Real versus expected market value creation (based on Warsaw Stock Exchange WIG30 companies)

Bank i Kredyt 56(6), 2025, 673-702 DOI: 10.5604/01.3001.0055.4547 Real versus expected market value creation (based on Warsaw Stock Exchange WIG30 companies) Jarosław Kaczmarek*, Sergio Luis Náñez Alonso# Submitted: 24 April 2025. Accepted: 6 August 2025. Suggested citation: Kaczmarek J., Náñez Alonso S.L. (2025), Real versus expected market value creation (based on Warsaw Stock Exchange WIG30 companies), Bank i Kredyt, 56(6), 673–702, DOI: 10.5604/01.3001.0055.4547. Abstract The purpose of this article is to assess the adequacy of excess market value added to equity as an external measure of company value creation in terms of meeting shareholders’ expectations. Panel research covered 30 WIG30 index companies on the Warsaw Stock Exchange in 2017–2024. Mathematical statistics tools, a density measure, and a taxonomic measure of similarity were used to evaluate the results. Three hypotheses were tested. First, the excess measure has been shown not to distort market information and to be suitable for assessing the effectiveness of value creation, taking into account shareholders’ expectations. Second, insufficient value creation has been demonstrated, which results in a negative assessment of value-based management, both in terms of its effectiveness and its efficiency. Third, the value creation profiles of companies are not similar in terms of rank position with respect to the strength of creation, its volatility, and its risk – both overall and broken down by activity. The value of this rare research is the objective way in which it assesses company value creation versus shareholder expectations and the application of its methodology in expectations-based management. Keywords: excess value, expectations-based management, value creation JEL: G32 * Corresponding author, Krakow University of Economics, College of Management and Quality Sciences; e-mail: [email protected].pl; ORCID: 0000-0002-2554-814X. # Catholic University of Ávila, Social and Legal Sciences Faculty; e-mail: [email protected]; ORCID: 0000-0001-5353-2017. The article presents the result of Project No. 054/ZIE/2024/POT financed from the subsidy granted to the Krakow University of Economics. J. Kaczmarek, S.L. Náñez Alonso 674 1. Introduction 1.1. The nature of value creation models Without entering into a broader theoretical discourse, in practice it is company value and its creation that provide a universal and comprehensive measure of company performance (Copeland, Koller, Murrin 2020, pp. 20–27). Assessing this value is a domain usually reserved for shareholders, but if value for shareholders is to grow, the value for stakeholders must grow too (Rappaport 2006). Such value is therefore a tangible expression of the realisation of their expectations and, more broadly, the development of the company (Srivastava, Shervani, Fahey 1998). This relationship does not invalidate the discussion about the attrition model of shareholders and stakeholders. The reason is not only the difference in objectives and the multiplicity of parties (Tirole 2001). A practical obstacle is the lack of a measure of stakeholder wealth (Bebchuk, Tallarita 2022). Therefore, despite the criticism of an excessive focus on short-term value creation and purely financial rewards, the shareholder model is still common (Bradford, Shapiro 2021). It is on this foundation that the concept of value based management (VBM) is built (Chari, Mohanty 2009). Undoubtedly, the stakeholders model is fostered by the development of the concept of corporate social responsibility (CSR), or sustainable development (Lidgreen et al. 2016). They directly target creating shared value (CSV) (Porter, Kramer 2011). Complications arise when the environment and community (setting) become ‘mute’ shareholders and are to be included in the measurement of value. In support of the stakeholders model, institutional investors play a central role (Dressler, Mugerman 2023), prompting pro-ESG actions. Although its impact on financial outcomes has been demonstrated (Dangelico, Pujari 2010), the measures of these outcomes, including value created, are still the same (York 2009). A mitigation against the polarity of value creation models is brought about by the proposal of an illuminated’ VBM, which assumes complementarity of interests and value creation for stakeholders and shareholders (Cwynar, Cwynar 2007, pp. 13–14). This proposition, developed in expectations-based management (EBM), has an additional key dimension in terms of its ability to ensure sustainable value creation (Fijorek et al. 2021). The prerequisite, however, is