Why do football clubs fail financially? A financial distress prediction model for European professional football industry

English version

Autoři: David Alaminos ^aff001; Manuel Ángel Fernández ^aff001
Působiště autorů: Department of Finance and Accounting, Universidad de Málaga, Málaga, Spain ^aff001; PhD Program in Mechanical Engineering and Energy Efficiency, Universidad de Málaga, Málaga, Spain ^aff002
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0225989

Souhrn

The study of financial distress has been the focus of financial research in recent decades and has led to the development of models for predicting financial distress that help assess the financial situation and the risks faced by companies. These models have focused exclusively on industrial and financial companies. However, a specific model that reflects the special characteristics of the football industry has not yet been created. Since recently the governing bodies of the football industry have increased the financial control of the clubs, as in the case of UEFA with the approval of the Financial Fair Play Regulation and demand a pronouncement on going concern in the annual financial statements of clubs as well as presenting a break-even deficit caused by losses, it seems necessary to have a model adapted to the characteristics of this industry. The present study provides a new model of prediction of financial distress for the football industry with an accuracy that exceeds 90%. It also offers a vision of the challenges facing the football industry in financial matters, helping the different interest groups to assess the financial solvency expectations of the clubs.

Klíčová slova:

Europe – Economics – Salaries – Finance – Sports – Regulations – Bankruptcy

Zdroje

1. Altman EI, Iwanicz-Drozdowska M, Laitinen E, Suvas A (2017) Financial distress prediction in an International context: A review and empirical analysis of Altman's Z-Score model. Journal of International Financial Management & Accounting, 28 (2), 131–171. https://doi.org/10.1111/jifm.12053

2. Union of European Football Associations, UEFA (2017). Financial Report 2016/2017. 42nd Ordinary UEFA Congress.

3. Storm RK, Nielsen K (2012) Soft budget constraints in professional football, European Sport Management Quarterly, 12(2), 183–201. https://doi.org/10.1080/16184742.2012.670660

4. Drut B, Raballand G (2012) Why does financial regulation matter for European professional football clubs? International Journal of Sport Management and Marketing, 11(1/2), 73–88. https://doi.org/10.1504/ijsmm.2012.045488

5. Union of European Football Associations, UEFA (2018) Club Licensing and financial fair play regulations, Edition 2018.

6. Deloitte (2018). Annual Review of Football Finance 2018.

7. Preuss H, Haugen KK, Schubert M (2014) UEFA financial fair play: the curse of regulation. EJSS-Journal of Sports Law & Economics, 2(1), 33–51. https://doi.org/10.12863/ejssax2x1-2014x1

8. Müller JC, Lammert J, Hovemann G (2014) The Financial Fair Play Regulations of UEFA: An Adequate Concept to Ensure the Long-Term Viability and Sustainability of European Club Football? International Journal of Sport Finance, 7(2), 117–140. https://doi.org/10.2139/ssrn.2853349

9. Vöpel H (2011) Do We Really Need Financial Fair Play in European Club Football? CESifo DICE Report 9 (3), 54–59.

10. Union of European Football Associations, UEFA (2009) Club Licensing and financial fair play regulations, Edition 2009.

11. Barajas Á, Rodríguez P, (2014) Spanish football in need of financial therapy: Cut expenses and inject capital. International Journal of Sport Finance, 9, 73–90. https://doi.org/10.2139/ssrn.2392533

12. Buraimo B, Simmons R, Szymanski S (2006) English Football. Journal of Sports Economics, 7(1), 29–46. https://doi.org/10.1177/1527002505282911

13. Ascari G, Gagnepain P (2006) Spanish Football. Journal of Sports Economics, 7(1), 76–89. https://doi.org/10.1177/1527002505282869

14. Baroncelli A, Lago U (2006) Italian Football. Journal of Sports Economics, 7(1), 13–28. https://doi.org/10.1177/1527002505282863

