IZVIRNI ZNANSTVENI ČLANEK - ORIGINAL SCIENTIFIC PAPER RELATION OF THE INTRINSIC VALUE OF COMPANIES AND SHARE PRICES ON THE STOCK EXCHANGES OF CENTRAL AND EASTERN EUROPEAN TRANSITION COUNTRIES Povezanost med notranjo vrednostjo podjetij in ceno njihovih delnic na borzah vrednostnih papirjev tranzicijskih držav srednje in vzhodne Evrope Prejeto/Revised: December 2012 Popravi jeno/Revised: Marec 2013 Sprejeto/Accepted: Marec 2013 Džafer Alibegovic University of Sarajevo, School of Economics and Business dzafer.alibegovic@efsa.unsa.ba Abstract This paper examines the relationship of the intrinsic value of companies and the price of their shares on stock exchanges. The research is based on an analysis of indicators of intrinsic values and market price trends among 37 companies from 7 stock exchanges in central and eastern European transition countries. Although a number of studies have confirmed a strong relationship between the intrinsic value of the company and the market price of shares on the stock markets of developed countries, this paper finds that such relationships in the case of companies from transition stock exchanges do not exist. Rather, a direct and very strong relationship exists among the share market price trends and among the leading market indexes of the observed stock exchanges. Keywords: intrinsic value, market price, stock exchanges, stock index, central and eastern Europe Povzetek Članek proučuje povezanost med notranjo vrednostjo podjetij in ceno njihovih delnic na borzah vrednostnih papirjev. Raziskava temelji na povezanosti med indikatorji notranjih vrednosti in trendi borznih vrednosti 37 podjetij s sedmih borz vrednostnih papirjev v tranzicijskih državah srednje in vzhodne Evrope. Čeprav številne raziskave potrjujejo močno povezanost med notranjo vrednostjo podjetja in borzno vrednostjo na borzah vrednostnih papirjev v razvitih državah, pričujoča raziskava kaže, da v primeru podjetij s tranzicijskih borz vrednostnih papirjev tovrstne povezave ne obstajajo. Obstaja pa neposredna in zelo močna povezava med trendi borznih vrednosti delnic ter med vodilnimi borznimi indeksi proučevanih borz vrednostnih papirjev. Ključne besede: notranja vrednost, borzna vrednost, borza vrednostnih papirjev, borzni indeks, srednja in vzhodna Evropa 1 Introduction Questions about how much shares traded on the stock exchange are really worth or opinions that certain shares are over- or underestimated are quite often heard not only among professional investors or intermediaries, but also within the wider investment public. Such questions or opinions lead to several conclusions—namely, that there is an intrinsic value of the company (and its shares), that this value is different than market value of the shares, and that there is a relationship between the intrinsic and the market value of the shares. The concept of intrinsic value was introduced into financial analyses by Graham and Dodd nearly 80 years ago, who defined intrinsic value as "the value justified by the facts, e.g., the assets, earnings, dividends, definite prospects, as distinct, let us rrr? Naše gospodarstvo / Our Economy Vol. 59, No. 3-4, 2013 pp. 3-13 DOI: 10.7549/ourecon.2013.3-4.01 UDK: 336.71 (4-191.2)(4-ll) JEL: G14 say, from market quotalions established by artificial manipulation or disturbed by psychological excesses" (1940, p. 20). These authors sought to separate a share's intrinsic value from its market pricc. placing it closcr to the value of the company's assets or business performance. The concepts of intrinsic value (separate and different from the market value) led to different thcorctical approaches and practical models of financial analysis as well as various investment strategies, directed to one or another aspect of value, to a lesser or greater extent. However, regardless of the acceptance of one or the other value (i.e.. intrinsic or market) as a reference in the valuation or choice of analytical instruments and investment strategics, the question of the relationship between the intrinsic value and market prices continues to garner attention. For the purpose of clarity, in this paper vvc will use the terms intrinsic value and market price in accordance with the basic definitions from Barron's Dictionary of Finance and Investment Terms, which defines the former as value "determined by applying data inputs to a valuation theory7 or model" and the latter as "last reported pricc at which a security was sold on an exchange." In terms of intrinsic value, "the resulting value is comparable to the prevailing market price" (Dovvnes & Goodman. 