Risk managers and analysts rely on MATLAB to:
The resulting parameters from these activities are used to rebalance portfolios, allocate economic capital, enable valuations (for example, credit valuation adjustment), model derivatives instruments (such as credit derivatives) and facilitate hedging and trading.
Using MATLAB, organizations build an integrated workflow from research to testing and deployment that helps protect balance sheets, scrutinize financial engineering methodologies, and satisfy the diverse requirements of regulators, governments, customers, and shareholders.
Teams develop and test applications in MATLAB that meet new requirements for base-case conditions and extensive what-if scenarios. MATLAB provides a flexible environment that combines numerical accuracy and algorithm traceability with extensive reference documentation.
Credit Risk Modeling in MATLAB (Webinar)
Using MATLAB visualization capabilities and interactive plots, risk-management departments communicate a quantitative and intuitive description of risk model behavior that is accessible to mathematicians and nonmathematicians alike.
Using MATLAB and related toolboxes, developers deploy standalone applications or software components that integrate with C and C++, .NET, Excel, and Java based applications. Deploying standalone executables and Web components helps reduce the risk of user error and tampering, common in spreadsheet applications. By leveraging multicore computers and grids developers can further accelerate application performance.
"MATLAB allows us to manage a huge amount of data and to generate an impressive number of scenarios very quickly. This has enabled us to monitor credit risk as a result of the estimated degree of portfolio diversification and concentration."Read the story