Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies

Bolek, Monika; Gniadkowska-Szymańska, Agata; Pietraszewski, Piotr Article Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly Provided in Cooperation with: University of Information Technology and Management, Rzeszów Suggested Citation: Bolek, Monika; Gniadkowska-Szymańska, Agata; Pietraszewski, Piotr (2025) : Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies, Financial Internet Quarterly, ISSN 2719-3454, Sciendo, Warsaw, Vol. 21, Iss. 1, pp. 27-41, https://doi.org/10.2478/fiqf-2025-0003 This Version is available at: https://hdl.handle.net/10419/329894 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/3.0/ 10.2478/fiqf-2025-0003 Abstract The aim of the article is to show differences in the growth process that translates into growth potential in groups of enterprises listed on the main and alternative markets of the London Stock Exchange. The study covered companies included in the Financial Times Stock Exchange 100 Index (FTSE 100), as well as companies listed on the Alternative Investment Market (AIM). Based on the results of statistical analysis including correlation and regression analysis of panel data, it was found that companies listed on the alternative exchange (AIM) were characterized by higher growth potential and faster growth than those listed on the main market (FTSE 100). The added value of the article is related to results indicating that there is a difference in the growth process between companies traded on both markets. This conclusion can be useful for investors expecting the growth of share value in the investment process. JEL classification: G32 Keywords: Growth Potential, Growth of Companies, Less Developed and Mature Companies Received: 19.08.2024 Accepted: 17.10.2024 Cite this: Bolek, M., Gniadkowska-Szymańska, A. & Pietraszewski, P. (2024). Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies. Financial Internet Quarterly 21(1), pp. 27-41. © 2025 Monika Bolek et al., published by Sciendo. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. 1 University of Lodz, Faculty of Economics and Sociology, Department of Capital Market and Investments, Poland, e-mail: [email protected], ORCID: https://orcid.org/0000-0003-4020-2988. 2 University of Lodz, Faculty of Economics and Sociology, Department of Capital Market and Investments, Poland, e-mail: agata.gniadkowsk[email protected], ORCID: https://orcid.org/0000-0002-7321-3360. 3 University of Lodz, Faculty of Economics and Sociology, Department of Capital Market and Investments, Poland, piotr.pietraszews[email protected].pl, ORCID: 0000-0002-0589-0327. Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 bitious companies with the potential to become future giants, but also with a higher risk of failure. Forecasting growth in both groups may have different rules due to differences in the companies and markets on which they are listed, consequently, it may influence investment decision-making. The expected growth process is related to the growth potential that investors are interested in. Growth potential ratios are based on investors’ expectations and should be related to the future growth (Danbolt et al., 2011). The correlations between the measures of growth and measures of growth potential show whether investors’ expectations meet the future growth of companies. Earlier research (Pietraszewski et al., 2023) found that companies included in the AIM index are more predictable in terms of business operations (e.g., growth of assets, equity, and sales) and companies included in the FTSE100 index in terms of earnings growth. It can be concluded that growth opportunity measures are significantly related to the growth of value of companies as measured by EPS growth. The EPS growth is lower in smaller firms as measured by market value and we can conclude that mature companies with higher capitalization are value drivers on a capital market. This statement was confirmed by the results referring to the lower impact of assets growth on the FTSE100 index included companies compared to the alternative AIM market. The article attempts to show the differences between enterprises according to the exchange upon which they are listed, which translates into the growth potential and the possibility of predicting their development. In the research part the hypothesis