1998. pp. 293, 351). 2 Relationship of the Intrinsic Value of Companies and Share Prices on the Stock Exchanges in Developed Markets Many studies have examined the relationship between the intrinsic value of companies and the market prices of tlicir shares in developed financial markets. These studies have generally approached the problem from one of two sides: exploring whether, and to what extent, the market value is determined by the intrinsic value of the company or examining the degree of efficiency of the stock market. The first approach is typically motivated by a desire for confirmation (or refutation, of course) of some practical analytical model: motives for using the sccond approach in research stem from the confirmation (and again, possible refutation) of efficient markets hypothesis. The two approaches arc not mutually exclusive: they arc. in fact, complementary. More direct relationships between the intrinsic and the market value of the company witnesses a greater degree of market efficiency, while the absolute determination of the market price by the intrinsic value would actually provide fundamental evidence of a perfectly efficient market. Lee. Myers, and Swaminathan (1997) structured their research of the relationship between intrinsic value and market price in an extremely interesting way. The authors used a valuation model of future earnings as a measure of intrinsic value for 30 companies whose shares arc included in the DJIA index. They established the statistical relationship of this indicator with the movement of tlie index. At the same time, as a sort of dclachmcnt from the thcorctical literature. they did not expect equality between intrinsic values and market prices. By modeling the relationship between the intrinsic value and share price in the time series as a co -integrated system, they concluded that the pricc and value of the company arc long-term convcrgcnts. but this docs not necessarily give the possibility to forecast the movement of sliarc prices in the future. Testing the relationship described, the authors concludcd that traditional indicators of market value (book to market value, earnings to price, dividends to pricc) from the previous period lwve little value in forecasting future pricc movements of shares, while the ratio of intrinsic value and price (with the intrinsic value based on the present value of future earnings available) has statistically confirmed relevance in forecasting future prices. Brainard. Shoven, and Shapiro (1990). based on theoretical foundations from James Tobin's research, dealt with the empirical links between the fundamental return on a company's physical assets and market return on financial claims to those assets (company's securities). The research sought to determine whether the market return on the securities of a certain company react more to changes in the aggregate intrinsic value of the company or to changes in the market value. The authors further examined the perception of risk and the impact of risk on the establishment of the pricc of financial instruments, emphasizing the issue of what kind of risk lias a greater impact on the price: fundamental or market risk. They conducted their research on a sample of 191 companies from various industrial sectors (not including the oil industry), using the financial reports and stock market reports from 1962 to 1985. The results confirmed two hypotheses—namely, a positive relationship between the intrinsic value of companies and market prices of their financial instruments and (what is especially interesting) the dominant influence of fundamental risk on the price of the securities in the long term. In addition to papers thai investigate the relationship between intrinsic value and the market value of individual companies, among which two of the works have been presented, a number of studies have focuscd primarily on assessing the degree of market efficiency. Demonstrating a high level of efficiency of the equity market, these authors have indirectly demonstrated the high level of positive correlation of the fundamental parameters of the company's value and the market price of its shares. Barsky and Dc Long (1993) recognized the current (paid) andlhc estimated dividend as key factors that influence the market price of the shares. Using the model of the present value of dividends