both the generation of added value and its realisation. This realisation takes place, among other things, through share appreciation, as discussed in the next section. As shown above, financial measures of value creation are still a common and adequate basis for measuring value creation. This statement underpins this article as an epistemological core. This is related to the objects of study, i.e. listed companies, for which value creation as a financial objective is a categorical imperative. The measurement of value creation has undergone an intensive evolution, now relying on market measures, mainly market value added (MVA) as an external measure. It expresses an objective, market- -based measurement, representing not the company’s performance, but the shareholders’ opinion on it. 1.2. Premises, objectives, and research hypotheses This last observation is valuable, but are there shortcomings in the way the MVA measures value? In fact, from the broadest perspective, the verification of the effects of corporate development is Real versus expected market value creation... 675 the assessment of the execution of stakeholders’ expectations. This approach, however, raises doubts whether managers, by pursuing a particular strategy of managing company value, and thus clearly belonging to the group of stakeholders themselves (Sakawa, Watanabel 2020), sufficiently ensure shareholders’ expectations. It can be questioned whether MVA is a measure that provides an appropriate/reliable basis for assessing value creation from the shareholders’ perspective alone. Does it realistically assess and express their level of expectations (i.e. minimum return covering the cost of capital, an at least similar and preferably above-average return on investment in the shares of a given company)? The key in this respect is how to measure value creation for shareholders. The concerns expressed above form the basis for the research in the article. The research problem addressed is the internal measurement of the company’s value creation in terms of meeting shareholders’ expectations. Therefore, the first objective of the article is to evaluate the adequacy of the proposed modified measure in the form of excess market value added. Adequacy, in this case, means whether the proposed measure does not distort market information while being appropriate for use in assessing the effectiveness of shareholder value creation, taking into account shareholder expectations. The achievement of the first objective makes it possible to undertake two further objectives: the detection of above-average value creation and the formulation of a related classification of companies, as well as the assessment of the similarity of company profiles in terms of their ranking position resulting from the strength of value creation, the volatility of that position and the degree of risk – both overall and by activity. The research in the article is conducted on the relationship in the domain of market value (company capitalisation) and market value added. The general assessment perspective adopted is the creation of value for shareholders, therefore, to their invested equity capital. Concerning the objectives of the article, three research hypotheses are set as follows: H1. Excess market value added to equity is positively, strongly, and statistically significantly correlated with changes in company capitalisation to a degree similar to increases in the market value added to equity. H2. The degree of creation of market value added to equity is sufficient from the point of view of shareholders’ expectations, i.e. it exceeds the minimum required rate of return on invested equity. H3. Value creation profiles in terms of the market value added to equity and the excess market value added to equity are similar. The realisation of the research objective and the verification of the formulated hypotheses took place under the conditions of the capital market in Poland. The panel research covered 30 companies with the highest capitalisation and market liquidity of shares (WIG30 index) on the Warsaw Stock Exchange (WSE). The study period is 2017–2024, with presentation of results following monthly periodisation. 