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Sorting out the financials: Making economic sense out of statistical factors

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  • Lončarski, Igor
  • Vidovič, Luka

Abstract

In this paper we explore systematic and efficient use of a large amount of financial statement data most often used by financial analysts for the valuation purposes in terms of relative valuation (multiples). We use principal component analysis to analyze financial statement data and/or ratios at a company level. We transform financial statement data into new variables that exhibit distinct economic interpretations and can be considered as value drivers reflecting profitability, growth prospects, and risk.

Suggested Citation

  • Lončarski, Igor & Vidovič, Luka, 2019. "Sorting out the financials: Making economic sense out of statistical factors," Finance Research Letters, Elsevier, vol. 31(C), pages 110-118.
    • Handle: RePEc:eee:finlet:v:31:y:2019:i:c:p:110-118
    DOI: 10.1016/j.frl.2019.04.009
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    References listed on IDEAS

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    2. Lan, Hai & Zheng, Puyang & Li, Zheng, 2021. "Constructing urban sprawl measurement system of the Yangtze River economic belt zone for healthier lives and social changes in sustainable cities," Technological Forecasting and Social Change, Elsevier, vol. 165(C).

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