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№ 3/2019
1Institute for Economics and Forecasting, NAS of Ukraine
Estimating risk exposure of Ukrainian enterprises using methods of corporate finance
Ekon. prognozuvannâ 2019; 3:40-59 | https://doi.org/10.15407/eip2019.03.040 |
ABSTRACT ▼
Weak market infrastructure makes the data provided by Ukrainian stock exchanges obscure and unreliable, which ultimately led to a loss of Ukraine's "frontier market" status since 2015. This, in turn, makes risk exposure estimation of Ukrainian enterprises, especially using CAPM and its modifications, a rather complex and creative process, which is highly dependent on the qualification of the expert making such assessment. The aims of this research are to itemize the main issues with calculating beta-coefficient using Ukrainian data and to offer possible ways of mitigating or avoiding them.
Using a set of Ukrainian engineering enterprises the author demonstrates the main limitations of the current statistics provided by Ukrainian stock exchange (namely, fragmentary data with dubious representativeness), gives a condensed characterization of reasons for such state of affairs, and proposes to use methods of calculation based on open source corporate data instead. The best results were achieved by using a method based on adjusting existing average industry-based beta coefficient to enterprise's individual financial leverage. The author hypothesizes that in order to receive results more representative for Ukraine's situation one should use industry average beta, calculated based on Ukrainian data instead of worldwide averages, available in the open sources.
The methodical approaches to calculating beta coefficient, examined in this paper, and their modifications in order to fit Ukrainian conditions better, could potentially be used in order to access risk exposure of enterprises, functioning on other frontier or developing markets. Creating an open database of industry-based average betas, calculated on basis of Ukrainian data, could be a valuable alternative to currently available sources for evaluating assets on non-developed markets.
Keywords: CAPM, beta-coefficient, frontier market; stock price; ROE
JEL: C18, C81, G12
Article in Ukrainian (pp. 40 - 59) | Download | Downloads :577 |
REFERENCES ▼
2. Harvey, C.R. (2005). 12 Ways to Calculate the International Cost of Capital. Retrieved from faculty.fuqua.duke.edu/~charvey/Teaching/BA456_2006/Harvey_12_ways_to.pdf
3. Roggi, O., Gianozzi, A., Baglioni, T. (2017). Valuing emerging markets companies: New approaches to determine the effective exposure to country risk. Research in International Business and Finance, 39, 553-567. doi: doi.org/10.1016/j.ribaf.2016.07.028
4. Pereiro, L.E. (2006). The Practice of Investment Valuation in Emerging Markets: Evidence from Argentina. Journal of Multinational Financial Management, 16 (2), 160-183. doi: doi.org/10.1016/j.mulfin.2005.06.001
5. Tereshchenko, O., Voloshaniuk, N., Savchuk, D. (2019). Rate of Costs on Investment Capital in Emerging Markets. Society. Integration. Education. Proceedings of the International Scientific Conference, VI (May 24th - 25th), 665-674. doi: doi.org/10.17770/sie2019vol6.3957 [in Ukrainian].
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7. Kerimov, P. (2019). Features of risk-free rate estimation in Ukraine. Finansy Ukrayiny – Ukraine's Finance, 8, 61-74 [in Ukrainian].
8. National Committee's on Securities and Fund Market Annual report, 2017. Retrieved from www.nssmc.gov.ua/documents/rtchniy-zvt-nktspfr-za-2017-rk/ [in Ukrainian].
9. Damodaran, A. Variables used in dataset. URL: people.stern.nyu.edu/adamodar/New_Home_Page/datafile/variable.htm
10. Law of Ukraine 'On joint stock companies'. Retrieved from zakon.rada.gov.ua/laws/show/514-17 [in Ukrainian].
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№ 2/2022
1Institute for Economics and Forecasting, NAS of Ukraine
COST OF CREDIT AND PROFITABILITY OF LARGE INDUSTRIAL FIRMS IN UKRAINE
Ekon. prognozuvannâ 2022; 2:53-73 | https://doi.org/10.15407/eip2022.02.053 |
ABSTRACT ▼
Lending in Ukraine is usually studied from the creditor’s perspective, and based on the macroeconomic-level data, due to statistics availability. This potentially leaves out the problems that exist on microeconomic level, and leads to one-sided conclusions regarding, for instance, justification for certain levels of cost of credit based exclusively on minimal required profitability. In order to complement these conclusions, it is expedient to use microeconomic data-based analysis performed on a representative selection of firms, and thus the aim of this study is to evaluate credit availability for large firms in Ukraine in 2006-2020.
Within the framework of the designated aim, liabilities structure, expected costs of financial resources, both credit and equity-based, have been analyzed for a selection of firms, and then compared to their respective profitability ratios. The main conclusion is that an average large industrial firm in Ukraine in 2006-2020 was not profitable enough to attract either loans or investments on market terms, and it is unlikely the situation has changed now. Individual firms, mainly of agricultural, mining, mechanical engineering, food and trade industries, are the exception to this rule. The reason for this is abnormally high profitability volatility, and in many cases – loss-making of large industrial firms, which in turn raise their risks (and thus the cost of financial resources for them); in other words, an average industrial firm has to pay elevated cost for credit due to its low creditworthiness.
