Asset managers meet the investment needs of individuals, institutions, and governments by delivering a wide range of investment opportunities that achieve risk-adjusted performance with consistent returns over time. Investment management and research teams use MATLAB® to develop custom mathematical models for analyzing and optimizing large or complex portfolios, quantifying and controlling risk, and developing and implementing effective investment management strategies.
Using MATLAB, researchers and portfolio managers develop algorithms to optimize performance, minimize risk, and analyze results, including the application of mean-variance and Black-Litterman methods. They access securities data from databases or data providers such as Thomson Reuters and Bloomberg, manipulate time-series data, perform statistical analyses to understand risk, undertake portfolio attribution, determine pricing, conduct sensitivity analyses, develop valuation methods, and implement buy-and-sell criteria.
When portfolio researchers want to communicate MATLAB model results to portfolio managers, company executives, or clients, they export results into Excel®, a database, or a PDF or HTML report. With MathWorks deployment tools, development teams integrate investment analytics functions and routines into their preferred front-office software environment. Researchers and developers deploy standalone applications or software components that integrate with C and C++, Visual Basic®, Excel, .NET, and Java™ based applications.