2. Created value measurement vs. shareholders’ expectations In practice, the internal measurement of value created is equated with economic value added (EVA), developed as systemic value added (Magni 2003). In essence, it is the difference in the rate of return and the cost of capital multiplied by the capital invested, taking into account changes in the value of its equivalents and adjustments for result items that are not created from the use of operating assets J. Kaczmarek, S.L. Náñez Alonso 676 (O’Hanlon, Peasnell 2000). In contrast, external measurement is market value added (MVA) as the difference between market value and invested capital (Hillman, Keim 2001). In listed companies, market value is the company capitalisation. Hence, MVA is the difference between this capitalisation and equity. Both EVA and MVA are absolute measures, and a positive value means value added creation. It has been postulated that MVA is the sum of the net present value of an EVA series, obviously taking into account only equity and its cost. In general, MVA as an opinion on performance expressed by the market applies only to listed companies and only to their entirety (not business units) (Nyiramahoro, Shooshina 2001), it treats the market capitalisation of a company as the only benefit to owners (no cash distributions to shareholders), it is an absolute measure and difficult to compare. The main weakness of MVA is that it does not take into account shareholders’ expectations of future value creation. Consequently, despite the creation of added value, achieving a return on investment below shareholders expectations results in a fall in share prices and vice versa – a return above expectations results in the share price increasing. The reason lies in the difference between the understanding of company value creation and shareholder value creation (La Porta 1996). From shareholders’ point of view, it is necessary both to generate added value and to realise it. This realisation is achieved, among other things, by increasing the value of the shares brought about by the achievement of results more favourable than expected by shareholders. The expected value is included in the market price of the share as the value of future growth. Based on this criticism, a postulate was made about the necessary consideration of the difference between the real (achieved) value added and the one expected by shareholders. This means measuring excess market value added, which is undoubtedly a more restrictive criterion than market value added. At its core, excess market value added is a combination of two measurement routes, i.e. surplus return and value added. The result is excess residual income as the difference between real and expected annual economic profit, or, more broadly, also multi-year profit. To date, empirical studies of value added have been conducted on equity (Perotti, Wagenhofer 2011) and bonds (Bosse, Wimmer, Philips 2013), also on emerging markets (Gilmore, Hayashi 2011) and the Far East (Nurwati, Ramdi 2013). These studies examined value creation but only using ‘classic’ value added measures (EVA, MVA). Additionally, the correlation was examined not for the expected shareholder value creation, but only between the resulting MVA and the performance of the companies (Quintiliani 2018). The relationship between MVA and EVA and their impact on the stock rate of return was also examined (Johan 2019). In view of the conditions of the Polish capital market, a study of surplus TSR and MVA for four companies in the fuel sector (Mikołajek-Gocejna 2010) can be mentioned, which showed a trend of destruction of values, without seeking relationships with other measures of value creation. Another relevant piece of research is a study of the relationship between the internal measures of EVA, DCF and the external measure of MVA (Kaczmarek 2018). It did not confirm the correlation searched in this regard. In turn, studies of IT and video game companies (Pilch 2021) have shown a non-relationship between ‘classic’ measures of value (MVA, TSR) and simple return ratios (EPS, ROA, ROE, ROIC). Therefore, the deficit in how to measure the creation of market value added from the point of view of shareholders was recognised. Its essence is the simultaneous assessment of the effectiveness Real versus expected market value creation... 677 and efficiency of value creation. Effectiveness is the achievement of positive market value added, and efficiency is the achievement of figures that are satisfactory to shareholders. This approach is provided by the excess value concept proposed in the article. 