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On meeting capital requirements with a chance-constrained optimization model
Ebenezer Fiifi Emire Atta Mills1, Bo Yu1, Lanlan Gu1
1School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024 China.
Springerplus
|May 18, 2016
Summary
This study presents a capital to risk asset ratio optimization model that ensures banks meet Basel III capital requirements with 95% certainty, even during loan defaults and market volatility.
Area of Science:
- Financial Mathematics
- Risk Management
- Banking Regulation
Background:
- Banks face challenges in meeting capital requirements due to asset volatility and loan defaults.
- Basel III regulations impose strict capital adequacy standards on financial institutions.
- Existing models may not adequately capture the complexities of asset dynamics and risk.
Purpose of the Study:
- To develop a chance-constrained optimization model for the capital to risk asset ratio.
- To incorporate realistic asset dynamics, including loans and treasury bills.
- To analyze the model's performance under worst-case scenarios like loan default.
Main Methods:
- Introduction of a modified CreditMetrics approach to model loan dynamics.
- Development of a deterministic convex counterpart for the capital to risk asset ratio chance constraint.
- Application of numerical procedures for theoretical model analysis.
Main Results:
- The proposed model guarantees banks meet Basel III capital requirements with 95% likelihood.
- The model remains effective despite fluctuations in the future market value of assets.
- Analysis under worst-case scenarios provides valuable financial insights.
Conclusions:
- The capital to risk asset ratio chance-constrained optimization model offers a robust solution for banks.
- The model enhances banks' ability to comply with regulatory capital requirements.
- This approach provides a reliable framework for managing financial risk and ensuring stability.
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