15. Frick B, Prinz J (2006) Crisis? What Crisis? Football in Germany. Journal of Sports Economics, 7(1), 60–75. https://doi.org/10.1177/1527002505282868

16. Andreff W (2007) French Football: A Financial Crisis Rooted in Weak Governance. Journal of Sports Economics, 8(6), 652–661. https://doi.org/10.1177/1527002506297021

17. Sayari N, Mugan CS (2016) Industry specific financial distress modeling. BRQ Business Research Quarterly, 20 (1), 45–62. https://doi.org/10.1016/j.brq.2016.03.003

18. Breuer M, Forrest D (2018) The Palgrave Handbook on the Economics of Manipulation in Sport. Palgrave Macmillan. https://doi.org/10.1007/978-3-319-77389-6

19. Jones S, Johnstone D, Wilson R (2017) Predicting corporate bankruptcy: An evaluation of alternative statistical frameworks. Journal of Business Finance & Accounting, 44(1–2), 3–34. https://doi.org/10.1111/jbfa.12218

20. Beaver WH (1966) Financial ratios as predictors of failure. Journal of Accounting Research, 4, Empirical Research in Accounting, 71–111. http://dx.doi.org/10.2307/2490171

21. Altman EI (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23, 589–609. http://dx.doi.org/10.2307/2978933

22. Zmijewski ME (1984) Methodological issues related to the estimation of financial distress prediction model. Journal of Accounting Research, 22, 59–82. http://dx.doi.org/10.2307/2490859

23. Altman E (1993) Corporate financial distress and bankruptcy, Second Edition, John Wiley & Sons, New York.

24. Jones S, Hensher DA (2004) Predicting firm financial distress: A mixed logit model. The Accounting Review, 79(4), 1011–1038. https://doi.org/10.2308/accr.2004.79.4.1011

25. Xie C, Luo C, Yu X (2011) Financial distress prediction based on SVM and MDA methods: the case of Chinese listed companies. Quality & Quantity, 45, 671–686. https://doi.org/10.1007/s11135-010-9376-y

26. Lin T (2009) A cross model study of corporate financial distress prediction in Taiwan: Multiple discriminant analysis, logit, probit and neural networks models. Neurocomputing, 72, 3507–3516. https://doi.org/10.1016/j.neucom.2009.02.018

27. Bae JK (2012) Predicting financial distress of the South Korean manufacturing industries. Expert Systems with Applications, 39, 9159–9165. https://doi.org/10.1016/j.eswa.2012.02.058

28. Bao X, Tao Q, Fu H (2015) Dynamic financial distress prediction based on Kalman filtering. Journal of Applied Statistics, 42(2), 292–308. https://doi.org/10.1080/02664763.2014.947359

29. Kim SY, Upneja A (2014) Predicting restaurant financial distress using decision tree and AdaBoosted decision tree models. Economic Modelling, 36, 354–362. https://doi.org/10.1016/j.econmod.2013.10.005

30. Beech J, Horsman S, Magraw J (2010) Insolvency events among English football clubs. International Journal of Sports Marketing and Sponsorship, 11 (3), 53–66. https://doi.org/10.1108/IJSMS-11-03-2010-B006

31. Szymanski S, (2017). Entry into exit: insolvency in English professional football. Scottish Journal of Political Economy, 64(4), 419–444. https://doi.org/10.1111/sjpe.12134

32. Szymanski S (2010) The Financial Crisis and English Football: The Dog That Will Not Bark. International Journal of Sport Finance, 5(1), 28–40.

