Analysis of the F-Score Indicator for Listed Companies from the IT and Video Games Industries

Bartłomiej Pilch

Abstract


Theoretical background: The F-Score is a model based on the scoring method. Its high values indicate solid financial foundations of a given company, and in a simplified way they make it possible to distinguish units that are attractive in terms of selection for the investment portfolio. Since the publication of the original version of this model by Piotroski in 2000, many studies have been carried out to verify its effectiveness in various markets. In the vast majority of cases, their results indicated the advisability of using this model. However, the Polish stock exchange was not often taken into account in this context, therefore, it seems that such a study may provide valuable information for Polish investors.

Purpose of the article: The main premise for undertaking research on the assessment of the effectiveness of the F-Score model was the existence of a small number of studies focusing on the Polish stock market in this area. In addition, the specific selection of companies representing two industries may significantly affect the results of such a study, also providing information about the effectiveness of the F-Score model in relation to selected economic sectors. Therefore, the aim of the study is to verify the effectiveness of the F-Score indicator on the example of companies from the IT and video game industries listed on the Warsaw Stock Exchange (WSE).

Research methods: The main methods used in this analysis are descriptive statistics (arithmetic mean, median, standard deviation, coefficient of variation). They were used to analyze the differentiation of the F-Score values, both between sectors and over time, as well as to assess the effectiveness of the title model (in the form of a comparison of rates of return with financial data for the previous year). The research was based on the financial data of companies listed on the WSE Main Market and NewConnect from the video games and IT industries. The analysis covered the period 2017–2019.

Main findings: Based on the study, the following conclusions were drawn: 1) there is a differentiation of the F-Score values both between the video game and IT industries, and also over time; 2) higher values of the B/M ratio did not affect the higher rates of return on shares in the following year; 3) higher values of the F-Score model influenced higher average rates of return on shares in the following year. Thus, the effectiveness of the F-Score model was confirmed on the basis of companies listed on the WSE. It also indicated the need to take into account the differentiation in terms of industries. These conclusions can be useful in the decision-making process for investors – companies with high F-Score values appear attractive in terms of investments, which can bring potential profits exceeding the benchmark.


Keywords


F-Score indicator; scoring; rates of return; video game industry; IT industry

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References


Agrawal, K. (2015). Default prediction using Piotroski’s F-Score. Global Business Review, 16(5). doi:10.1177/0972150915601261

Bülow, S. (2017). The Effectiveness of Fundamental Analysis on Value Stocks – an Analysis of Piotroski’s F-score. Lund: University Sweden (Bachelor thesis in Financial Economics Department of Economics).

Gimeno, R., Lobán, L., & Vicente, L. (2020). A neural approach to the value investing tool F-Score. Finance Research Letters, 37. doi:10.1016/j.frl.2019.101367

Gray, W.R. (2015). Simple Methods to Improve the Piotroski F-Score. American Association of Individual Investors Journal, (May).

Hyde, Ch. (2013). An Emerging Markets Analysis of the Piotroski F-Score. SSRN Electronic Journal. doi:10.2139/ssrn.2274516

Korir, Ch.J. (2019). Applicability of Piotroski F-Score model in predicting financial distress of listed companies at the Nairobi Securities Exchange 20 Share Index, Kenya. A Research Project Presented to the Institute of Postgraduate Studies of Kabarak University in Partial Fulfillment of the Requirements for the Award of the Master of Business Administration (Finance Option).

Mehta, N., Pothula, V.K., & Bhattacharyya, R. (2019). A Value Investment Strategy that Combines Security Selection and Market Timing Signals. WorldQuant University MScFE Working Paper. doi:10.2139/ssrn.3451859

Mohanram, P.S. (2005). Separating Winners from Losers among LowBook-to-Market Stocks using Financial Statement Analysis. Review of Accounting Studies, 10, 133–170. doi:10.1007/s11142-005-1526-4

Mohr, J.-H.M. (2012). Utility of Piotroski F-Score for predicting Growth-Stock Returns. Working Paper, MFIE Capital.

Nast, T.K. (2017). Transforming Piotroski’s (binary) F-score into a real one. A research project submitted to the Gordon Institute of Business Science, University of Pretoria, in partial fulfilment of the requirements for the degree of Master of Business Administration.

Piotroski, J.D. (2000). Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Journal of Accounting Research, 38, 1–41. doi:10.2307/2672906

Rathjens, H., & Schellhove, H. (2011). Simple Financial Analysis and Abnormal Stock Returns – Analysis of Piotroski’s Investment Strategy. Stockholm: Stockholm School of Economics (Master Thesis in Accounting and Financial Management).

Tikkanen, J., & Äijö, J. (2018). Does the F-score improve the performance of different value investment strategies in Europe? Journal of Asset Management, 19(3), 495–506. doi:10.1057/s41260-018-0098-3

Tripathy, T., & Pani, B. (2017). Effect of F Score on Stock Performance: Evidence from Indian Equity Market. International Journal of Economics and Finance, 9(2), 89–99. doi:10.5539/ijef.v9n2p89

Walkshäus, Ch. (2020). Piotroski’s F-Score: International Evidence. Journal of Asset Management, 21, 106–118. doi:10.1057/s41260-020-00157-2

Wasyłkowska, M. (2013). Ocena sytuacji finansowej przedsiębiorstwa przy zastosowaniu metod analizy fundamentalnej. Zeszyty Naukowe Uniwersytetu Szczecińskiego. Finanse, Rynki Finansowe, Ubezpieczenia, 59, 363–372.

Wycinka, E. (2013). Uniwersalność zastosowań modeli skoringowych. Warszawa: StatSoft Polska.




DOI: http://dx.doi.org/10.17951/h.2021.55.1.41-50
Date of publication: 2021-05-11 08:57:00
Date of submission: 2021-01-01 10:59:35


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