that there is a difference regarding the growth dynamics, potential, consistency and factors affecting the EPS growth in both groups of companies included in the FTSE100 and AIM indices is tested. The article consists of an introduction, a literature review, a description of the data and research methods, results, and conclusions. A company’s growth is related to its value management, and therefore the expected growth should be included in every strategy (Doyle, 2009). According to Lotti et al. (2003), value is also related to its internal growth, which may be balanced and stable (e.g., in mature companies) or fast and dynamic (e.g., in younger companies). A company’s growth is most often described as quantitative (Patton, 2005; Barringer et al., 2005), while its development is qualitative (Vaismoradi et al., 2016). A company’s development is related to expanding its competencies (Troisi et al., 2020), and there is also a feedback loop between growth and development. Miller and Modigliani (1958) recognized The growth of enterprises is important in their valuation, where factors that influence this process are taken into account. The research problem in the presented article covers the topic of enterprises that are divided according to their level of development. Mature companies are those that are included in the FTSE100 index, while less mature, smaller firms are listed on the alternative exchange and are included in the AIM index. Smaller companies can operate in the niche, or they can grow quickly on the basis of their innovative product with the financing obtained on the alternative stock exchange. Capital supporting the commercialization process can lead to a rapid increase in assets when investment projects are implemented and, as a consequence, sales and earnings per share (EPS) growth, if the investments are efficient. Growth understood in this way should translate into an increase in the fundamental value and thus the market price, if the market is efficient. Taking into account the growth process in the group of less mature enterprises, investors expect that the capital they invest will bring higher benefits in the form of rates of return in the future, therefore, the growth potential in this group should be higher. However, the growth process may be different depending on the type of company and, consequently, the stock exchange on which it is listed. The presented research covers enterprises included in the Financial Times Stock Exchange 100 Index (FTSE100) and in the Alternative Investment Market (AIM) index. The main differences between companies included in the FTSE 100 and the AIM index on the London Stock Exchange lie in their size, stage of development, and regulations. FTSE 100 companies are large, well-established companies with a strong track record. These are typically blue -chip companies that are household names in the UK and often globally. The FTSE 100 comprises the 100 largest companies by market capitalization listed on the London Stock Exchange and are under stricter listing requirements, including financial performance benchmarks and corporate governance standards. These companies are generally considered less volatile due to their established nature. On the other hand, companies included in the AIM index are smaller, with high growth potential. These can be young, innovative companies or established firms looking to raise capital for expansion. The AIM is a much broader market with over 800 companies listed and there are less stringent listing requirements compared to the FTSE 100, making it easier for smaller companies to list. This market is generally considered more volatile due to the higher growth potential and inherent risks associated with smaller companies. The FTSE 100 is like the Premier League of UK stocks - established giants with a proven track record. The AIM is like the Championship League - smaller, am- Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 human resources and technology (Beck et al., 2006). Investors may be interested in supporting innovative ideas, contributing to job creation, or making a positive impact in their community. This can be particularly true for impact investors or those who are interested in socially responsible investing (Skalicka et al., 2023; Khanka et al., 2022). However, investors must carefully evaluate