The practical conclusion is that the average large industrial firm in Ukraine is maladapted to market-based economy, and thus they should not be the centerpiece for planning of an economic development policy. Due to the tendency of such firms to bias any form of aggregated statistics in their favor, it is advisable to exclude them altogether, and aim to use representative selections based on medium and small firms instead. In particular, such approach must be used for aggregation of industry-specific capital structure, as well as for evaluation of costs of credit, equity and of their underlying risks. This would allow for setting a better scale in estimation of costs of financial resources.
The article was prepared within the research project on "The relationship between financial depth and economic growth in Ukraine" (State Registration No 0121U110766).
Keywords:loans, trade credit, cost of capital, cost of credit, return on capital
JEL: G31, G32
Article in Ukrainian (pp. 53 - 73) | Download | Downloads :109 |
REFERENCES ▼
2. Kerimov, Pavlo (2019). Estimating risk exposure of Ukrainian enterprises using methods of corporate finance. Ekon. prognozuvannâ – Economy and forecasting, 3, 40-59. doi.org/10.15407/eip2019.03.040 [in Ukrainian].
3. Ruda, O.L. (2018). Loans as a ground for interrelations between commercial banks and enterprises. Investytsyi: praktyka i dosvid – Investment: practice and experience, 9, 22-25 [in Ukrainian].
4. Sydorenko, V.A. (2020). Ways of intensification of bank-led investment crediting of real sector of economy. Naukoviy Visnyk NLTU Ukrayiny – National Forestry University of Ukraine Scientific Bulletin, 1: 30, 104-108 [in Ukrainian].
5. Kerimov, Pavlo, Zymovets, Vladyslav (2021). Quasi-Risk and Fraudulent Financing Models: The Case of Firms with Negative Equity in Ukraine. Economic Studies (Ikonomicheski Izsledvania), 8, 48-68.
6. Kozyuk ,V.V. (2020). The cult of predatory loans. Why low credit rates do not help to "jump-start the economy". Vox Ukraine. Retrieved from finance.liga.net/ekonomika/article/kult-hischnogo-kredita-pochemu-nizkie-stavki-ne-pomogayut-zapustit-ekonomiku [in Ukrainian].
7. Rekova N.V., Dyatlova Y.V. (2019). Development of lending towards real sector of economy: focus on the Agro-Industrial Complex as a priority industry. Fynansoviy prostir – Financial space, 1 (33), 8-17 [in Ukrainian].
8. Pasynovich I.I., Dmytruk V.O. (2019). Crediting real sector of regional economy: current state, problems and perspectives. Regional'na ekonomika – Regional economy, 3 (137), 42-49. doi.org/10.36818/2071-4653-2019-3-7 [in Ukrainian].
9. Vlasyuk S.A., Bondarenko N.V. (2018). Bank loans to real sector of economy. Zbirnyk naukovykh prats' Umans'koho natsional'noho universytetu sadivnytstva – Uman National University of Horticulture Scientific Bulletin, 93: 2 (Economic sciences), 32-41. doi.org/10.31395/2415-8240-2018-93-2-32-40 [in Ukrainian].
10. NBU board resolution No. 18 from February 24, 2020, "On banking system operation during martial law". Retrieved from bank.gov.ua/ua/legislation/ Resolution_24022022_18 [in Ukrainian].
11. National bank have issued 50 billions of hryvnas. Slovo i Dilo – Word and a business. Retrieved 08.07.2022 from www.slovoidilo.ua/2022/04/28/ novyna/ ekonomika/naczbank-kvitni-proviv-emisiyu-50-milyardiv-hryven [in Ukrainian].
12. Moiseyev, V. Question of 25%: why NBU, banks and Ministry of finance conflict over discount rate? thepage.ua. Retrieved 09.06.2022 from thepage.ua/ua/economy/chomu-nbu-banki-ta-minfin-konfliktuyut-z-privodu-oblikovoyi-stavki [in Ukrainian].
13. Shyshkov, S.Y. (2022). Effects of implementing martial law on capital markets in Ukraine. Ukr. socìum – Ukrainian society, 1 (80), 63-86. doi.org/10.15407/socium2022.01.063 [in Ukrainian].
14. NBU board resolution No. 23 from February 23, 2022, "On certain issues concerning activities of banks of Ukraine and bank groups". Retrieved from bank.gov.ua/ua/legislation/Resolution_25022022_23 [in Ukrainian].
15. NBU board resolution No. 41 from March 7, 2022, "On compiling and submitting financial statements during the martial law". Retrieved from bank.gov.ua/ua/legislation/Resolution_07032022_41 [in Ukrainian].
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20. US 10 year treasury yield. Retrieved from www.cnbc.com/quotes/US10Y
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