as the basis for assessing the internal value of the company, the authors analyzed the Standard & Poor's Composite index for 1880-1991. comparing the index trend to the movement of the dividends of companies in the same index. In addition to finding a high level of correlation between the dividend, as a parameter of the fundamental value, and the market pricc of shares, the authors suggested a very interesting and important conclusion: The stock market index fluctuates more widely than the value of div idends paid, not less, which—according to the authors—means that investors in (lie capilal markets do nol base llicir decisions on the assumption of the constant growth of dividends. Lehmann (1991) presented a similar view in his systematized presentation of the works of other authors who have studied and confirmed the efficient market hypothesis. Important, for this paper, is the review of Samuclson's paper (1965). entitled "Proof That Properly Anticipated Prices Fluctuate Randomly." because Samuclson confirmed market efficiency in an interesting way: through' the negation of inefficiency . In fact, as the author states, "for many, the proposition that returns arc unpredictable is synonymous with market efficiency" (Lehmann. 1991. p. 8). If the expected returns were predictable or constant, it would mean that investors can predict the price mov ements of securities and therefore achieve returns on investment that are different from the market return. Such investors would be able to "beat" the market, which is excluded according to the efficient market hypothesis. Samuclson as well as Barsky and De Long asserted that the assumption of a constant cxpcctcd return (or predictable returns, in general) is nol realistic, except in the short term in daily or weekly trading, when the expected return can be considered constant. In this case, according to Samuclson's model, it is not necessary to make an objective assessment of the intrinsic value of the company for comparisons to the market price of shares. McGrattan and Prcscott (2001) provided arguments in favor of the efficient market hypothesis, in a particularly interesting and even extravagant way. These authors also proved market efficiency by disproving market inefficiency; however, unlike others, they used the example of the best known and most drastic crisis of the U.S. equity market in its history: the crash of the New York Stock Exchange in 1929. The overpricing of securities traded at the NYSE is commonly accepted as one of the key causes of the crash and the drastic fall in share prices. This thesis, which actually represents a dramatic example of the inefficiency of the market, has been constantly present ever since. However, just three days before the collapse of the NYSE. Irving Fisher—one of the most important economists of that time (and one of the most important authors in the domain of economic theory in general)—argued that the majority of shares is not overpriced, but that share prices indeed "readied a permanently high level" and that at the same level will remain. McGrattan and Prcscott (2001) claimed that Fisher was right. Following Fisher's claims of stable and strong fundamental indicators of companies (such as disclosed earnings, the high level of investment in research and other forms of intangible capilal. favorable industrial environment), McGrattan and Prescott (2001) reevaluated the intrinsic value of companies from NYSE in 1929 and compared the results with the market value of the same companies. They concluded that shares on the NYSE were not overpriced, but rather undcrpriccd. even at the peak in October 1929. In assessing the market value, the authors used the data for the leading 135 companies traded on the NYSE in August 1929 and for the 50 companies in the Standard & Poor's index. As a measure of market value, they used market capitalization (the ratio of capitalization to the U.S. GNP and the ratio of capitalization to the actual company earnings after taxes). As a measure of fundamental value they used the value of productive assets of the company, while they avoided the use of earnings as a measure of value as earnings were a reference point for a comparison. Research findings have shown that, at the time of the NYSE crash, "a conservative estimate for the market value of U.S. corporations |was| no greater than 19 times corporate earnings (or 1.67 times GNP). A conservative estimate for the fundamental value of U.S. corporations |was| no smaller than 20 times corporate earnings (or 1.78 limes GNP)" (McGrattan & Prcscott. 