The drivers of volume volatility: A big data analysis based on economic uncertainty measures for the Greek banking system
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Author(s)Leonidas TheodorakopoulosLink to ORCID Index: https://orcid.org/0000-0002-0891-6780
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Hera AntonopoulouLink to ORCID Index: https://orcid.org/0000-0002-3936-435X
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Vicky MamalougouLink to ORCID Index: https://orcid.org/0000-0002-7731-8207
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Konstantinos C. GiotopoulosLink to ORCID Index: https://orcid.org/0000-0001-5989-6313
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DOIhttp://dx.doi.org/10.21511/bbs.17(3).2022.05
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Article InfoVolume 17 2022, Issue #3, pp. 49-57
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158 Downloads
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Creative Commons Attribution 4.0 International License
In this paper, an investigation is conducted to estimate the effect of economic uncertainty on volume volatility, focusing on four systemic Greek banking institutions, including (i) Alpha Bank, (ii) Eurobank, (iii) National Bank of Greece, and (iv) Piraeus Bank. The purpose of this study is to explain in detail if the EPU is linked with volume volatility in the largest banking institutions in Greece. For the analysis of this paper, data used are monthly data of volume to explain the economic uncertainty on volume volatility. The analysis period covers the period from January 2001 to August 2018, incorporating various market phases, such as the global financial crisis of 2008, the European debt crisis, and capital controls in the Greek economy. The methodology used for the research is the well-known GARCH model. Based on the estimated regressions, the present research findings showed that economic uncertainty has various effects on the volume volatility of the four systemic Greek banking institutions. More specifically, when economic uncertainty receives a high value, then the volatility of the volume in Greek banking institutions increases, receiving a higher value. In conclusion, it is observed that economic uncertainty positively affects the volume volatility of the Greek banking system.
- Keywords
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JEL Classification (Paper profile tab)F65, G11, G12, G24
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References42
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Tables2
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Figures1
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- Figure 1. Greek banks’ volume (in y axes) evolution from 2001 to 2018
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- Table 1. Descriptive statistics
- Table 2. Parameter estimates for the marginal distribution of returns
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doi: http://dx.doi.org/10.21511/imfi.18(3).2021.02
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Hemendra Gupta
doi: http://dx.doi.org/10.21511/imfi.17(3).2020.11
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Manju Rajan Babu ,
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