Детальная информация

В этой диссертации изучаются факторы, влияющие на эффективность листинговых коммерческих банков в Китае, и в качестве индекса оценки используется экономическая добавленная стоимость (EVA). Предметом исследования являются восемь листинговых коммерческих банков в период с 2008 по 2022 год. Тема этого исследования — анализ EVA этих банков и влияющих на них факторов с целью выявления ключевых факторов, влияющих на экономическую добавленную стоимость (EVA) листинговых коммерческих банков Китая с помощью эмпирического анализа, чтобы помочь этим банкам улучшить свои операционные показатели и возможности создания стоимости. Методология исследования приняла сочетание качественного и количественного анализа, а анализ множественной линейной регрессии проводился с помощью программного обеспечения Eviews. Результаты исследования показывают, что логарифм вознаграждения руководителей, коэффициент достаточности капитала, логарифм размера активов, коэффициент покрытия неработающих кредитов и коэффициент расходов к доходу существенно связаны с EVA, в то время как факторы коэффициента кредита к депозиту и структуры капитала не проходят тест на значимость. Статья разделена на четыре части: в первой части представлены предыстория, цель, значение и методология исследования; во второй части устанавливается система оценки эффективности банков на основе EVA, а также рассчитываются и анализируются значения EVA восьми банков; в третьей части изучаются факторы, влияющие на EVA, посредством эмпирического анализа; а в четвертой части обобщаются выводы и выдвигаются предложения по улучшению, что направлено на предоставление теоретических Четвертая часть исследования обобщает выводы и выдвигает предложения по улучшению. Объем исследования ограничен восемью перечисленными коммерческими банками, которые могут не быть полностью репрезентативными для всей отрасли. В разделе заключения говорится, что путем укрепления связи между вознаграждением руководителей и эффективностью, оптимизации распределения активов и управления капиталом, а также улучшения управления кредитными рисками коммерческие банки могут увеличить свою экономическую добавленную стоимость, тем самым повышая свой потенциал создания стоимости.

This thesis investigates the factors influencing the performance of listed commercial banks in China and uses economic value added (EVA) as an evaluation index. The subjects of the study are eight listed commercial banks between 2008 and 2022. The theme of this study is to analyse the EVA of these banks and their influencing factors, with the aim is to identify the key factors affecting the economic value added (EVA) of Chinas listed commercial banks through empirical analysis to help these banks improve their operational performance and value creation capabilities. The research methodology adopted a combination of qualitative and quantitative analysis, and multiple linear regression analysis was conducted through Eviews software. The results of the study show that the logarithm of executive compensation, capital adequacy ratio, logarithm of asset size, non-performing loan coverage ratio and cost-to-income ratio are significantly related to EVA, while the factors of loan-to-deposit ratio and equity structure fail the significance test. The paper is divided into four parts, the first part introduces the background, purpose, significance and methodology of the study; the second part establishes the bank performance evaluation system based on EVA, and calculates and analyses the EVA values of eight banks; the third part explores the factors affecting EVA through empirical analysis; and the fourth part summarizes the findings and puts forward suggestions for improvement, which is aimed at providing theoretical The fourth part of the study summarises the findings and puts forward suggestions for improvement. The scope of the study is limited to eight listed commercial banks, which may not be fully representative of the whole industry. The conclusion section states that by strengthening the link between executive compensation and performance, optimising asset allocation and capital management, and enhancing loan risk management, commercial banks can increase their economic value added, thereby enhancing their value creation capacity.