2001. pp. 17-18). These data suggest that the companies at that time were not overpriced; on the contrary, they were slightly undcrpriccd. According to this conclusion, the market has nol been inefficient: the irrational behavior of investors in the market lias actually led to anomalies, vvithcataslropliic consequences. 3 Research Methodology Research similar to that described in the previous chapter is relatively rare in the financial markets of transition countries of Central and Eastern Europe. For this reason, this paper examines the relationship between the intrinsic value and market price of the shares of companies traded on the slock exchanges in Warsaw. Prague, Budapest, Ljubljana. Zagreb. Sarajevo, and Banjaluka. These exchanges were selected for this study because they are in the same region, bul in different stages of development due nol only to the diffcrcnl stages of transition of socio-economic systems, but also various business policies of exchanges. For the purposes of this paper, we selected companies whose shares from 2005 to 2009 dominated traffic on the chosen exchanges, so they collectively realized more than a half share in the composition of the main market index (if there is such a set of shares) or the shares lhal were retained in the index throughout the considered period. An overview of companies whose shares make up the sample for the research, with the percentage of participation in the composition of the indexes, is included in the Appendix. The study focused on the period of active trading in the stock markets with significanl changcs in share prices of observed companies. The goal of the research is to investigate the relationship between the trends of intrinsic value of the companies (changcs or the absence of changcs in key parameters of intrinsic value) and the trends of the market price of the shares. Therefore, as a reference period of study, we selected the five-year period from 2005 to 2009. Before and after this period, all observed exchanges were (more or less) trcndlcss. From the point of technical analysis, this situation is inconclusive. As a measure of the intrinsic value of a company, we selected 20 ratio analysis indicators, grouped into four key NG, ■ . 3-4/2013 IA'IKN /NAM UVIKI :IAN /O NA ■:! NI I ; ivVfks categories (i.e.. liquidity, solvency, operational efficiency, and profitability), as follows1: - Liquidity indicators: Current assets Current ratio = Quick ratio = Cash ratio = Current laibilitics Current assets - Inventory Current laibilities Cash + Short term marketable securities Working capital productivity Current laibilitics Annual sales (1) (2) (3) Sales to current assets = - Solvency indicators: Debt Working capital (4) Annual sales Current assets (5) Debt/Equity = Equity Debt to Assets ratio = Total debt Current assets (6) (7) Funded _ Stockholders' equity + Long term debt capital ratio Fixed assets (8) Retained earnings to = Retained earnings Stockholders'equity Stockholders'equity (9) Interest coverage - EBIT Interest (10) Operational efficiency indicators: Sales to Annualized net sales Fixed assets Total fixed assets prior to accumulated depreciation (11) Sales to Annualized net sales Working capital Account receivable + Inventory7 - Accounts pay vaablc (12) Sales to Equity = Investment Annual net sales Equity Sales turnover Equity + Long trcrin liabilities (13) (14) 1 Formulas of ratio analysis indicators are taken from Bragg (2002) and Helton (2001). Net worth = Total assets - Total liabilities - Prcffcrcd stock dividends Total outstanding common shares (15) - Profitability indicators: Gross profit (%) = Revenue - (overhead + Direct materials + Direct labour) Revenue Operat. profit (%) = Sales - (Cost to goods sold + ,, _ sales, general, admin, expenses Sales (16) (17) Return to assets cmplovcd = ls,et Proflt F • Total assets (18) Return to equity = Net profit Equity Comon stock price EPS 0») (20) The value of all indicators for all years of the observed period and for all observ ed companies was calculated; then the average value of these indicators with equal weights for each of them was also calculated, according to the following formula: ARAI = 0.05 x x, + 0.05 x x, + 0.05 x x, + 0.05 x x, + 0.05 x x, + 0.05 x-L + o.05 x — + 0,05 x x, + x„ x7 0.05 x x, + 0.05 x x„, + 0.05 x xn + 0.05 x xI2 + 0.05 x x„ + 0.05 x x,., + 0.05 x x15 + 0.05 x Xw + 0.05 x xr + 0.05 x x,s + 0.05 x x„ + 0,05 x J- x,„ (21): where: x, is the current ratio, x, is the quick ratio, x, is the cash ratio. x, is the working capital productivity ratio, x, is the salcs-to-current assets ratio. x6 is the dcbt-to-cquity ratio, x- is the debt-to-assets ratio. xx is the funded capital ratio. Xp is the retained earnings to stockholder's equity ratio. x,„ is the interest coverage ratio, x|, is the sales-to-fixed assets ratio, xJ2 is the salcs-to-working capital ratio. x„ is the sales-to-equitv ratio. 