Econometrics with MATLAB
How do you prepare time series data and quickly test different models of fits? Ensuring data is reliable and clean, converting the non-stationary data to proper stationary data, testing different models of fits --- these are all critical steps in econometrics analysis and can take a significant amount of time to accomplish.
MATLAB provides creative and interactive tools for easy evaluation and analysis each step of the way. Using point and click techniques, you can transform your data, perform statistical tests, choose models based on residual diagnostics, generate functions and create reports at the end of the process
In this session, we will demonstrate MATLAB’s econometrics modeler app that lets you explore data, apply data transformation, and fit econometric using models such as ARIMA, EGARCH, GJR, and VEC. After completing your model, we’ll show you how to export the model to the MATLAB workspace or generate a summary report.
Moreover, we will showcase how you can share you results using the web app, a powerful tool that takes minimum time to build in MATLAB but can make your research available to a broad audience.
- Interactive time series Modeling
- Vector Autoregression Modeling
- Conditional Mean and Regression Modeling
- Volatility Modeling
- Regime-Switching Modeling
- State-Space Modeling
- Hypothesis Testing
Who Should Attend
People with an interest in:
- Econometrics Modeling
- Time Series Analysis
- Automatic Report Generation
- Web Application
About the Presenter
Xuyang Ma is a senior application engineer at MathWorks based in the company's Natick, MA office. She supports customer applications related to the computational finance area, including pricing and valuation, econometrics data science, risk management, portfolio management, and execution strategy (AI). Before joining MathWorks, she worked at a Boston-based quantitative investment management firm for six years as a quantitative researcher on Macro and Equity strategies. Prior, she graduated from the University of Washington with a Ph.D. degree in Economics and Computational Finance and is familiar with MATLAB, SAS, R, and Python.