the risks and rewards before making an investment and should have a clear understanding of the business and its growth potential (Zinecker et al., 2022). Large companies have more resources and can leverage economies of scale to maintain a competitive advantage (Nosratabadi et al., 2019). Bocken et al. (2019) presented several reasons why large companies tend to grow more slowly and more steadily while mentioning market saturation, bureaucracy, risk aversion and focus on profitability. However, mature companies can still achieve significant growth through strategic investments, mergers and acquisitions, and other initiatives that leverage their resources and market position (Alvino et al., 2021). Wennberg (2013) found that larger companies tend to grow more slowly than smaller ones. However, smaller companies had higher growth rates than larger ones. Fors Connolly et al. (2021) found that small businesses tend to have higher growth rates than large businesses in the early stages of their development. However, they also found that larger businesses tend to have more stable growth rates over the long term. Roh et al. (2022) found that larger firms tend to be less innovative than smaller firms. These studies suggest that while large companies may grow more slowly and more linearly than small companies, they can still achieve significant growth through strategic investments, mergers and acquisitions, and other initiatives that leverage their resources and market position. However, larger companies may be more risk-averse and less innovative than smaller ones, which can affect their ability to achieve rapid growth (Di Vaio et al., 2020; Streimikiene et al., 2021). This paper examines companies listed on the London Stock Exchange (LSE) and included in the AIM and FTSE100 indexes. Data come from Bloomberg’s database. The analysis includes data on the FTSE 100 1971– 2019 and AIM 1980–2019 (up to the outbreak of COVID -19). Data for the AIM and FTSE100 indices are analyzed from the beginning of the public trading, which is due to the asymmetry of the sample. Share prices have been adjusted to reflect changes in capital from subscription rights, dividends, and divisions. The database contains 2584 observations (year-on-year) for the FTSE100 and 1794 observations for AIM. that a company’s value comprises the value of assets and the flows they generate, as well as the value of the growth potential. For the company to grow, future investment projects must have a rate of return that exceeds the cost of capital (Chen 2019; Irawan et al., 2023). Long-term growth potential depends on the company’s return on equity and the retained net profit rate (Brusov et al., 2021; Lucky, 2019; Rahim et al., 2021; Kamila et al., 2021). A key factor that affects growth potential and its possibilities is company size (Perdana et al., 2022), which therefore determines its growth and its stability (Baskaran et al., 2019; Holliday, 2001). Small companies are typically characterized by greater flexibility and agility to quickly pivot their business strategies and seize new opportunities, which can lead to faster growth (Gherghina et al., 2020; Fitriasari, 2020; Saputra et al., 2022). However, as noted by Achim et al. (2022), this can also result in more chaotic and unpredictable growth patterns, as small companies which may not have established processes and structures in place to handle rapid expansion. Investors who focus on small companies are often willing to take on more risk in exchange for potentially higher rates of return (Côté et al., 2022; Fisch et al., 2021). As a result, investors can demand a higher rate of return to compensate for the additional risk (Salm et al., 2016; Baker et al., 1977; Merikas et al., 2004). Small businesses are often in the early stages of growth and may not have a proven track record or market position, increasing the risk for investors (D’Angelo, 2019). In exchange for taking on this risk, investors typically expect higher returns when investing in small businesses as they have the potential for significant growth and can provide investors with a greater return on their investment if the business is successful (Smith et al., 1994; OECD, 2010a, 2011a). As shown by Dunne and Hughes (1994), large companies tend to grow more slowly and steadily because they have already established