11)0 acronym ARAI is used only for the purposes of this paper. x14 is the investment turnover ratio, x15 is the net worth per share, x16 is the gross profit indicator, x17 is the operational profit indicator, x18 is the return on assets employed ratio, x19 is the return on equity ratio, and x20 is the price-to-earnings ratio. This approach was intended to facilitate mutual comparability as the focus of this research was not the analysis of intrinsic values of individual companies, but the comparisons of trends of intrinsic values and share prices over time. It should be noted that the ratios of debt to equity and debt to assets in calculating the average were taken in inverse form, so their negative or positive gain would better fit the trend of the average ratio analysis indicators (positive or negative). The ratio of price to earnings (P'E) in the calculation of averages was also taken in inverse form because, despite the controversies in the interpretation, the lower value of the P'E ratio was commonly considered as a positive signal for investment (i.e., the company is underpriced in the market). The trends of averages of ratio analysis indicators were then compared with the trends in the shares of market prices of individual companies. Furthermore, the same averages of ratio analysis indicators were calculated on the level of the index (where the weights were equal to participation that companies had in the index), and comparisons with the index trends were made. Finally, we compared the share price trends of the companies and the trends of stock market indexes to each other. 4 Results The following tables present the values of correlation coefficients between trends of averages of ratio analysis indicators ("ARAI") and the trends of the share prices3: Tables 1 through 7 present the different values of correlation coefficients between ARAI and share price trends, from a few companies with a relatively high positive correlation (SAVA, ATPL, BSNLR) to companies whose intrinsic value is even negatively correlated with the market price (CEZ, TELEFONICA, MOL, OTP, RICHTER, KRKG, DLKV, ULPL, METL, TLKM, BHTSR, JPESR). It is important to note that the correlation coefficients of prices and ARAI is statistically significant for 20 companies, while for six 3 Correlation coefficients and significance factors were calculated using the program SOFA Statistics (www.sofastatistics.com), according to the Pearson's method ("Pearson-R" and "two-tailed p"). The level of significance was 0.05. A comparative series was taken of the closing or official price on the stock exchange (depending on which of these two was uninterrupted) and the ARAI value for the current year, during all days of the year. Company KGHM PEKAO PKNORLEN PKOBP TPSA Correlation coefficient ARAI—share prices 0.2573 0.0133 0.4136 0.4144 0.5293 Source: Author's calculations Table 2: Correlation coefficients between ARAI and share prices—Prague SE (2005-2009) Company CEZ ERSTE TELEFONICA Correlation coefficient ARAI—share prices -0.2573 0.2282 -0.0125 Source: Author's calculations Table 3: Correlation coefficients between ARAI and share prices—Budapest SE (2005-2009) Table 3: Correlation coefficients between ARAI and share prices—Budapest SE (2005-2009) Company MOL OTP RICHTER Correlation coefficient ARAI—share prices -0.4007 -0.4616 -0.0245 Source: Author's calculations Table 4: Correlation coefficients between ARAI and share prices—Ljubljana SE (2005—2009) Company KRKG MELR PETG SAVA Correlation coefficient ARAI—share prices -0.6672 0.3734 0.4804 0.7069 Source: Author's calculations Table 1: Correlation coefficients between ARAI and share prices—Warsaw SE (2005-2009) Table 5: Correlation coefficients between ARA1 and share prices—Zagreb SE (2005-2009) Company ADRS ATPL DLKV IGH JDPL Correlation coefficient ARAI—share prices 0.0301 0.6255 -0.0844 0.5488 0.4518 Company KOEI PBZ PODR TNPL ULPL Correlation coefficient ARAI—share prices 0.0898 