The Relationship between the Volatility of Returns and the Number of Jumps in Financial Markets
Econometric Reviews, Vol. 35 , Iss. 6,2016
25 Pages Posted: 18 Nov 2009 Last revised: 30 Aug 2017
Date Written: May 7, 2014
We propose a methodology to employ high frequency financial data to obtain estimates of volatility of log-prices which are not affected by microstructure noise and Lévy jumps. We introduce the 'number of jumps' as a variable to explain and predict volatility and show that the number of jumps in SPY prices is an important variable to explain the daily volatility of the SPY log-returns, has more explanatory power than other variables (e.g. high and low, open and close), and has a similar explanatory power to that of the VIX. Finally, number of jumps is very useful to forecast volatility and contains information that is not impounded in the VIX.
Keywords: volatility forecasts, high-frequency data, implied volatility, VIX, jumps, microstructure noise
JEL Classification: C53, G12, G14, C22
Suggested Citation: Suggested Citation