Taking Quantitative Analytics Beyond the Spreadsheet
Learn how capital markets players are leveraging the combined power of MATLAB and Numerix CrossAsset to create rich quantitative modeling sandboxes with the robust controls and structure of enterprise level analytics.
For capital markets firms, spreadsheets can deliver flexibility for quants and a way to innovate and deliver new products or models that existing systems can’t support. But when it comes time to expose those efforts to the rigors of regulators or deliver business at scale, an enterprise grade solution is in order.
MathWorks, the world leading developer of mathematical computing software, and Numerix, the leader in risk management and quantitative analytics for the capital markets, have teamed up to provide an integrated approach to delivering innovative analytics at enterprise level.
The Numerix Interface in MATLAB’s Financial Instruments Toolbox integrates the best-in-class MATLAB development environment with Numerix’s award-winning quantitative modelling library. This interface empowers our joint customers with a flexible accelerated development environment for creating a broad variety of risk management and valuation analytics for OTC derivatives and securities.
This webinar provides case studies illustrating how capital market leaders are leveraging the Numerix Interface in MATLAB. And whether you’re familiar with Numerix and MATLAB or new to them, we also provide a demonstration of how these power-house solutions can be utilized together for rapid financial modeling.
JOIN OUR PRESENTERS AS THEY DISCUSS:
- Introduction to Numerix and MATLAB
- Client Case Studies
- Intraday Pricing and Risk for Commodity Trading Desk
- Model Validation Environment for Derivatives Trading
- Launching a New Insurance Line of Business
- Scenario Generation and Hedging Processes
- Demonstration of Numerix capabilities in MATLAB
- Using the Live Editor in MATLAB for modeling and reporting
- Importing Data into MATLAB using the Datafeed Toolbox
- Estimating the Diebold-Li model using a Kalman filter
- Calibrating a real-world 2 factor Hull-White model using Numerix
- Computing counterparty risk exposures for a capped, amortizing swap in Numerix using Las Vegas Monte Carlo and Resampling Technique
- Visualization of Counterparty Credit Risk measures in MATLAB
- Conclusion
Featured Speakers
Kevin Shea
Kevin Shea joined MathWorks in 2000 and is a principal software engineer and manager for the Computational Finance Development team. He is responsible for the development of financial instruments and risk modeling and analysis functionality in MATLAB. He was previously a consultant at MathWorks where he worked primarily with customers in the financial services industry. He is a CFA® charter holder.
Bill Dwyer
Bill has over 20 years of experience in the financial services technology sector. During his career he’s had the privilege of working with some of the world’s leading financial institutions on both the buy- and sell-side, including BNP Paribas, Fidelity, Socgen, ABN-Amro, RBC, Jefferies, TD, Clearstream, Credit Agricole, Unicredit, and State Street.
Bill joined Numerix in early 2016, he is currently in charge of the Numerix partner business development function in the Americas, as well as Numerix corporate development activities. Bill started his career in capital markets technology with Teknekron Software Systems (now Tibco) in 1994. Prior to Numerix, he also served in senior sales leadership related roles in S&P, Murex, SunGard, and Reuters.
Greg Murray
Greg Murray is responsible for increasing awareness of the Numerix brand in financial markets around the globe, as well as conducting strategic industry research for different departments within Numerix. Previously, he oversaw product and field marketing initiatives at the company, and he started his tenure in a sales role. Prior to Numerix, Mr. Murray worked in derivative analytics sales roles at other software firms, and he held derivative trading positions for seven years as an option market-maker and proprietary trader across a variety of asset classes.
