✦ LIBER ✦
Forecasting volatility with noisy jumps: an application to the Dow Jones Industrial Average stocks
✍ Scribed by Basel M. A. Awartani
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 149 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0277-6693
- DOI
- 10.1002/for.1057
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✦ Synopsis
Abstract
Empirical high‐frequency data can be used to separate the continuous and the jump components of realized volatility. This may improve on the accuracy of out‐of‐sample realized volatility forecasts. A further improvement may be realized by disentangling the two components using a sampling frequency at which the market microstructure effect is negligible, and this is the objective of the paper. In particular, a significant improvement in the accuracy of volatility forecasts is obtained by deriving the jump information from time intervals at which the noise effect is weak. Copyright © 2008 John Wiley & Sons, Ltd.