In this webinar, you will learn how MATLAB can be used to streamline the development of energy trading and risk management applications from inception to deployment. This webinar presents an example of computing cash-flow-at-risk and expected profit from operating a portfolio of gas-fired plants.
Highlights include:
- Modeling and simulating natural gas prices, temperature and electricity prices
- Calculating optimal dispatch
- Computing cash-flow-at-risk for a portfolio of gas-fired power plants
- Deploying an energy trading application as an Excel add-in
This webinar is for practitioners or academics in energy trading whose focus is quantitative analysis, modeling, risk management, or deal valuation. Familiarity with MATLAB is not required.
NOTE: As of R2015a, the Application Deployment products referenced in this video have changed. For the details of this transition, please watch a short video on the Application Deployment R2015a Transition.
About the Presenter:
Ameya Deoras is an application engineer at the bat365 with a focus on the Finance industry. Prior to joining the bat365 in 2008, Ameya undertook graduate research in computational gene prediction as well as robust speech recognition, both involving building statistical models for pattern recognition on large datasets using MATLAB. Ameya holds a B.S. in Electrical Engineering from the University of Illinois and an M.S. in Electrical Engineering from the Massachusetts Institute of Technology.
