A model proposal for estimating banks’ future value: Evidence from Turkey
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DOIhttp://dx.doi.org/10.21511/bbs.16(4).2021.14
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Article InfoVolume 16 2021 , Issue #4, pp. 169-178
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Investors make solid decisions when evaluating their investments based on positive indicators the firm may show in the future, rather than based on its past performance. Accordingly, this study aims to investigate the relationship between performance criteria and the most significant value-based criterion; Economic Value Added (EVA). Further, it evaluates the impact of future EVA values on the bank value. Panel Data Analysis and the OLS Regression model are used to estimate the regression equation. The analysis is performed using data of 10 banks on the BIST Banks Index over the period 2011 to 2020. Furthermore, the EVA criterion was converted into standardized EVA(SEVA) by dividing EVA by total assets. The OLS regression analysis results revealed that the model’s explanatory power for the SEVA variable is 71.92%. The three variables that have positive correlation with SEVA are earnings per share (EPS) and TOBINQ rates at the 1% significance level and the price to sales growth rate with a degree of significance at 10%. Regarding the Panel Data Analysis results, while the explanatory power of the SEVA variable is 72.14%, its association with the EPS and TOBINQ criteria was found to be significant at the 1% significance level. The empirical investigations reveal that the model developed using the future SEVA as a proxy for bank value is found to be promising, and it is accepted that the SEVA variable can be used instead of the bank value.
- Keywords
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JEL Classification (Paper profile tab)C23, G19, G21
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References26
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Tables7
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Figures0
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- Table 1. The Information of banks used in the analysis
- Table 2. The definition of variables
- Table 3. Descriptive statistics
- Table 4. Correlation coefficients
- Table 5. Diagnostic tests results
- Table 6. OLS regression results
- Table 7. Panel regression results
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