By Zoraver Lamba
This paper examines the contemporaneous and dynamic relationships between the volatilities of the technology stocks in the S&P 100 index. Factor analysis and heterogeneous autoregressive regressions are used to examine contemporaneous and dynamic, inter-temporal relationships, respectively. Both techniques utilize high frequency data by measuring stock prices every 5 minutes from 1997-2008. We find that a strong industry effect explains the bulk of the volatility of the technology stocks and that the market’s volatility has very low correlation with the stocks’ volatility. Further, we find the market’s volatility has insignificant predictive content for the stocks’ volatility. The stocks themselves contain large quantities of unique predictive content for each other’s volatilities.
Advisor: George Tauchen