3. Research methods Since M VA E is the difference between Market Value to Equity ( MVE ), or stock market capitalisation, and invested equity with equivalents ( C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ) – share capital, reserves and surplus less revaluation reserve and accumulated losses plus equivalents, e.g. adjustments for deferred tax reserve, inventory pricing reserve), positive value and value creation will occur when return on invested equity ( C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ) exceeds equity cost ( C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ) (Pfeiffer 2004). C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC (1) Shareholder expectations can be accommodated in two ways: (1) by relativisation to rates of value creation in other investments, thus examining Superior Shareholder Return (SSR), which, however, does not ensure that the objectives of the article are met, (2) by comparison of the real return with the expected return, which brings excess return. When the expected return is expressed by equity cost, excess return is the rate of return that exceeds what was expected or predicted (e.g. by CAPM – Capital Asset Pricing Model). This second way (Holler 2009; Mikołajek-Gocejna 2014) was used in the article to define the excess market value added to equity ( M VA EN ). It is the difference between the expected value ( M VA EP ) and the real value ( M VA ER ). Thus, M VA EP means the incremental MVE over the minimum required rate of return on invested equity ( C E IC C E R OIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ), equivalent to the equity cost margin ( C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ). This increment is reduced by invested equity ( C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ). A positive MVAEN value means that excess value is achieved. It can be compared with the change in dM VA E (delta, value creation), but not with the absolute value of M VA E. C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC (2) C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC (3) As a comment, it should be added that proposing a modification towards a redundant EVAE is not justified, as it still applies the above-mentioned criterion (its positive value implies a return higher than expected, determined by the cost of equity). The research hypotheses defined in the introduction can be translated into the expected values of the correlational relationships studied: If H1 were true, then the correlation for the associated correlation coefficients r ( M VA EN ; dMVE ) and r ( dM VA E ; dMVE ) should be very high; If H2 were true, then the correlation r ( M VA E ; dM VA EP ) should be almost full; If H3 were true, then the measure of the similarity of value creation and risk profiles for dM VA E and M VA EN should be close to unity. J. Kaczmarek, S.L. Náñez Alonso 678 3.1. Analytical tools To verify hypothesis H1, it was necessary to use non-standard mathematical statistics tools. Williams test statistic (T2) was applied for the equality of two related r-Pearson correlation coefficients (Meng, Rosenthal, Rubin 1992). Hypothesis H2 was verified using a test for a single r-Pearson correlation coefficient (degrees of correlation strength: < 0.1 faint; 0.1–0.3 weak; 0.3–0.5 average; 0.5–0.7 high; 0.7–0.9 very high; > 0.9 almost full). The critical level of significance was taken as a = 0.05. A probability value (p-value) lower than a entitles one to proceed ad hoc as if the null hypothesis of no correlation had been rejected, which is the basis for accepting the alternative hypothesis of the existence of a correlation (Wasserstein, Lazar 2016; Hubbard, Bayarri 2012). In general, changes in stock market capitalisation with a stable share price, affecting the components of the value measures equally (e.g. merger, acquisition, spin-off), do not impact the direction and strength of the correlations studied. To verify hypothesis H3, the taxonomic measure of similarity (TMS) was used (Kolegowicz, Kaczmarek, Szymla 2022). It determines the difference in structures over time, simultaneously, in terms of two quantities, i.e. dM VA E and M VA EN . The closer its value is to unity, the higher the similarity of the structures. The average rank method was used in the ranking. The rule of thumb was to assign the lowest rank value to the highest value of the measure analysed at the given moment. For the time series, the average rank position (ARP) and the variability of rank position (VRP) were calculated, taking the standard deviation as the VRP measure. In principle, the ranking procedure eliminates the impact of outlier observations. The density of sites (companies) was investigated using a density measure (DM) constructed for this purpose (Kaczmarek 2022). Its value corresponds to the area of the ellipse that covers the set of objects (companies) studied in the plane. A higher DM value indicates greater dispersion. The required rate of return on invested equity ( C E IC C E R OIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ) was determined by the CAPM model (augmenting the risk-free rate by the product of the systemic risk measure ‘beta’ and the equity risk premium – ERP). Calculations were made individually for each company. The beta measure was calculated from the returns on company shares relative to the returns on the portfolio that makes up the WIG30 index (weekly rates, 2017–2024). Stock quotes, including splits, subscription rights, and dividends, were used. The ERP was calculated as the difference between the average annual return on the S&P 500 index and the average yield on 30-year US Treasury bonds (stepwise, for jumps in the time series). This was then enhanced by a country risk premium as the difference in yields on 10-year US and Polish government bonds. 