You can download the necessary data for this assignment from WRDS (Wharton Research Data Services). You can sign up for a WRDS account at https://wrds- web.wharton.upenn.edu/wrds/?register=1. On WRDS, go to CBOE Indexes and download the CBOE S&P 500 Volatility Index Closing daily values from January 2nd 2000 to December 29, 2017. Then go to CRSP, Stock/Security Files, Stock Market Indexes, and download the daily “Level on S&P Composite Index” from January 1st 2000 to December 29, 2017.
- Run the following linear regressions:
- &= + 1 ∗ +
- & = + 2 ∗ −1 +
Repeat these regressions for every full calendar year. Graph 1 and 2 separately on a chart,
with beta values on the Y axis and Year on the X axis. Scale the charts so that it is easy to
read. Also make a table of the respective t-statistics of each 1 and 2 value. Describe what
you see. What is the relationship between the S&P and the VIX? Why do you think this
relationship is this way?
- Now download the 10 Year Treasury VIX at http://www.cboe.com/products/vix-index- volatility/volatility-on-interest-rates/cboe-cbot-10-year-u-s-treasury-note-volatility-index- tyvix. Run the following multiple linear regression:
- & = + 1 ∗ −1 + 2 ∗ −1 +
Run this once for the entire 2003-2017 dataset. Is the lagged VIX or lagged TYVIX a better
predictor of the S&P? Why do you think this is?
Print out your SAS or R code and attach it to your assignment. This assignment is due March 8th. Good luck!