themselves on the market and have a solid customer base. They may also have more established processes and structures in place to manage growth, which can make it easier for them to scale up in a sustainable way (Lazonick, 2017; Chesbrough, 2019). In general, both small and mature companies are characterized by their own unique strengths and weaknesses when it comes to growth (Klein et al., 2021). Small companies may be more nimble and able to take advantage of new opportunities, but they also face greater uncertainty and risk. Large companies may grow more slowly, but they also have more stability and resources to weather market fluctuations (Weingaertner et al., 2014). Some of the factors that can influence small business growth include business strategy, financial management, market conditions, Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 The growth rates of earnings per share are determined as follows: (2) where: EPSn is earnings per share in n years after year 0. Earnings growth is calculated in relation to asset size (TA) since earnings can be negative and affect the results. The descriptive statistics of the growth indicators for both groups of companies are presented in Tables 1 and 2. However, due to the lack of the required data, these databases did not allow us to calculate the growth opportunity indicators for all company/year observations. In this paper, the growth of companies is represented by the growth of assets, equity, sales, and EPS. The growth rate of assets, equity, and sales for one, three, five, eight, and ten years is calculated by the following formula: (1) Where: n = 1, 3, 5, 8, 10, accordingly, and Xn denotes the total assets, equity, or sales at the end of n years after the year in which the total earnings equal X0. 0 0 n n XX XX + − = 0 0 n n EPS EPS EPS TA + − = Table 1: Statistical characteristics of future growth measures for the FTSE100 companies N Mean Median SD Min Max Q1 Q3 gTAS1 2356 0.071000 0.025900 0.13150 -0.171300 0.70280 0.000000 0.119000 gTAS3 2196 0.264700 0.161600 0.37740 -0.295300 2.09300 0.035700 0.370900 gTAS5 2034 0.506600 0.323000 0.66500 -0.318600 3.64840 0.096600 0.684600 gTAS8 1791 0.975400 0.593900 1.19370 -0.339400 6.20710 0.189600 1.259400 gTAS10 1634 1.372200 0.831400 1.62820 -0.304700 8.97480 0.284700 1.788000 gSA1 2372 0.066900 0.032200 0.11890 -0.228400 0.52180 0.000000 0.124200 gSA3 2210 0.229700 0.166100 0.32020 -0.360100 1.55060 0.029100 0.353100 gSA5 2049 0.418300 0.290900 0.52880 -0.422900 2.37110 0.057300 0.635300 gSA8 1807 0.786700 0.516500 0.91760 -0.378500 4.27950 0.129300 1.156400 gSA10 1650 1.084400 0.717000 1.22530 -0.394900 6.00300 0.201400 1.583200 gEQ1 2356 0.071800 0.026700 0.19810 -0.541000 1.12100 0.000000 0.133800 gEQ3 2195 0.251900 0.170600 0.49310 -0.999400 2.52830 0.000000 0.390700 gEQ5 2034 0.447600 0.302800 0.77040 -1.614700 4.34440 0.001200 0.675600 gEQ8 1791 0.831100 0.523500 1.25180 -3.754700 6.42340 0.050900 1.153000 gEQ10 1633 1.164100 0.702300 1.65470 -3.856600 7.82630 0.118600 1.630000 gEPS1 2303 0.000017 0.000001 0.00006 -0.000166 0.00032 0.000000 0.000023 gEPS3 2143 0.000057 0.000014 0.00014 -0.000320 0.00079 -0.000004 0.000077 gEPS5 1983 0.000100 0.000023 0.00022 -0.000354 0.00120 -0.000003 0.000123 gEPS8 1745 0.000183 0.000034 0.00039 -0.000317 0.00251 -0.000003 0.000203 gEPS10 1592 0.000247 0.000040 0.00053 -0.000318 0.00332 -0.000001 0.000261 Notes: The growth rates are in real numbers. They need to be multiplied by 100 to find the percentage. The more than one-year growth rates are total rates for those time horizons, not annualized Source: Author’s own work. Table 2: Statistical characteristics of future growth measures for the AIM companies N Mean Median SD Min Max Q1 Q3 gTAS1 1624 0.153800 0.0424 0.2844 -0.2454 1.5922 0.000000 0.2045 gTAS3 1466 0.597300 0.2838 0.9143 -0.3945 6.5258 0.077000 0.7428 gTAS5 1229 1.588500 0.6271 2.7831 -0.4624 21.6160 0.232800 1.5819 gTAS8 1074 2.338100 0.8463 4.0930 -0.4494 29.6548 0.315000 2.2797 tion within the sample is higher for AIM companies than for the FTSE100 companies – the standard deviation is higher, and the intervals between the minimum and maximum values are wider. The data presented in Tables 1 and 2 confirm that, as expected, assets, sales, equity, and EPS grow much faster in the companies listed on the AIM than in the FTSE100 