3.2. Empirical data The 2017–2024 panel study covered 30 companies from the Warsaw Stock Exchange WIG30 index, prevailing in the capitalisation of the stock market (39.4%). Their assets at the end of 2024 were PLN 3,031 bn and reached revenues of PLN 834 bn. They accumulated PLN 564 bn in equity, with a capitalisation value of PLN 571 bn. In terms of assets and capitalisation, finance companies (banking and insurance) predominate. In contrast, in terms of equity and sales, production companies (mining Real versus expected market value creation... 679 and manufacturing) do. Commerce and hospitality companies rank third in terms of capitalisation. The characteristics of the companies studied have been provided in Table 3 (Appendix). Data sources included emis.com, notoria.pl, gpw.pl, stockwatch.pl, and ekrs.ms.gov.pl. (commercial access). Regression-based imputation was used in completing the input data for the estimation of the value added, without significantly deforming the absolute values. The scope of value-added calculation adjustments has been limited to the information available in the financial statements. The results of the value-added measurement are presented for a monthly periodisation. The input periodic data are converted to an annual timeframe, and therefore the added value and related categories are cumulative figures. 4. Results 4.1. Value creation and its gap Until 2019, the capitalisation of the companies surveyed ( MVE ) was stable (annual average), with a lockdown period (2020), an attempted rebound in 2021 and a rapid one from 2023 onward. The final increase between 2017 and 2024 was 17.0%. On the other hand, the marked value added to equity ( M VA E ) decreased steadily until 2019, and the deep collapse is not the lockdown period, but the years 2022–2023. These two years represent a market value loss ( MVL ) of PLN -104.7 bn, compared to the creation of PLN 270.9 bn for the period 2017–2024. Finance companies reacted in a strongly negative way to the lockdown, whereas the slump in production companies emerged only after 2021. Meanwhile, commerce companies recorded a positive MVAE throughout. In general, the increase in dMVE between 2017 and 2024 is PLN +111.0 bn (+19.4%), and yet the loss of dM VA E amounting to PLN -80.1 bn is a negative assessment and a strong signal to investors (shareholders). Production companies lost the most (PLN -118.3 bn) (Figure 1). A weakness of M VA E is its failure to take into account the expectations of shareholders. This is because the creation of added value may be progressing, but the return on investment is below their expectations. The application of the proposed measure of excess market value added, taking into account these expectations, first requires checking that it does not distort market information (verification of hypothesis H1). For H1 verification, two pairs of correlations were examined: dMVE and dM VA E , and dMVE and M VA EN . The correlation was expected to be very high (0.7–0.9). The Williams test generally showed a very high, positive and statistically significant correlation, T2 = 0.794 (as an average for 30 companies, for each p-value < 0.000, min = 0.646, max = 0.950). The highest degree of correlation was for production companies (T2 = 0.838), followed by commerce (T2 = 0.764) and finance (T2 = 0.729). The above is the basis for accepting the first hypothesis as true: H10 – excess market value added to equity is correlated with changes in company capitalisation to a similar extent as increases in market value added. This means that M VA EN is an appropriate, non-deformative measure suggested for use in assessing the effectiveness of shareholder value creation, taking into account shareholder expectations. J. Kaczmarek, S.L. Náñez Alonso 680 4.2. Expected versus real value creation The demonstrated loss of market value added to equity ( M VA E ) between 2017 and 2024 of PLN -80.1 bn, is not the end of the negative assessment. In fact, the size of the value gap as measured by excess market value added to equity ( M VA EN ) was PLN -369.1 bn (4.6 times larger). The shareholders expected such value creation. Unfortunately, not only were their expectations not met (the condition is M VA EN = 0), but there was a significant gap ( M VA EN < 0). The relative size of this gap ( M VA EN to C E IC C E ROIC ECCC ; 0 C C C E E E E E MVA MV IC ROIC ECC MVA value creation= −>→ > → ( ) C E ROIC ( ) C E IC ( ) 1 1 1 ; C C EP Et t Et EN ER EP MVA MV ECC IC MVA MVA MVA − − = + −=− 0 EN MVA excess value >→ ( ) C E ROIC ratio) as an average for 2017–2024 was -1.4%, while relative to stock market capitalisation (MVAEN to MVE ratio) it was -10.3%. In view of the creation of market value added to equity (MVAE) that was in place since 2017, investor expectations also gradually weakened and thus the value gap narrowed. The 2020 pandemic and the accompanying deeply pessimistic sentiment and low expectations did not translate into dramatically poor company performance, and the gap narrowed in the second half of 2020 on that account. It was different in 2022. Instead of the expected rapid rebound, there was a post-pandemic recession due to the dislocation of the global economy and the value gap widened (Figure 2). Between 2017 and 2024, the largest M VA EN value gap (PLN -139.6 bn) appeared in finance companies (37.8% share of the total gap), followed by production (PLN -127.1 bn, 34.4%) and trade (PLN -102.3 bn, 27.7%). Differences between these types of business were not significant in the period under review, except 2022 and especially 2024 – in finance (PLN -30.6 bn) twice as high as in commerce and half as high as in production. To verify hypothesis H2, the correlation of M VA E and dM VA EP was examined. A result close to unity was expected. The resulting r = 0.192 is a near-poor correlation (as an average for 30 companies, for each p-value < 0.000, min = 0.059, max = 0.299, sd = 0.066). The result is also not significantly improved by correlation studies using higher-degree polynomials. The above is the basis for rejecting the second hypothesis as null hypothesis H20 and accepting the alternative hypothesis H21: the degree of market value added creation by WSE WIG30 companies between 2017 and 2024 was insufficient in terms of shareholders’ expectations. 4.3. Properties of a set of companies: ranking and classification For the measure of M VA EN (as excess or value gap), a comparable measure is the change (increase/ decrease) in the value-added dM VA E . These values can be analysed as a distribution over time and companies. Between 2017 and 2024, there was a dispersion and displacement of companies in the coordinate system ( dM VA E; MVAEN ). The value of the dispersion measure (DM) increased 2.1 times and its changes were weakly, positively correlated with the stock market capitalisation ( MV E ) (r = 0.145). Until 2019, the DM remained stable, with the first spike occurring in 2020 (lockdown), but the highest in 2022 (also the highest amplitude of change) (Figure 3a). Increasing dispersion means that companies are moving away from each other, diversifying. The focal point moved deeper into the quadrant ( +dM VA E ; -M VAEN ). What was significant was the displacements of companies in the least unfavourable direction, that is, into the quadrant ( -dM VA E; -M VAEN ). Therefore, in general, there was not only a loss of added value, but also an increase in the gap between expected and real results (Figure 3b). Real versus expected market value creation... 681 Between 2017 and 2024, positive dM VA E (PLN +107.6 bn) were associated with 16 companies (six finance, seven production, three commerce) and negative values with 14 companies (PLN -187.7 bn, nine production, three commerce, two finance). On the contrary, in terms of M VA EN , no company achieved a positive result (Figure 4). Of the top ten companies representing positive dM VA E values, only one made it into the top ten in terms of M VA EN – this was Bank Handlowy w Warszawie SA (BHW). It was ranked 10th on both lists of tops. Dino Polska SA (DNP) was characterised by the greatest value creation, while LW Bogdanka SA (LWB) had the smallest value gap. There were three companies in the last ten both in terms of dM VA E and M VA EN , namely KGHM Polska Miedź SA (KGH), Allegro.eu SA (ALE) and Polski Koncern Naftowy Orlen SA (PKN). The latter recorded the largest loss of dM VA E , while Allegro.eu SA showed the largest M VA EN value gap among all companies (Table 1). The data in Table 1 can be used as a basis for classifying the companies surveyed. They express absolute and cumulative results. Therefore, the classification has been improved by calculating the average rank position (ARP) in consecutive monthly periods within a given year and the variability of rank position (VRP), taking the standard deviation as its measure. In general, the ranking procedure eliminates the impact of outlier observations. Firstly, ARP indicates that the companies differed more in terms of M VA EN than dM VA E . The gap between maximum and minimum for M VA EN was 28.5 : 2.6, while for dM VA E it was 18.2 : 12.6. For only three companies did proximity to the ARP occur: Cyfrowy Polsat SA (CPS), Alior Bank SA (ALR) and Bank Millennium SA (MIL) (Figure 5a). Within the group of production companies, the ARP for dMVAE was the highest, as was the split. In contrast, commerce companies had the lowest ARP and financial companies the smallest split. In terms of M VA EN , the highest ARP was achieved by finance companies and the lowest by production companies, with the split being the largest for the latter. Secondly, the variability of rank position (VRP) was almost 2.5 times higher in terms of dM VA E (8.3) than of M VA EN (3.4). A group of companies with a relatively low but persistent M VA EN gap became apparent: – Ten Square Games SA (TEN), – Grupa Kęty SA (KTY), – Asseco Poland SA (ACP), – LiveChat Software SA (LVC), – LW Bogdanka SA (LWB), and with a relatively high and also persistent MVAEN gap: – Powszechny Zakład Ubezpieczeń SA (PZU), – Bank Pekao SA (PEO), – PKO BP SA (PKO), – Pepco Group N.V. (PCO), – Polska Grupa Energetyczna SA (PGE), – Allegro.eu SA (ALE), – mBank SA (MBK), – Polski Koncern Naftowy Orlen SA (PKN), – KGHM Polska Miedź SA (KGH), – Santander Bank Polska SA (SPL). J. Kaczmarek, S.L. Náñez Alonso 688 Rappaport A. 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Available online: https://www-1emis-1com-1v9owocmt1833.hanbg.uek.krakow.pl/php/home, https://uekr-1notoria-1pl-1y3wmvzmt1837.hanbg.uek.krakow.pl/companies/dashboard/WIG30, https://www.gpw.pl/archiwum-notowan, https://www.stockwatch.pl/gpw/indeks/wig30,sklad.aspx, https://ekrs.ms.gov.pl/. For Pepco Group N.V., Allego.eu SA, Dino Polska SA, and Ten Square Games SA, regression-based imputation was used. J. Kaczmarek, S.L. Náñez Alonso 690 Figure 2 Excess market value added to equity (MVAEN) and market value added to equity (MVAE) of WSE WIG30 listed companies in 2017–2024 -200 -150 -100 -50 0 50 100 -90 -45 0 45 PLN bn PLN bn 2017 2018 2019 2020 2021 2022 2023 2024 MVAEN MVAEN average MVAEMVAE average Notes: MVAE – right axis. Source: as in Figure 1. Real versus expected market value creation... 691 Figure 3 Market value (MVE) versus density measure (DM) for dMVAE and MVAEN (panel 3a) and position of companies with respect to dMVAE and MVAEN (panel 3b) of WSE WIG30 listed companies in 2017–2024 300 350 400 450 500 550 600 0 2 4 6 8 10 PLN bn PLN bn PLN bn Figure 3a Figure 3b 2017 2018 2019 2020 2021 2022 2023 2024 MVEDM DM average -5 0 5 10 15 20 -8 -6 -4 -2 0 dMVAE MVA EN 2017 2024 –MVA EN –dMVA E –MVA EN + dMVA E Notes: DM – left axis (dimensionless values). Source: as in Figure 1. J. Kaczmarek, S.L. Náñez Alonso 692 Figure 4 Excess value added to equity (MVAEN) and changes in market value added to equity (dMVAE) of WSE WIG30 listed companies in 2017–2024 -50 -40 -30 -20 -10 0 10 20 -90 -70 -50 -30 -10 10 30 PLN bn PLN bn dMVAE DNP PKO LPP SPL PEO MBK CDR KTY ACP BHW MIL OPL KRU LVC TPE EAT TEN ALR CCC PZU LWB ATT ENA KGH CPS PGE JSW PCO ALE PKN MVAEN Notes: MVAEN – right axis. Stock tickers were used to identify the companies (see Table 3). Source: as in Figure 1. Real versus expected market value creation... 693 Figure 5 Average rank position (ARP) of WSE WIG30 companies by excess value added to equity (MVAEN) and changes in market value added to equity (dMVAE): panel a) in 2017–2024, as a whole period; panel b) classification of the entire period 2017–2024; panel c) in 2017–2024, ‘heat map’, year by year 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Figure 5a Figure 5b ACP ALE ATT CCC CDR CPS DNP EAT ENA JSW KGH KRU KTY LPP LVC LWB OPL PCO PGE PKN TEN TPE ALR BHW MBK MIL PEO PKO PZU SPL dMVA E MVA EN 12 13 14 15 16 17 18 II I 19 0 4 8 12 16 20 24 28 dMVA E MVA EN J. Kaczmarek, S.L. Náñez Alonso 694 Figure 5, cont'd Figure 5c dMVA E dMVA EN Ticker 20172018201920202021202220232024 TEN 1.2 1.8 1.5 6.5 6.0 1.5 1.2 1.2 LVC 2.3 1.5 2.0 5.0 5.3 4.2 5.6 3.8 KTY 3.7 4.3 4.3 5.8 5.1 6.0 6.3 8.3 LWB 4.3 4.1 3.9 2.8 1.1 1.8 2.3 2.0 ACP 5.0 4.7 4.8 8.1 5.3 7.3 7.7 6.7 DNP 6.3 11.7 14.8 20.2 23.1 25.8 27.2 23.7 KRU 8.4 7.4 7.1 7.4 8.6 10.9 13.2 13.9 OPL 9.2 9.7 10.4 15.6 13.8 13.8 13.7 13.9 BHW 9.5 9.6 9.5 9.5 5.4 10.5 14.5 15.3 CDR 10.6 14.3 18.3 25.6 21.0 17.0 17.8 16.1 ENA 10.6 8.6 9.7 8.3 8.3 8.5 6.3 8.5 TPE 11.6 8.3 7.8 