The Volatility Laboratory (V-Lab) provides real time measurement, modeling and forecasting of financial volatility, correlations and risk for a wide spectrum of assets. V-Lab blends together both classic models as well as some of the latest advances proposed in the financial econometrics literature. The aim of the website is to provide real time evidence on market dynamics for researchers, regulators, and practitioners. V-Lab is currently running 83,950 analyses on 16,983 datasets producing a total of 140,849 series each day!
VINSIGHT is a gateway application supporting the V-lab. Behind the scenes, VINSIGHT crunches over 10 years of financial market data and combines it with volatility prediction models developed by most famous scholars such as Robert Engle to come up with a customized prediction of volatility.
The VINS Student Research Assistant Program is a highly competitive program geared toward students interested in Chinese financial markets, economics, business, and computer science. It is open to students from all disciplines. The first pool of applicants featured 30 outstanding students, all of whom went through an academic election process that included interviews. Below is a sample of the program's learning goals that VINS Student Researchers expect to achieve by the end of the program:
- An understanding of basic topics in Econometrics, including the basics of the GARCH model
- General product development and product development for financial market customer segments
- Public speaking and training presentation development
- Empirical research skills
- Data analysis and integrity
During the course of the Spring 2015 semester, VINS Student Research Assistants (RAs) will work on a variety of tasks directly related to the support and development of the VINS mission outlined above. Specific projects include:
- Apply Volatility Index of China Stock Markets to hedging
- Impact of Hong Kong-Shanghai link on China Stock Market
- Relationship between Volatility Index of China and option pricing
- Private equity targeting system under corporate governance index
RAs are divided into four groups, respectively focusing on the four projects above. After empirical research, programming, and data analysis, RAs attend weekly meetings with their supervisors to gain inspiration and suggestions from other groups. Self-motivation and self-teaching are both essential for RAs since softwares like Wind, SAS, Python, and MatLab are not completely covered in class. Each group is expected to produce a written document detailing their research-related contribution to VINS prior to the end of the Spring 2015 semester.