companies; both the average and median growth rates are higher for all time horizons. The varia- Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 (5) where: Pg – value of growth potential, Ps – share price, EPS – earnings per share, ke – cost of equity. The higher the indicator, the greater the opportunity for growth, as reflected by the market. This model should not be used when company profits are negative. The next measure of growth opportunity, proposed by Otto (2000), is related to the concept of value added. The higher the indicators, the greater the potential for growth of the company being examined. (6) where: EVF – excess value of the company, MVE – market value of equity, BVE – book value of equity, and BVD – book value of debt. The second model represents the value that exceeds the value (EVE – Exceeding Value to Equity): (7) Where: EVE – excess value of equity. These models relate to growth opportunities included in share market prices. Growth companies are expected to pay low dividends and will retain a large share of investment revenues. For example, low dividend yields (dividend-price ratio D/P) can also be a proxy for high growth opportunities; the lower the ratio, the higher the growth opportunities. All growth potential measures are based on the idea that market prices reflect the companies’ prospects for growth. Tobin (1969) proposed a market value index of assets and their replacement costs as a measure of growth potential. (3) where: TQ – Tobin’s Q, MVC – market value of capital invested in the company, ARC – asset replacement cost. Due to the problems associated with determining the level of replacement costs, it is possible to modify the Tobin’s Q ratio in line with Danbolt et al. (2011): (4) where: TA – total assets, MVE – market value of equity; BVE, book value of equity. The higher the value of this index, the greater the opportunities for growth, assuming that the difference in the market value of the shares and the book value determines the growth potential included in the share market price. Another indicator used to evaluate growth prospects is the P/E ratio. The higher the P/E value, the greater the company’s growth potential. This ratio should not be used when company profits are negative. The models of Kester (1984) as well as Brealey and Myers (1981) were based on decomposing stock prices to the value of existing assets and the value of potential growth opportunities. N Mean Median SD Min Max Q1 Q3 gTAS10 936 3.126000 1.1412 5.6050 -0.3904 44.6250 0.401800 2.8920 gSA1 1566 0.142000 0.0597 0.2310 -0.2302 1.3191 0.000000 0.2116 gSA3 1413 0.504700 0.2884 0.7320 -0.4324 4.8911 0.087000 0.6320 gSA5 1263 1.010600 0.4953 1.6366 -0.4255 11.4243 0.182100 1.1202 gSA8 1043 1.777500 0.7981 2.8979 -0.4059 19.2373 0.339900 1.8821 gSA10 912 2.456200 0.9846 4.2731 -0.3996 28.7539 0.418500 2.6113 gEQ1 1624 0.160000 0.0461 0.3571 -0.5831 2.3496 0.000000 0.2107 gEQ3 1466 0.646300 0.2783 1.1209 -0.9542 7.6005 0.068900 0.7883 gEQ5 1308 1.255100 0.5338 2.2853 -1.8379 17.2332 0.149800 1.4035 gEQ8 1074 2.339900 0.9090 4.3753 -1.5143 37.9360 0.267300 2.4346 gEQ10 936 2.941100 1.1755 5.1514 -0.8459 45.1004 0.371100 2.9867 gEPS1 1521 0.000200 0.0000 0.0013 -0.0043 0.0100 0.000000 0.0003 gEPS3 1367 0.001200 0.0002 0.0044 -0.0092 0.0374 -0.000090 0.0010 gEPS5 1215 0.002300 0.0003 0.0073 -0.0075 0.0764 -0.000040 0.0015 gEPS8 1011 0.004200 0.0006 0.0124 -0.0079 0.0943 0.000005 0.0025 gEPS10 897 0.005720 0.0009 0.0163 -0.0078 0.1192 0.000040 0.0029 Note: as for Table 1 Source: Author’s own work. MVC TQ ARC = TA MVE BVE TQ TA +− = / Se g S P EPS k P KBM P − = ( ) ( ) g MVE BVD BVE BVD P EVF MVE BVD + − + =+ g MVE BVE P EVE MVE − = Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 (8) In the above equation, gEPS refers to the one-year, two-year or three-year growth of EPS, given by formula (7). denotes a one-year-lagged return on equity, is the natural logarithm of the market value, and GO0 represents one of six growth potential measures included in the analysis. According to Danbolt et al. (2011), the one-year equity return (ROE-1) was included in the regression to cover the impact of the average return on income. When the coefficient is negative and statistically significant, an average reversal is observed. The recent oneyear revenue growth is added to control the persistence of the