The Relationship between the Transparency in Provision of Financial Data and the Change in Investors’ Expectations


  • Leonidas Sakalauskas Vilnius University Institute of Mathematics and Informatics
  • Zivile Kalsyte Kaunas University of Technology
  • Ingrida Vaiciulyte Vilnius University Institute of Mathematics and Informatics
  • Irmantas Kupciunas Kaunas University of Technology



Random Forests, stable distribution, skew t-distribution, prediction, AGR rating, data analysis, mathematical models.


The purpose of the work is to establish a relationship between the enterprise’s practice of providing financial data and the investors’ opinion about the enterprise as well as to predict whether the enterprise will be inclined to cheat while providing its financial data in the future. To reflect the investors’ opinion about an enterprise, the parameters of skew t-distribution and stable distribution calculated from stock data (close and volume) have been used. The obtained preference area, the parameters (calculated from close and volume stock price data) of the distributions and the indicators representing the present have been employed as Random Forest inputs in predicting the direction of the change in future Accounting & Governance Risk (AGR) rating, which defines the change in the risk of provision of financial data, i.e., whether the risk will increase or decrease. As it has been revealed by the selection of features, stable distribution parameters better reflect the amplitude of the change in stock prices, while the investors’ preference area, drawn on the basis of skew t-distribution parameters, has reflected the discrepancy between the investors’ expectations and the enterprise’s actual value. The same most important selected features have been found to be equally well applicable in describing enterprises characterised by the tendency for AGR rating to rise as well as those characterised by the tendency for AGR rating to drop, or describing both those groups of enterprises collectively.


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