33. Plumley D, Wilson R, Ramchandani G (2014) Towards a model for measuring holistic performance of professional Football clubs. Soccer & Society, 18(1), 16–29. https://doi.org/10.1080/14660970.2014.980737

34. Wilson R, Ramchandani G, Plumley D (2018) Parachute payments in English football: Softening the landing or distorting the balance? Journal of Global Sport Management, 3(4), 1–18. https://doi.org/10.1080/24704067.2018.1441740

35. Ascari G, Gagnepain P (2007) Evaluating Rent Dissipation in the Spanish Football Industry. Journal of Sports Economics, 7(1), 468–490. https://doi.org/10.1177/1527002506292582

36. Rico M, Puig F (2015) Why do Spanish football clubs success in their insolvency proceedings? Universia Business Review, 48(4), 52–85.

37. Buraimo B, Paramio JL, Campos C (2010) The impact of televised football on stadium attendances in English and Spanish league football. Soccer & Society, 11 (4), 461–474. https://doi.org/10.1080/14660971003780388

38. Barajas Á, Rodríguez P, (2010) Spanish football clubs’ finances: Crisis and player salaries. International Journal of Sport Finance, 5, 52–66.

39. Dietl HM, Franck E (2007) Governance Failure and Financial Crisis in German Football. Journal of Sports Economics 8(6), 662–69. https://doi.org/10.1177/1527002506297022

40. Budzinski O, Müller, A (2013) Fnanzregulierung und internationale Wettbewerbsfähigkeit: Der Fall Deutsche Bundesliga. Ilmenau Economics Discussion Papers, No. 82 echn. Univ., Inst. für Volkswirtschaftslehre, Ilmenau. http://hdl.handle.net/10419/76812

41. Symanski S, Weimar D (2019) Insolvencies in Professional Football: A German Sonderweg? International Journal of Sport Finance, 14(4), 54–88. https://doi.org/10.32731/IJSF.141.022019.05

42. Nicoliello M, Zampatti D (2016) Football clubs’ profitability after the Financial Fair Play regulation: evidence from Italy. Sport, Business and Management. 6(4), 460–475. https://doi.org/10.1108/SBM-07-2014-0037

43. Scarfato V, Dimitropoulos P (2018) Human capital and financial performance in professional football: the role of governance mechanisms. Corporate Governance: The international journal of business in society, 18(2), 289–316. https://doi.org/10.1108/CG-05-2017-0096

44. Andreff W (2015) Club governance and budget constraints in European and French football. Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01305710, HAL.

45. Scelles N, Szymanski S, Dermit-Richard N (2018) Insolvency in French soccer: The case of payment failure. Journal of Sport Economics, 19(5), 603–624. https://doi.org/10.1177/1527002516674510

46. Galariotis E, Germain C, Zopounidis C (2018) A combined methodology for the concurrent evaluation of the business, financial and sports performance of football clubs: the case of France. Annals of Operations Research, 266(1–2), 589–612. https://doi.org/10.1007/s10479-017-2631-z

47. Ecer F, Boyukaslan A (2014) Measuring performances of football clubs using financial ratios: The gray relational analysis approach. American Journal of Economics, 4(1), 62–71. https://doi.org/10.5923/j.economics.20140401.06

48. Sakınç İ (2014) Using grey relational analysis to determine the financial performance of Turkish football clubs. Journal of Economics Library, 1(1), 22–33. http://dx.doi.org/10.1453/jel.v1i1.160

49. Madden P (2015) Welfare Economics of “Financial Fair Play” in a Sports League with Benefactor Owners. Journal of Sports Economics, 16(2), 159–184. https://doi.org/10.1177/1527002512465759

50. Sass M (2016) Glory Hunters, Sugar Daddies, and Long-Term Competitive Balance Under UEFA Financial Fair Play. Journal of Sports Economics, 17(2), 148–158. https://doi.org/10.1177/1527002514526412

51. Frank E, Lang M (2014) A theoretical analysis of the influence of money injections on risk taking in football clubs. Scottish journal of political economy 61 (4), 430–454. https://doi.org/10.1111/sjpe.12052

52. Bachmaier B, Lammert J, Plumley D, Wilson R, Hovemann G (2018) Regulatory intensity in English and German professional football. Sport, Business and Management, 8(3), 276–297. https://doi.org/10.1108/SBM-02-2017-0012

53. Frank E (2018) European Club Football after “Five Treatments” with Financial Fair Play—Time for an Assessment. International Journal of Financial Studies 6 (4), 97. https://doi.org/10.3390/ijfs6040097

54. Barajas A, Castro-Limeres O, Gasparetto T (2017) Application of MCDA to Evaluate Financial Fair Play and Financial Stability in European Football Clubs. Journal of Sports Economics & Management, 7(3), 143–164.

