Spot Volatility Estimation for High-Frequency Data: Adaptive Estimation in Practice
2015 | book part
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Spot Volatility Estimation for High-Frequency Data: Adaptive Estimation in Practice
Sabel, T.; Schmidt-Hieber, J.& Munk, A. (2015)
In:Antoniadis, Anestis; Poggi, Jean-Michel; Brossat, Xavier (Eds.), Modeling and Stochastic Learning for Forecasting in High Dimensions pp. 213-241. Springer Nature. DOI: https://doi.org/10.1007/978-3-319-18732-7_12
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Details
- Authors
- Sabel, Till; Schmidt-Hieber, Johannes; Munk, Axel
- Editors
- Antoniadis, Anestis; Poggi, Jean-Michel; Brossat, Xavier
- Abstract
- We develop further the spot volatility estimator introduced in Hoffmann et al. (Ann Inst H Poincaré (B) Probab Stat 48(4):1186–1216, 2012) from a practical point of view and make it applicable to the analysis of high-frequency financial data. In a first part, we adjust the estimator substantially in order to achieve good finite sample performance and to overcome difficulties arising from violations of the additive microstructure noise model (e.g. jumps, rounding errors). These modifications are justified by simulations. The second part is devoted to investigate the behavior of volatility in response to macroeconomic events. We give evidence that the spot volatility of Euro-BUND futures is considerably higher during press conferences of the European Central Bank. As an outlook, we present an estimator for the spot covolatility of two different prices.
- Issue Date
- 2015
- Publisher
- Springer Nature
- Series
- Lecture Notes in Statistics
- ISBN
- 978-3-319-18731-0
- ISSN
- 0930-0325
- Language
- English