revenue growth rate (if it is positive). However, both control variables contain similar information to some extent, and depending on whether the respective regression coefficient sign is positive or negative, each variable can explain the average reverse or residual income. The recent annual growth of total assets is Statistical analysis shows that most measures are higher in the mean and median for companies listed on the AIM compared to the FTSE100 companies (D/P is lower because smaller and younger companies do not pay dividends but reinvest earnings in growth projects). This result is accompanied by a higher variation between years (measured by standard deviation) and a wider range between the minimum and maximum ratios for companies traded on AIM market. The statistics of the surveyed sample confirm that the companies included in the FTSE100 index are larger than those included in the AIM index. The relationship between future earnings growth and the measurement of growth opportunities is also investigated in depth using a multivariate regression model proposed by Danbolt et al. (2011). In addition to measuring growth potential, the model also includes other factors associated with revenue growth identified in the literature. In each estimated linear regression, the measurement of the growth opportunities is only one of several explanatory variables. These estimates will therefore help to investigate whether the level of growth opportunity has an incremental impact on revenue growth, taking into account other factors that may be related to that growth. The regression models are presented in the following general formula: Table 3: Statistical characteristics of growth opportunity measures for the FTSE companies Table 4: Statistical characteristics of growth opportunity measures for the AIM companies N Mean Median SD Min Max Q1 Q3 TQ1 1511 2.23830 1.73090 1.61270 0.59790 10.43900 1.13420 2.76920 TQ2 1533 2.14420 1.71150 1.34900 0.61300 8.14310 1.13800 2.70400 P/E 1344 27.61540 18.95220 28.54120 3.31520 181.15900 11.91960 29.92010 MV/BV 1511 3.23530 2.39670 2.87410 0.25800 17.22690 1.21380 4.27470 D/P 1033 0.00027 0.00022 0.00019 0.00001 0.00109 0.00013 0.00035 KBM 781 0.99936 0.99969 0.00088 0.99418 0.99998 0.99929 0.99985 EVF 1511 0.35030 0.42230 0.36120 -0.67260 0.90420 0.11830 0.63890 EVE 1511 0.39890 0.59440 0.54080 -1.84480 0.96030 0.20870 0.77530 Note: as in Table 3 Source: Author’s own work. 1 0 2 1 3 0 4 0 5 0 ln it it it it it it it gEPS GO ROE EPS TA MV        − = + + +  +  + + 1 1 1 /ROE EPS EQ − − − = 0 1 0 1 0 0 0 11 , ,ln EPS EPS TA TA EPS TA MV TAS TA −− −− −−  =  = N Mean Median SD Min Max Q1 Q3 TQ1 2299 1.80530 1.47790 0.99710 0.79030 6.81330 1.15090 2.07880 TQ2 2292 1.86100 1.54920 0.97080 0.82280 6.50520 1.20410 2.15820 P/E 2286 19.59890 17.13200 11.63400 4.74720 87.68540 12.14560 23.33060 MV/BV 2299 3.16610 2.20160 3.11400 0.08460 21.09090 1.26320 3.75720 D/P 2098 0.00036 0.00034 0.00018 0.00001 0.00099 0.00023 0.00045 KBM 1628 0.99993 0.99994 0.00004 0.99978 0.99999 0.99991 0.99996 EVF 2299 0.32020 0.32370 0.26350 -0.26530 0.85320 0.13110 0.51860 EVE 2299 0.47060 0.57290 0.37170 -0.69640 0.99940 0.24760 0.75260 Note: P/E, D/P, and KBM are calculated only for positive earnings Source: Author’s own work. Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 The expectation of growth should be reflected by different measures, regardless of which growth opportunity indicator is applied. The matrix of Pearson correlation coefficients between various ratios that reflect growth opportunity is presented in Table 5. A positive correlation between all measures is expected, except for the one between D/P (which should be negative due to its reverse nature) and the other measures. The statistical significance of these correlation coefficients is assessed with the t-test and its significance. slightly more arbitrary, based on its strong prediction of future abnormal profits observed in the literature. Finally, the logarithm of the current market value, lnMV, is an indicator of company size. In the next section, the results of the statistical analysis are presented. Pooled OLS model was found the most suitable. In this section, the results of statistical analysis are presented for the companies on the FTSE100 and the AIM indexes. Table 5: Correlation matrix for various growth