Effects and Risks of Mergers and Acquisitions on Entrepreneurship in Banking and Finance: Empirical Study from Slovakia
Bibliographic record
Abstract
This study examines effects of mergers and acquisitions on entrepreneurship in the banking industry and identifies substantial factors of changing in its financial performance and risks from aspect of bank profitability in the economy of Slovakia, using regression modelling. The relationships between the dependence of the profitability of banking sector and selected financial indicators from aspect of its performance have been surveyed spanning a period of nine years (2004-2012). The research problem is as following: Do mergers and acquisitions create a value added and are desirable or more risky from financial aspect in the market economy. The task of this study is to use the financial analysis and project a multiple regression model (using data 1997-2011) to determine the success level of bank merger/acquisition between CSOB Bank and ISTROBANK in 2009, operating on the Slovak banking market. In the research hypotheses we investigate if the real profit development strengthened due to the impact of the bank merger/acquisition and impact of risks due to the global crisis on the financial performance. The novel designed linear regression model with seven independent variables, based on the methodology of empirical studies, compares the estimated and real profit development before and after bank merger/acquisition (2009-2011) as well. Our findings indicate that comparable models based on the existence of common relationships and dependences can be applied in other countries of the EU and present implications for decisions-making in the field of the increase global financial performance, trends and growth strategies of commercial banks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".