Abstract
This paper uses high frequency stock trading data from 2007 to 2014 to study patterns of stock returns in the very short run. The paper verifies stylized facts of stock prices at low frequency with the exploration of high-frequency data and uses the concept of relative realized volatility (RRV) to measure volatility to understand the market uncertainty intraday. By providing a large number of empirical data facts, this paper advocates the use of ultra-high frequency data to study instantaneous real volatility, and demonstrates that long-term market volatility and the relationship between short and long term volatility can be implied by a simple RRV mean regression model.
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