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Erschienen in:
Short Term Load Forecasting in the Industry for Establishing Consumption Baselines: A French Case Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Spot Volatility Estimation for High-Frequency Data: Adaptive Estimation in Practice

verfasst von : Till Sabel, Johannes Schmidt-Hieber, Axel Munk

Erschienen in: Modeling and Stochastic Learning for Forecasting in High Dimensions

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel Massive-Scale Simulation of Electrical Load in Smart Grids Using Generalized Additive Models
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Metadaten
Titel
Spot Volatility Estimation for High-Frequency Data: Adaptive Estimation in Practice
verfasst von
Till Sabel
Johannes Schmidt-Hieber
Axel Munk
Copyright-Jahr
2015
Buch
Modeling and Stochastic Learning for Forecasting in High Dimensions

Print ISBN: 978-3-319-18731-0

Electronic ISBN: 978-3-319-18732-7

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-18732-7_12

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