.

Fama, E. F., Fisher, L., Jensen, M., & Roll, R. (1969). The adjustment of stock prices to new information. International Economic Review, Vol 10, No. 1. (FEB., 1969) pp 1-21.

Roberts, H. (1967). Statistical versus clinical prediction of the stock market. Unpublished Manuscript

Grossman S. (1976) On the Efficiency of Competitive Stock Markets Where Trades Have Diverse Information, The Journal of Finance, Vol. 31, No. 2, Papers and Proceedings of the Thirty-Fourth Annual Meeting of the American Finance Association Dallas, Texas December 28-30, 1975 (May, 1976), pp. 573-585

Kothari S.P. (2001) Capital markets research in accounting, Barber B. M. and Lyon J. D. (1996) Detecting abnormal operating performance: The empirical power and specification of test statistics, Journal of Financial Economics 41, p. 359-399

Brown S.J. and Warner J. B. (1985) Using daily stock returns: The case of event study, Journal of Financial Economics, 14, p. 3-31, North-Holand

Patell, J. (1976). Corporate forecasts of earnings per share and stock price behaviour: Empirical tests. Journal of Accounting Research, 14, 246–276.

Beaver, W. (1968). The information content of annual earnings announcements. Journal of Accounting Research, Supplement, Vol. 6 No.3, pp.67-93.

Campbell J. Y., Lo A.W., and MacKinlay A.C. (1997) The Econometrics of Financial Markets

Bartholdy, J., Olson, D., Peare, P. (2006), „Conducting event studies on a small stock exchange“, European Journal of Finance, Vol. 13 No.3, pp.227-52., retreived from http://ssrn.com/abstract=710982 on 2010 february 12

Roberts, H. (1967). Statistical versus clinical prediction of the stock market. Unpublished Manuscript

Grossman S. (1976) On the Efficiency of Competitive Stock Markets Where Trades Have Diverse Information, The Journal of Finance, Vol. 31, No. 2, Papers and Proceedings of the Thirty-Fourth Annual Meeting of the American Finance Association Dallas, Texas December 28-30, 1975 (May, 1976), pp. 573-585

Jarmalaite Pritchard N. (2002) The Relationship between Accounting Numbers and Returns in the Baltic Stock Markets, CERT, Heriot-Watt University, Discussion Paper 2002/06

Mihailov T. and Linowski D. (2002) Testing Efficiency of the Latvian Stock Market: An Evolutionary Perspective, unpublished research paper retreived on 2010 february 13, from http://ssrn.com/abstract=302285

Bistrova J. And Lace N. (2009) Relevance of fundamanetal analysis on the Baltic equity market, Economics and Management, ISSN 1822-6515, p. 132- 137 retreived from http://www.ktu.lt/lt/mokslas/zurnalai/ekovad/14/1822-6515-2009-132.pdf

Januskevicius M. (2003)Testing Stock Market Efficiency Using Neural netvorks: case of Lithuania, SSE Riga Working Papers 2003: 17 (52)

Laidroo L. (2008) Public Announcement‘s Relevance, Quality and Determinants on Tallinn, Riga and Vilnius Stock Exchanges, Tallinn University of Technology, School of Economics and Business Administration: Department of Economics, Unpubilshed doctoral thesis

M. Dubnikovas, V. Moskaliova and S.Girdzijauskas (2009) Analysis of the Share Price Bubbles in the Baltic countries , 119 – 129 WitoldAbramowicz and DominikFlejter: Business information systems workshops, Berlin: Springer – Verlag Berlin Heidelberg

[1] „Instantaneously means, among other things, that the actual price will initially overshoot the new intrinsic value as often as it will undershoot it“.

[2] Stocks are not traded on every day basis

[3] K.Kiete, G. Uloza (2005) The information efficiency of the stock markets in Lithuania and Latvia, SSE Riga Working Papers, Vol. 75 No.7, pp.1-53

[4] Meaning that if abnormal returns were larger by 1 percent then the announcement was treated as “god” and bad – otherwise.

[5] ROE, equity ratio, ROIC, net debt to assets, PE, PB

[6] Efficient Market Hypothesis

Please be aware that the free essay that you were just reading was not written by us. This essay, and all of the others available to view on the website, were provided to us by students in exchange for services that we offer. This relationship helps our students to get an even better deal while also contributing to the biggest free essay resource in the UK!