0.0041 0.2557 0.3132 -0.3872 Source: Author's calculations Table 6: Correlation coefficients between ARAI and share prices—Banjaluka SE (2005-2009) Company BIRA BLPV BOKS METL Correlation coefficient ARAI—share prices 0.3838 0.0804 0.0819 -0.2896 Company RFUM TLKM TRZN VITA Correlation coefficient ARAI—share prices 0.7583 -0.0405 0.2861 0.1046 Source: Author's calculations Table 7: Correlation coefficients between ARAI and share prices—Sarajevo SE (2005-2009) Company BHTSR BSNLR ENISR JPESR Correlation coefficient ARAI—share prices -0.2462 0.6999 0.2893 -0.0945 Source: Author's calculations Table 8: Correlation coefficients between average ARAI at the level of exchange and index trend Stock exchange WSE PSE BSE LJSE ZSE BLSE SASE Correlation coefficient Average ARAI—index 0.0663 0.3636 -0.3945 0.3036 0.0578 -0.6215 0.0067 Source: Author's calculations companies (i.e., PEKAO, TELEFONICA, RICHTER, ADRS, PBZ and TLKM) it is not. Due the variety of correlation coefficients of ARAI and price trends of individual companies, a better foundation for drawing conclusions could give a comparative examination of the movement of the index and the average of ARAI at the level of exchange, as can be seen from Table 8: Although some companies have a high positive correlation of intrinsic value and market price, at the level of the market as a whole, this is not the case. The highest degree of positive correlation between the average ARAI and index is at the Prague and Ljubljana Stock Exchanges, but it still falls within the domain of weak ties. The intrinsic values of companies traded at the Warsaw, Zagreb, and Sarajevo Stock Exchanges is not related with their market values, while the correlation coefficient of intrinsic and market value of companies from Budapest and Banjaluka Stock Exchanges is even negative.4 At the same time, the relationship between market price trends of companies whose shares are traded on the same stock exchange is generally positive and statistical- correlation coefficients of average ARAI and indexes were statistically significant in all cases except BLSE. ly significant (except in the case of the VITA-BLPV pair). The same is true in most cases in strong, very strong, or even extremely strong domains,5 as can be seen in Tables 9 through 15: The high level of correlation between price trends of shares traded on the same stock exchange, which also dominate the index of that exchange, should not be a surprise. However, it is especially interesting to examine the correlation between the indexes of selected stock exchanges. As can be seen from Table 16, all indexes are positively correlated (all significant), with a very strong or extremely strong relationship: 5 Conclusion According to the distribution of correlation coefficients, there is no causality in the relationship between the intrinsic value of companies and the market prices of their shares on the stock exchanges of transition countries of Central and Eastern Europe. Correlation close to perfect was not found, and no company showed a very strong relationship between intrinsic and market value. In six of the 37 An interpretation of correlation coefficients as relationship strength levels is given by Mujic, Legcevic, and Mikrut (2009). Table 9: Correlation coefficients between share price trends—Warsaw SE KGHM PEKAO PKNORLEN PKOBP TPSA KGHM PEKAO 0.7576 PKNORLEN 0.2881 0.6163 PKOBP 0.7721 0.8688 0.2816 TPSA 0.1506 0.6091 0.6639 0.4684 Source: Author's calculations Table 10: Correlation coefficients between share price trends—Prague SE CEZ ERSTE TELEFONICA CEZ ERSTE 0.1015 TELEFONICA 0.5643 0.6931 Source: Author's calculations Table 11: Correlation coefficients between share price trends—Budapest SE MOL OTP RICHTER MOL OTP 0.8996 RICHTER 0.6355 0.4874 Source: Author's calculations Table 12: Correlation coefficients between share price trends—Ljubljana SE KRKG MELR PETG SAVA KRKG MELR 0.8608 PETG 0.9061 0.9545 SAVA 0.8683 0.9058 0.8954 Source: Author's calculations Table 13: Correlation coefficients between share price trends—Zagreb SE ADRS ATPL DLKV IGH JDPL KOEI PBZ PODR TNPL ULPL ADRS ATPL 0.5308 DLKV 0.7652 0.8614 IGH 0.5734 0.9456 0.9013 JDPL 0.7397 0.9092 0.8650 0.8688 KOEI 0.7438 0.8077 0.9532 0.8732 0.7754 PBZ 0.8549 0.7261 0.9392 0.7952 0.7777 0.9659 PODR 0.8724 0.5546 0.8595 0.6361 0.6516 0.8764 0.9378 TNPL 0.8847 0.7832 0.9148 0.7788 0.9072 0.8519 0.9066 0.8293 ULPL 0.8406 0.5369 0.7570 0.5584 0.7257 0.6609 0.7739 0.8118 0.8627 Source: Author's calculations Source: Author's calculations Table 15: Correlation coefficients between share price trends—Sarajevo SE Table 14: Correlation coefficients between share price trends—Banjaluka SE BIRA BLPV BOKS METL RFUM TLKM TRZN VITA BIRA BLPV 0.4276 BOKS 0.8516 0.5401 METL 0.7912 0.1069 0.7027 RFUM 0.9554 0.4417 0.8294 0.8196 TLKM 0.8611 0.7052 0.9109 0.6191 0.8450 TRZN 0.7590 0.0760 0.7310 0.9046 0.8083 0.5920 VITA 0.8164 0.0327 0.7070 0.9174 0.8052 0.6246 0.8941 BHTSR BSNLR ENISR JPESR BHTSR BSNLR 0.9630 ENISR 0.9784 0.9648 JPESR 0.9504 0.9592 0.9542 Source: Author's calculations Ta ble 16: Correlation coefficients between indexes of selected stock exchanges Ta ble 16: Correlation coefficients between indexes of selected stock exchanges WSE PSE BSE LJSE ZSE BLSE SASE WSE PSE 0.9542 BSE 0.9391 0.9562 LJSE 0.7803 0.7795 0.7257 ZSE 0.8692 0.8413 0.7860 0.9570 BLSE 0.8232 0.7776 0.7015 0.7481 0.8417 SASE 0.8406 0.8326 0.7578 0.8638 0.9156 0.9537 Source: Author's calculations companies tested, a strong correlation was found, with correlation coefficients ranging between 0.51 and 0.76. Most of the remaining companies were located in the zone of weak or no relationship, and some had negatively correlated intrinsic and market values. Although correlation as a statistical measure does not determine the nature or direction of the relationship, the absence of a strong relationship for most companies in the sample, we believe, justifies the conclusion. At the individual company level we have variety of results, but the relationship between the average ratio analysis indicators at the level of the stock market and market index trends is generally weak. Two exchanges indicated weak relationships, three have no relationship between intrinsic and market values of the companies, and two have a negative correlation coefficient between those two values. Thus, the absence of a relationship between intrinsic value and market price is generally the case. Opposed to the relationship between intrinsic values of the companies and market prices of their shares (both at the level of individual companies and at the level of stock exchanges), the relationship between the trends of analyzed stock market indexes is positive and very strong—all without exception. The correlation coefficients of all individual pairs fall in the area of strong, very strong, or extremely strong relationships. Here we highlight two regions where the indexes are in almost perfect correlations: stock exchanges in the region of Central Europe and exchanges from the Western Balkans. Considering these findings, it can be concluded that the intrinsic value of a company is neither a determinant nor generator of the share market price on the stock exchanges of these transition countries. The question of what it is remains. Transition markets are far from efficient, according to efficient market hypothesis. The nature and intensity of relationships between intrinsic and market D/a II: Aim alt":: R lall' sk < >f i ll iMRIN.Sli VaUIE ; ■ Co,V.I a.n S Ah S la-'l PklAAN :|\ i ii Sl'!':k E:« :l-ah.;a', < ,| ClM'W and Ea i kN E .'• '¡ai Trai m"i< >N ....... r i values strongly suggest this conclusion. In order for the market to be efficient, the relationship between the indicators of company's business performance that result in a financial report at the end of the year and the share market price should always be measured by a positive and high correlation coefficient, which in the case of companies and slock exchanges in the sample is not present. Investors in transition stock markets do not recognize the intrinsic value of a company and do not incorporate it into the share market price. However, the movement of share prices on the observed stock exchanges is not a consequence of pure chance. Unconditionally positive and high correlations between the stockmarket indextrends (especially within the two regions) leave no room for the conclusion of randomness in price movement. In contrast, slock indexes "track" each other, leading to the possible conclusion that the fundamental determinant of share prices on the transition slock exchange is the behavior of investors and other market participants. Although the intrinsic values of companies in the sample arc not even close to the same, it appears that investors have an almost identical perception of these values and. following that perception, drive supply and demand trends in nearly identical direction and intensity. Therefore, the generators of the market value of companies in transition stock markets, we believe, can be found in the behavioral rather than the rational domain. References 1. Bragg. S. M. (2002). Business ratios and formulas. Hobokcn. NJ: John Wiley & Sons. 2. Brainard. W. C.. Shapiro. M. D.. & Shoven. J. B. 