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Czasopismo
2022 | 18 | nr 1 | 66--73
Tytuł artykułu

Can we Predict High Growth Firms with Financial Ratios?

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study attempts to predict high growth firm (HGF) status with financial ratios. Measures related to the firm's effectiveness in using assets to generate profits, EBITDA margin, debt ratio, equity-to-debt ratio and return on assets are associated with HGF status. While the financial ratios improve HGF prediction, prediction remains modest (AUC = 0.627). This study suggests it is difficult to assume a very good HGF forecast from only financial ratios; therefore, the recommendation for researchers and policymakers building models for predicting HGFs is to incorporate non-financial ratio variables, like the intangible innovation and team-related variables. Finally, study suggests a standardized reporting of prediction performance metrics in the out-of-sample and out-of-time simulation for HGF prediction studies. (original abstract)
Czasopismo
Rocznik
Tom
18
Numer
Strony
66--73
Opis fizyczny
Twórcy
  • University of SplitSplit, Croatia
Bibliografia
  • Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, XXIII(4), 589-609.
  • Altman, et al. (2017). Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z-Score Model. Journal of International Financial Management and Accounting.
  • Belloni, A., Chernozhukov, V., & Wei, Y. (2016). Post-Selection Inference for Generalized Linear Models With Many Controls. Journal of Business and Economic Statistics, 34(4), 606-619.
  • Coad, et al. (2014). High-growth Firms: Introduction to the Special Section. Industrial and Corporate Change, 23(1), 91-112.
  • Coad, A., Frankish, J., Roberts, R.G., & Storey, D.J. (2013). Growth Paths and Survival Chances: An Application of Gambler's Ruin Theory. Journal of Business Venturing, 28(5), 615-632.
  • Coad, A., & Karlsson, J. (2022). A Field Guide For Gazelle Hunters: Small, Old Firms are Unlikely to Become High -growth Firms. Journal of Business Venturing Insights, 17, e00286.
  • Coad, A., & Scott, G. (2018). High-growth Firms in Peru. Cuadernos de Economia, 37(SPE75), 674-696.
  • Coad, A., & Srhoj, S. (2020). Catching Gazelles with a Lasso: Big Data Techniques for High Growth Firm Prediction. Small Business Economics, 55, 541-565.
  • Crosato, L., Domenech, J., & Liberati, C. (2021). Predicting SME 's Default: Are Their Websites Informative? Economics Letters, 204.
  • Daunfeldt, S.O., & Halvarsson, D. (2014). Are High -growth Firms One-hit Wonders? Evidence from Sweden. Small Business Economics, 44, 361-383.
  • Du, J., & Temouri, Y. (2015). High-growth Firms and Productivity: Evidence from the United Kingdom. Small Business Economics, 44(1), 123-143.
  • Dvoulety, O., Srhoj, S., & Pantea, S. (2021). Public SME Grants and Firm Performance in European Union: A Systematic Review of Empirical Evidence. Small Business Economics, 57(1), 243-263.
  • Eurostat-OECD (2007). Eurostat-OECD Manual on Business Demography Statistics. Luxembourg.
  • Flachenecker, et al., (2020). High Growth Enterprises: Demographics, Finance & Policy Measures. Joint Research Center European Commission.
  • Goswami, A.G., Medvedev, D., & Olafsen, E. (2019). High -growth Firms: Facts, Fiction, and Policy Options for Emerging Economies. World Bank Publications.
  • Megaravalli, A.V., & Sampagnaro, G. (2019). Predicting the Growth of High -growth SMEs: Evidence from Family Business Firms. Journal of Family Business Management, 9(1), 98-109.
  • Srhoj, S., Vitezic, V., & Wagner, J. (2020). Export Boosting Policies and Firm Behaviour: Review of Empirical Evidence around the World. Working Paper Series in Economics No. 395. Leuphana Universität Lüneburg, Institut für Volkswirtschaftslehre, Lüneburg.
  • Srhoj, S., Zupic, I., & Jaklic, M. (2018). Stylised Facts about Slovenian High -growth Firms. Economic Research -Ekonomska Istrazivanja, 31(1), 1851-1879.
  • Tibshirani, R. (2011). Regression Shrinkage and Selection via the Lasso: A Retrospective. Journal of the Royal Statistical Society: Series B, 73(2), 273-282.
  • Weinblat, J. (2018). Forecasting European High-growth Firms - A Random Forest Approach. Journal of Industry, Competition and Trade, 18(3).
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171659380

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