The Relationship between the Volatility of Returns and the Number of Jumps in Financial Markets |
| |
Authors: | Álvaro Cartea Dimitrios Karyampas |
| |
Institution: | 1. University College London, London, UK;2. ICMA, University of Reading |
| |
Abstract: | 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, the number of jumps is very useful to forecast volatility and contains information that is not impounded in the VIX. |
| |
Keywords: | High-frequency data Implied volatility Jumps Microstructure noise VIX Volatility forecasts |
|
|