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Appendix Companies from the sample and review of participation of shares of these companies in the stock indexes Stock Exchange Ticker 2005 2006 2007 2008 2009 Warsaw (WSE) Participation in WIG20 at the end of year (%) KGHM KGHM 15,91 10,79 10,42 5,11 13,59 Pekao Bank PEKAO 10,98 12,17 13,84 15,38 14,68 PKN Orlen PKNORLEN 13,85 7,69 13,61 12,45 11,59 PKO Bank PKOBP 9,19 15,30 16,70 17,46 15,64 Telekom Polska TPSA 10,07 10,93 9,62 14,07 8,40 Total 60,00 56,88 64,19 64,47 63,90 Prague (PSE) Participation in PX at the end of year (%) CEZ Group CEZ 25,67 25,28 25,11 25,03 24,81 Erste Group ERSTE 18,13 25,42 24,13 20,09 24,41 Telefonica TELEFONICA 18,46 16,60 15,77 20,69 16,45 Total 62,26 67,30 65,01 65,81 65,67 Budapest (BSE) Participation in BUX at the end of year MOL MOL 27,27 27,32 29,17 26,71 27,46 OTP Bank OTP 29,46 35,53 32,84 22,73 28,77 Richter Gedeon RICHTER 18,61 16,26 17,76 26,01 22,95 Total 75,34 79,11 79,77 75,45 79,18 Ljubljana (LJSE) Participation in SBI20 at the end of year (%) Krka KRKG 13,26 15,52 16,88 15,98 13,5 Mercator MELR 16,44 13,41 9,53 11,29 12,41 Petrol PETG 11,01 14,5 14,87 13,98 15,94 Sava SAVA 17,94 10,81 14,02 13,49 9,73 Total 58,65 54,24 55,3 54,74 51,58 Zagreb (ZSE) Participation in CROBEX at the end of year (%) Adris grupa ADRS 7,17 7,68 10,23 10,89 12,92 Atlantska plovidba ATPL 3,75 3,26 9,38 6,81 8,72 Dalekovod DLKV 3,04 4,87 5,07 4,38 4,89 Institut IGH IGH 1,40 1,68 5,24 4,34 2,86 Jadroplov JDPL 1,55 1,26 0,96 0,55 0,61 Končar KOEI 2,35 4,27 3,26 3,42 3,42 Privredna banka PBZ 17,73 19,81 2,63 2,06 2,51 Podravka PODR 5,62 6,75 4,67 6,49 5,61 Tankerska plovidba TNPL 5,82 5,88 2,08 1,24 1,16 Uljanik plovidba ULPL 1,44 1,13 1,72 2,09 2,22 Total 49,86 56,58 45,25 42,27 44,92 Banjaluka (BLSE) Participation in BIRS at the end of year (%) Banjalučka Pivara BLPV 13,30 4,85 1,60 0,81 5,92 Birač BIRA 12,45 15,45 6,55 2,89 3,13 Boksit Milici BOKS 4,92 2,84 2,41 2,27 1,49 Metal Gradiška METL 1,13 1,14 1,41 1,07 1,21 Rafinerija ulja Modrica RFUM 17,95 15,61 4,98 2,58 2,46 Telekom Srpske TLKM 20,00 19,27 20,00 20,00 20,00 Tržnica Banja Luka TRZN 3,49 3,37 5,91 8,40 7,23 Vitaminka VITA 1,76 4,53 1,14 1,29 1,15 Total 75,00 67,06 44,00 39,31 42,59 Sarajevo (SASE) Participation in SASX-10 at the end of year (%) BH Telecom BHTSR 20,00 20,00 20,00 20,00 20,00 Bosnalijek BSNLR 7,75 8,02 6,89 10,84 9,51 Energoinvest ENISR 14,81 7,66 11,74 13,27 6,51 JP Elektroprivreda BiH JPESR 20,00 20,00 20,00 20,00 20,00 Total 62,56 55,68 58,63 64,11 56,02 Dzafer Alibegovic, PhD, was born in 1974 in Travnik, Bosnia and Herzegovina. He graduated from the Faculty of Economics in Sarajevo in 1999, where he earned his master's and PhD degrees. He is currently employed as an assistant professor with the Sarajevo School of Economics and Business. He has authored of dozens of articles published in scientific and professional magazines and conference proceedings, co-authored a textbook, and authored or co-authored various research studies and projects in the field of capital market development in Bosnia and Herzegovina. His primary field of interest is financial analysis and the functioning of capital markets. He is also frequently involved in professional trainings and seminars in the area of professional intermediation in capital markets, accounting, and auditing. Dr. Džafer Alibegovic je bil rojen leta 1974 v Travniku v Bosni in Hercegovini. Leta 1999 je diplomiral na Ekonomski fakulteti v Sarajevu. Na isti fakulteti si je pridobil tudi naziva magister znanosti in doktor znanosti. Trenutno je zaposlen kot docent na Ekonomski fakulteti v Sarajevu. Je avtor velikega števila člankov, ki so bili objavljeni v znanstvenih in strokovnih revijah ter zbornikih konferenčnih prispevkov. Je tudi soavtor učbenika ter avtor oziroma soavtor številnih raziskovalnih študij ali projektov s področja razvoja kapitalskega trga v Bosni in Hercegovini. Njegov osnovni raziskovalni interes predstavljata finančna analiza in delovanje kapitalskih trgov. Pogosto sodeluje pri strokovnem izobraževanju in seminarjih o intermediaciji na področju kapitalskih trgov, računovodstva in revizije.