opportunity measures for the FTSE100 companies TQ1 TQ2 P/E P/BV D/P PgKBM PgEVF TQ2 0.92*** P/E 0.24*** 0.21*** P/BV 0.76*** 0.69*** 0.20*** D/P -0.32*** -0.24*** -0.31*** -0.21*** PgKBM 0.31*** 0.25*** 0.56*** 0.27*** -0.35*** PgEVF 0.86*** 0.81*** 0.25*** 0.72*** -0.36*** 0.37*** PgEVE 0.68*** 0.63*** 0.25*** 0.66*** -0.32*** 0.38*** 0.92*** Note: */**/*** The coefficients are significant at the 10% / 5% / 1% level Source: Author’s own work. the measures that represent the two distinctly different groups related to how they are calculated. Company growth can be measured by different means, but all of them should be correlated if the growth is consistent. If the company executes profitable investment projects, the growth of assets, equity, sales, and EPS should be strongly correlated. The correlation coefficients between all the different company growth measures are presented in Table 6. All measures are significantly correlated with each other and with the predicted sign. The absolute values of the correlation coefficients range from 0.21 to 0.92. A deeper analysis reveals clear rules between these relationships. All market-to-book-based measures (P/BV, TQ, EVF, EVE) are highly correlated with each other. There is also a very strong relationship between the two measures based on the price-to-earnings concept (P/E and KBM). The correlation is weaker between Table 6: Correlation coefficients between various future growth measures for the FTSE100 companies gTAS1 gSA1 gEQ1 gSA1 0.470*** gEQ1 0.521*** 0.304*** gEPS1 0.222*** 0.207*** 0.221*** gTAS3 gSA3 gEQ3 gSA3 0.634*** gEQ3 0.602*** 0.431*** gEPS3 0.196*** 0.307*** 0.225*** gTAS5 gSA5 gEQ5 gSA5 0.740*** gEQ5 0.692*** 0.535*** gEPS5 0.230*** 0.342*** 0.272*** gTAS8 gSA8 gEQ8 gSA8 0.728*** gEQ8 0.693*** 0.545*** gEPS8 0.271*** 0.381*** 0.275*** gTAS10 gSA10 gEQ10 gSA10 0.726*** gEQ10 0.754*** 0.570*** gEPS10 0.284*** 0.318*** 0.278*** Note: */**/*** The coefficients are significant at the 10% / 5% / 1% level Source: Author’s own work. Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 horizons. Furthermore, EPS growth is also strongly related to firm size (measured by lnMV0) – the correlation coefficients in all regressions are statistically significant at the 1% level. There is also evidence of persistence in earnings rather than the effect of mean reversion, which is demonstrated by the positive signs of statistically significant coefficients at and in some regressions. Additionally, the results in columns 9 and 10 demonstrate that the proportion of the variance in EPS that is predictable based on the independent variable (coefficient of determination) rises with the time horizon. In the second step, the same analysis was repeated companies traded on the alternative exchange of the LSE. The correlation coefficients between various growth opportunity measures in AIM-listed companies are presented in Table 7. All correlation signs are positive. The highest significant correlation is between total assets growth and sales growth or equity growth rate in each of the five periods considered (except for one-year growth rates, with correlation coefficients that exceed 0.6 or 0.7). Sales growth rates are also quite strongly correlated with equity growth. Earnings growth rates are more independent of size growth measures. A relative change in EPS indicates the growth of a company’s future value. The results of the regression based on equation (8) and models related to the determinants of future earnings growth are reported in Appendinx 1. The incremental impact of the market level of growth opportunity is reported in column 8. Shaded cells indicate that the coefficient of the growth opportunity measure is significant and of the predicted sign. Almost all measures perform very well in every time horizon. The only exception is the dividend yield (D/P), which is not significant in the 3, 5, and 10-year time Table 7: Correlation matrix for various growth opportunity measures for the AIM companies TQ1 TQ2 P/E P/BV D/P PgKBM PgEVF TQ2 0.83*** P/E 0.28*** 0.26*** P/BV 0.87*** 0.73*** 0.27*** D/P -0.34*** -0.31*** -0.35*** -0.32*** PgKBM 0.15*** 0.11*** 0.17*** 0.15*** -0.11*** PgEVF 0.78*** 0.74*** 0.26*** 0.74*** -0.38*** 0.15*** PgEVE 0.62*** 0.59*** 0.23*** 0.64*** -0.34*** 0.14*** 0.93*** Note: */**/** The coefficients are significant at the 10% / 