55. Ramchandani G, Plumley D, Boyes S, Wilson R (2018) A longitudinal and comparative analysis of competitive balance in five European football leagues. Team Performance Management: An International Journal. https://doi.org/10.1108/TPM-09-2017-0055

56. Soto-Pineda JA (2017) El control de ayudas públicas en la Unión Europea sobre los clubes del fútbol español. Revista de Derecho, 48, 54–130. https://doi.org/10.14482/dere.48.10142

57. Alaminos D, del Castillo A, Fernández MÁ (2016) A global model for bankruptcy prediction. PLoS ONE, 11(11), e0166693. http://dx.doi.org/10.1371/journal.pone.0166693 27880810

58. Geng R, Bose I, Chen X (2015) Prediction of financial distress: An empirical study of listed Chinese companies using data mining. European Journal of Operational Research, 241(1), 236–247. https://doi.org/10.1016/j.ejor.2014.08.016

59. Platt HD, Platt MB (2008). Financial distress comparison across three global regions. Journal of Risk Financial Management, 1(1), 129–162. https://doi.org/10.3390/jrfm1010129

60. Hair JF, Anderson RE, Tatham RL, Black WC (1999) Análisis multivariante, 5a edición. Editorial Prentice Hall, Madrid.

61. Grippo L, Manno A, Sciandrone M (2016) Decomposition techniques for multilayer perceptron training. IEEE Transactions on Neural Networks and Learning Systems, 27 (11), 2146–2159. https://doi.org/10.1109/TNNLS.2015.2475621 26415186

62. Flórez R, Fernández JM (2008) Las redes neuronales artificiales: fundamentos teóricos y aplicaciones prácticas. Oleiros (La Coruña): Netbiblo.

63. Ramchoun H., Idrissi MAJ, Ghanou Y, Ettaouil M (2016) Multilayer perceptron: Architecture optimization and training. International Journal of Interactive Multimedia and Artificial Intelligence, 4(1), 26–30. http://dx.doi.org/10.9781/ijimai.2016.415

64. Yang JY, Wang JS, Chen YP (2008) Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers. Pattern Recognition Letters, 29(16), 2213–2220. https://doi.org/10.1016/j.patrec.2008.08.002

65. Fallahpour S, Lakvan EN, Zadeh MH (2018) Using an ensemble classifier based on sequential floating forward selection for financial distress prediction problem. Journal of Retailing and Consumer Services, 34, 159–167. https://doi.org/10.1016/j.jretconser.2016.10.002

66. Liang D, Tsai CF, Dai AJ, Eberle W (2018) A novel classifier ensemble approach for financial distress prediction. Knowledge and Information Systems, 54 (2), 437–462. https://doi.org/10.1007/s10115-017-1061-1

67. Jabeur SB, Fahmi Y (2018) Forecasting financial distress for French firms: a comparative study. Empirical Economics, 54(3), 1173–1186. https://doi.org/10.1007/s00181-017-1246-1

68. Amani FA, Fadlalla AM (2017) Data mining applications in accounting: A review of the literature and organizing framework. International Journal of Accounting Information Systems, 24(C), 32–58. https://doi.org/10.1016/j.accinf.2016.12.004

Why do football clubs fail financially? A financial distress prediction model for European professional football industry

Souhrn

Klíčová slova:

Zdroje

PLOS One

Aktuální možnosti diagnostiky a léčby litiáz