For financial institutions, risk modeling is common practice to identify, assess, control, and monitor risk. Mathematical risk models and statistical methods applied in MATLAB® (e.g., regression, Monte Carlo simulation, and copulas) are used by risk professionals to quantify the impact of risk, optimize capital allocation, accelerate regulatory submission, and enable more risk-based service offerings.
This ebook is a practical guide to modeling financial risk with MATLAB and provides access to applied examples, documentation, and user stories. Learn more about:
- Types of financial risk models in MATLAB, including credit risk, market risk, operational risk, systemic risk, liquidity risk, concentration risk, capital risk, and value at risk
- How to improve your product offerings through automated risk-integrated service improvements
- How you can adapt risk models in MATLAB to conform to new regulations and address new types of risk factors, reducing project time
- Real-world application of mathematical modeling and statistical methods with MATLAB