5% / 1% level Source: Author’s own work. measures (P/BV, TQ, EVF, EVE). There is also a relatively strong relationship between D/P and other measures. The correlation coefficients between all the different measures of company growth are presented in Table 8. For the AIM companies, all measures are significantly correlated with each other and are of the predicted sign. The absolute values of the correlation coefficients range from 0.11 to 0.87. The highest correlation is observed between all market-to-book-based Table 8: Correlation coefficients between various future growth measures for the AIM companies gTAS1 gSA1 gEQ1 gSA1 0.564*** gEQ1 0.753*** 0.414*** gEPS1 0.212*** 0.243*** 0.178*** gTAS3 gSA3 gEQ3 gSA3 0.623*** gEQ3 0.746*** 0.500*** gEPS3 0.237*** 0.228*** 0.177*** gTAS5 gSA5 gEQ5 gSA5 0.604*** gEQ5 0.746*** 0.465*** gEPS5 0.372*** 0.359*** 0.258*** gTAS8 gSA8 gEQ8 gSA8 0.666*** Monika Bolek, Agata Gniadkowska-Szymańska, Piotr Pietraszewski Unveiling growth divergence on LSE: FTSE100 vs. AIM listed companies Financial Internet Quarterly 2025, vol. 21 / no. 1 Sample Const. ROE-1 ΔEPS0 ΔTA0 lnMV0 GO0 R2 % Adj. R2 % F-stat. Wald Explained variable: One-year EPS growth TQ1 1311 0.077*** -0.0001 0.016 -6e-05 -0.018*** 0.0180*** 5.2 4.9 14.400*** 2.02*** TQ2 1328 0.068*** 8e-05 0.012 -3e-05 -0.016*** 0.0150*** 3.0 2.7 8.240*** 2.14*** P/E 1216 0.082*** 0.0002 -0.066 0.0030 -0.015*** 0.0005*** 2.3 1.9 5.800*** 2.60*** MV/BV 1322 0.088*** -0.0002* 0.020 -7e-05 -0.019*** 0.0110*** 5.6 5.2 15.500*** 1.98*** D/P 950 0.133*** 0.0001 -3.395** 0.0100** -0.018*** -84.2400*** 3.3 2.8 6.490*** 2.48*** KBM 1368 0.099*** -3e-05 0.007 -3e-05 -0.018** 0.0530*** 3.7 3.3 10.400** 2.14*** EVF 1311 0.096*** -0.0002 0.016 -6e-05 -0.019*** 0.0760*** 4.4 4.0 11.900*** 2.13*** EVE 1321 0.104*** -0.0002* 0.017 -6e-05 -0.018*** 0.0410*** 3.4 3.0 9.240*** 2.07*** Explained variable: Three-year EPS growth TQ1 1172 0.336*** -0.0020*** 1.095*** -0.0030*** -0.073*** 0.0540*** 12.2 11.8 32.400*** 4.09*** TQ2 1190 0.303*** -0.0020*** 1.025*** -0.0030*** -0.071*** 0.0720*** 12.4 12.0 33.500*** 3.72*** P/E 1086 0.314*** 0.0005 -0.001 -0.0040 -0.061*** 0.0020*** 5.8 5.4 13.300*** 4.34*** MV/BV 1181 0.386*** -0.0020*** 1.041*** -0.0030*** -0.081*** 0.0350*** 14.0 13.7 38.340*** 4.19*** D/P 841 0.509*** 0.0003 3.582 -0.0100 -0.081*** -192.9000*** 7.3 6.7 13.170*** 4.57*** KBM 1220 0.432** -0.0020 1.017 -0.0030*** -0.079*** 0.1790** 12.2 11.9 33.900*** 4.01*** EVF 1172 0.407*** -0.0020*** 1.058*** -0.0030*** -0.082*** 0.2750*** 13.8 13.5 37.400*** 4.42*** EVE 1175 0.456*** 0.0020*** 0.990*** -0.0030*** -0.085*** 0.1570*** 13.2 12.8 35.400*** 4.32*** Variable explained: Five-year EPS growth TQ1 1028 0.668*** -0.0020*** 0.025 -0.0002 -0.166*** 0.1310*** 15.0 14.6 36.100*** 4.65*** TQ2 1045 0.504*** -0.0020*** 0.120 -0.0004 -0.144*** 0.1600*** 16.4 16.0 40.700*** 4.77*** P/E 960 0.567*** 0.0020*** 0.028 -0.0020 -0.118*** 0.0030*** 7.5 7.1 15.600*** 5.67*** MV/BV 1034 0.718*** -0.0030*** 0.007 -0.0001 -0.158*** 0.0650*** 13.6 13.2 32.300*** 5.00*** D/P 741 0.872*** 0.0007 18.090** -0.0530** -0.141*** -404.5000*** 10.3 9.7 16.900*** 5.06*** KBM 1067 0.831*** -0.0020*** -0.016 -8e-05 -0.166*** 0.3810*** 12.7 12.3 30.800*** 5.39*** EVF 1028 0.833*** -0.0020*** 0.004 -0.0001 -0.179*** 0.5330*** 14.7 14.2 35.100*** 4.91*** EVE 1026 0.896*** -0.0020*** -0.070 6e-05 -0.177*** 0.2800*** 12.8 12.4 29.900*** 5.20*** Explained variable: Ten-year EPS growth TQ1 753 1.356*** -0.0002 2.249 -0.0070 -0.373*** 0.3070*** 16.0 15.4 28.400*** 5.66*** TQ2 766 1.339*** -0.0020 2.115 -0.0060 -0.407*** 0.4170*** 19.3 18.8 36.300*** 7.13*** P/E 699 1.050*** 0.0040** 2.510 -0.0600 -0.214*** 0.0060*** 4.8 4.1 7.025*** 6.86*** MV/BV 759 1.576*** -0.0030** 1.389 -0.0040 -0.382*** 0.1620*** 17.2 16.6 31.200*** 5.99*** D/P 524 1.957*** 0.0010 -50.150*** 0.1460*** -0.324*** -978.3000*** 11.4 10.5 13.270*** 6.66*** KBM 782 1.972*** -0.0020 1.802 -0.0005 -0.425*** 0.9520*** 14.0 13.4 25.180*** 7.10*** EVF 753 1.817*** -0.0010 1.888 -0.0060 -0.414*** 1.1550*** 14.4 13.8 25.070*** 6.31*** EVE 752 2.161*** -0.0030* 1.392 -0.0040 -0.455*** 0.6190*** 13.9 13.3 24.100*** 6.92*** Appendinx 2: Determinants of future earnings growth (AIM) – Pooled OLS Note: */**/*** The coefficients or F-statistic are significant at the 10% / 5% / 1% level Source: Author’s own work.