8.5 11.3 9.7 9.1 9.7 ATT 12.0 9.1 8.8 8.6 6.1 6.9 4.8 3.6 EAT 12.3 14.0 14.3 13.8 12.9 9.7 9.6 8.8 JSW 15.9 15.7 12.3 6.3 9.8 14.3 12.0 6.3 MIL 17.0 18.0 17.9 15.2 12.8 14.5 14.6 17.3 ALR 17.3 16.4 14.7 10.3 9.9 12.2 14.1 18.4 CCC17.4 16.4 14.8 9.9 14.4 6.4 5.5 11.9 CPS 18.3 16.3 16.7 19.4 19.8 18.1 16.3 10.3 LPP 18.6 20.0 19.1 19.8 21.7 22.6 22.6 23.1 PZU 21.9 22.6 24.3 25.0 23.0 22.8 24.8 24.7 PCO 22.1 22.8 22.7 22.7 22.9 21.2 19.5 14.6 MBK 23.4 24.4 23.8 21.1 19.5 20.5 20.4 22.8 KGH 24.3 22.8 22.3 24.3 28.5 26.6 23.8 22.3 PEO 24.5 24.8 24.8 21.3 21.2 23.3 23.5 26.3 PGE 25.3 23.8 20.9 19.7 21.5 22.0 18.4 19.9 PKN 27.0 25.8 27.3 25.0 24.6 24.6 29.9 29.7 SPL 27.0 27.7 27.3 23.8 24.0 26.2 26.1 27.9 PKO 28.4 29.2 28.8 25.7 28.3 29.0 28.5 29.3 ALE 30.0 29.8 30.0 30.0 29.8 27.3 25.9 25.0 Ticker 20172018201920202021202220232024 DNP 9.3 12.0 11.3 9.1 14.7 12.8 15.1 16.7 LPP 10.9 16.5 12.4 14.5 9.8 15.3 12.3 16.1 PCO 11.3 15.7 16.7 13.8 15.7 17.3 19.6 17.1 CCC12.3 15.7 19.2 13.8 17.5 16.2 14.8 9.9 CDR 12.7 11.8 6.1 12.4 16.9 18.4 16.0 11.5 MBK 12.8 16.6 16.0 21.6 10.1 15.3 13.5 18.2 ALR 13.8 18.0 17.8 16.9 11.9 14.9 15.3 14.9 PKN 14.0 17.4 21.7 18.3 18.5 18.2 16.1 21.4 EAT 14.1 12.9 13.8 15.3 16.8 14.4 16.0 16.0 MIL 14.4 15.3 18.3 16.6 10.8 14.3 15.1 14.0 SPL 14.8 16.9 16.0 19.9 9.2 18.3 13.1 15.0 PZU 14.8 13.9 17.5 20.3 13.3 16.4 11.2 17.5 PKO 15.0 18.1 20.1 19.0 10.0 18.3 13.8 12.4 KRU 15.3 16.2 15.2 14.3 12.8 14.3 14.1 15.6 PEO 15.9 15.5 16.3 18.8 8.3 17.3 14.5 18.8 JSW 16.3 19.5 22.8 13.2 17.0 17.2 20.5 15.4 KGH 16.3 19.7 12.6 11.3 23.5 14.8 17.3 17.4 TEN 16.4 12.8 13.2 12.3 18.9 14.1 17.7 13.2 PGE 16.8 20.5 17.7 19.0 17.7 17.3 13.4 20.2 KTY 16.9 13.2 14.3 13.4 16.2 13.8 14.1 14.3 OPL 17.1 16.2 12.4 16.3 17.3 15.1 14.4 15.1 ENA 17.3 15.9 15.8 15.7 18.3 14.2 15.1 15.5 CPS 17.6 15.6 12.3 14.8 16.2 20.3 20.7 15.4 ATT 17.8 18.0 15.0 16.3 16.8 13.4 16.8 13.2 BHW 18.1 13.8 17.0 16.6 13.8 10.8 15.4 15.4 TPE 18.2 16.7 16.4 13.8 18.3 14.6 15.5 15.8 LVC 18.3 13.0 13.8 13.2 17.0 12.8 16.7 15.3 LWB 18.3 13.3 16.2 15.8 17.1 12.4 18.1 13.1 ALE 19.0 12.9 15.2 14.8 24.9 19.2 13.4 19.5 ACP 19.4 11.8 12.1 14.3 16.0 13.6 15.8 11.2 Note: as in Table 1. Source: as in Figure 1. Real versus expected market value creation... 695 Figure 6 Profiles of WSE WIG30 companies in terms of taxonomic measure of similarity (TMS) for the ranking position (ARP, panel 6a) and its variability (VRP, panel 6b) based on the market value added to equity (dMVAE) and the excess value added to equity (MVAEN) in 2017–2024 ARP MVAEN dMVAE MVAEN dMVAE Figure 6a Figure 6b Production Commerce Finance Production Commerce Finance VRP Production Commerce Finance ACP ATT CDR CPS EAT ENA JSW KGH KTY LVC LWB OPL PGE PKN TEN TPE ALE CCC DNP KRU LPP PCO ALR BHW MBK MIL PEO PKO PZU SPL ACP ATT CDR CPS EAT ENA JSW KGH KTY LVC LWB OPL PGE PKN TEN TPE ALE CCC DNP KRU LPP PCO ALR BHW MBK MIL PEO PKO PZU SPL Note: as in Table 1. Source: as in Figure 1. J. Kaczmarek, S.L. Náñez Alonso 696 Table 1 Changes in market value added to equity (dMVAE) and excess value added to equity (MVAEN) of WSE WIG30 listed companies by rank position in 2017–2024 dMVAEMVAEN dMVAEMVAEN Ticker rank position PLN bn Ticker rank position PLN bn Ticker rank position PLN bn Ticker rank position PLN bn DNP 126.9 LWB 1-0.9 EAT 16 0.5 MIL 16 -8.1 PKO 217.5 TEN 2-0.9 TEN 17 -0.4 CPS 17 -9.5 LPP 314.2 LVC 3-1.5 ALR 18 -0.6 CDR 18 -11.1 SPL 410.1 KTY 4-2.3 CCC 19 -1.5 PCO 19 -14.8 PEO 59.3 ACP 5-2.4 PZU 20 -2.1 PGE 20 -16.1 MBK 66.4 ATT 6-2.9 LWB 21 -2.2 LPP 21 -16.3 CDR 74.5 ENA 7-3.5 ATT 22 -3.1 DNP 22 -16.7 KTY 84.4 TPE 8-3.8 ENA 23 -3.5 MBK 23 -17.4 ACP 94.2 KRU 9-4.1 KGH 24 -8.0 PZU 24 -19.9 BHW 10 3.2 BHW 10 -4.5 CPS 25 -10.0 PEO 25 -20.5 MIL 11 2.1 EAT 11 -5.2 PGE 26 -10.6 KGH 26 -22.5 OPL 12 1.4 OPL 12 -5.3 JSW 27 -12.1 SPL 27 -26.6 KRU 13 1.1 JSW 13 -5.4 PCO 28 -17.1 PKN 28 -33.9 LVC 14 0.9 CCC 14 -5.8 ALE 29 -31.4 PKO 29 -35.8 TPE 15 0.8 ALR 15 -6.9 PKN 30 -85.3 ALE 30 -44.6 Note: stock tickers were used to identify the companies (see Table 3). Source: as in Figure 1. Real versus expected market value creation... 697 Table 2 Risk charge on value creation (dMVAE) of WSE WIG30 listed companies by rank position in 2017–2024 RVC (positive dMVAE) RVC (negative dMVAE) Ticker rank position PLN/PLN Ticker rank position PLN/PLN ACP 10.06 ALR 30 1.15 KTY 20.06 PZU 29 0.93 DNP 30.08 CCC 28 0.56 LPP 40.13 TEN 27 0.53 BHW 50.14 KGH 26 0.30 PKO 60.18 PGE 25 0.21 LVC 70.19 ENA 24 0.15 PEO 80.21 ATT 23 0.13 SPL 90.23 ALE 22 0.12 MBK 10 0.29 CPS 21 0.09 KRU 11 0.31 PCO 20 0.09 OPL 12 0.36 PKN 19 0.09 MIL 13 0.41 JSW 18 0.08 CDR 14 0.42 LWB 17 0.08 TPE 15 0.80 EAT 16 1.60 Note: as in Table 1. Source: as in Figure 1.