• TASK
• ABSTRACT
• INTRODUCTION
• 1. CONCEPTS AND THEORIES RELATED TO BANK PERFORMANCE
  • 1.1. Literature review
    • 1.1.1. Literature review on the theoretical basis of performance evaluation
    • 1.1.2. Literature review on the application of performance evaluation in commercial banks
    • 1.1.3. Literature review of EVA normative studies
    • 1.1.4. Literature review of the study on the effectiveness of EVA evaluation index
    • 1.1.5. Literature review of empirical studies on EVA evaluation indicators
    • 1.1.6. Literature review on the application study of EVA evaluation indicators of commercial banks
    • 1.1.7. Summary of the literature review
  • 1.2. Theoretical basis of economic value added
    • 1.2.1. Theoretical foundation
      • 1. Financial Innovation Theory.
      • 2. The theory of the long tail.
    • 1.2.2. Business Performance Evaluation Methodology
      • 1. Financial indicator method.
      • 2. Economic Value Added.
      • 3. Efficiency evaluation method.
      • 4. BSC Assessment Method.
      • 5. DEA evaluation method.
  • 1.3 Summary
• 2. ASSESSMENT OF COMMERCIAL BANKS PERFORMANCE
  • 2.1. Analysis of the development of the commercial banking industry
  • 2.2. Factors affecting the activities of Chinese commercial banks
    • 1. The macroeconomic environment's impact.
    • The basis for the operations of commercial banks is the macroeconomic environment. The loan demand, asset quality, and profitability model of banks are directly impacted by China's economic growth rate, inflation rate, monetary policy, and other macro...
    • 2. The function of financial regulations.
    • 3. Shifts in the market's competitive environment.
    • 4. Variations in the global economic landscape.
    • 5. Streamlining internal bank management.
    • 6. Motivated by advancements in technology and the shift towards digitalization.
    • 7. Diversification of Client Requirements.
    • 8. A Focus on Ecological Finance and Social Responsibility.
  • 2.3. Construction of commercial bank performance system based on EVA
    • 2.3.1. The necessity of introducing EVA in commercial banks
    • 1. Accurate depiction of company performance.
    • 2. Encouraging operations that prioritize efficiency.
    • 3. Improving capital cost control.
    • 4. Encouraging the development of sustainable.
    • 2.3.2. Calculation of EVA related indicators and corresponding accounting account adjustments
      • 1. Net operating profit after tax (NOPAT) and its adjustments.
      • 1. Total capitalization (TC) and its adjustments.
      • 2. Weighted average cost of capital ratio (WACC).
    • 3. Risk-free rate of return (Rf).
    • 4. Market risk premium (Rm-Rf).
    • 5. Listed commercial banks β coefficient.
    • 2.3.3 Measurement of commercial bank operating performance based on EVA
    • 1. Sample and data.
    • 2. Measurement and Results.
    • 3. Analysis of results.
  • 2.4. Summary
• 3. EMPIRICAL ANALYSIS OF FACTORS INFLUENCING EVA OF COMMERCIAL BANKS
  • 3.1. Selection of influencing factors
    • 3.1.1. Asset quality
      • 1. Loan-deposit Ratio.
      • 2. Non-performing loan provision coverage ratio.
      • 3. Non-Performing Loan Ratio.
      • 4. Fixed Assets Investment Ratio.
    • 3.1.2. Asset Management
      • 1. Capital Adequacy Ratio.
      • 2. Income Cost Ratio.
      • 3. Net Non-Interest Margin.
    • 3.1.3. Other influencing factors
      • 1. Consumer Price Index (CPI).
      • 2. Executive Compensation.
      • 3. Equity Structure.
      • 4. Total Asset.
  • 3.2. Variable descriptive statistics and analytical testing
    • 3.2.1. Descriptive statistics and correlation coefficient analysis
      • 1. Descriptive statistical analysis.
      • 2. Stability test.
      • 3. Correlation coefficient analysis.
      • 4. Variance inflation factor.
    • 3.2.2. Model selection and modification
  • 3.3. Empirical regression test and result analysis of panel data model
    • 3.3.1. Empirical test of model regression
    • 3.3.2. Analysis of empirical regression results
      • 1. Analysis of the impact of the logarithm of executive compensation LNINXC on the EVA of commercial banks.
      • 2. Analysis of the impact of capital adequacy ratio CAR on commercial banks’ EVA.
      • 3. Analysis of the impact of logarithm of asset scale LNINTA on commercial banks’ EVA.
      • 4. Analysis of the impact of non-performing loan provision coverage ratio PCR on commercial banks’ EVA.
      • 5. Analysis of the impact of cost-to-income ratio ICR on commercial banks’ EVA
      • 6. Analysis of the impact of factors that fail the significance test on the EVA of commercial banks.
  • 3.4. Summary
• 4. CONCLUSION AND RECOMMENDATIONS
  • 4.1. Improve the link between executive compensation levels and performance
  • 4.2. Optimize asset allocation and capital management
  • 4.3. Strengthen loan risk management
  • 4.4. Optimize operating efficiency and resource allocation
  • 4.5. Summary
• CONCLUSION
• LIST OF REFERENCES
• APPENDIX A
• Table A.1. - Listed Commercial Banks 2008-2022 WACC Calculations (completed by the author)
• Continued Table A.1.
• Continued Table A.1. (1)
• Ending of Table A.1