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@inproceedings{1312614,
author = {Hruška, Juraj and Deev, Oleg},
address = {Brno},
booktitle = {European Financial Systems 2015. Proceedings of the 12th International Scientific Conference},
keywords = {market microstructure noise; optimal sampling; LM test},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Brno},
isbn = {978-80-210-7962-5},
pages = {211-217},
publisher = {Masaryk University},
title = {Optimal Sampling for the Detection of Market Microstructure Noise},
year = {2015}
}
TY - JOUR
ID - 1312614
AU - Hruška, Juraj - Deev, Oleg
PY - 2015
TI - Optimal Sampling for the Detection of Market Microstructure Noise
PB - Masaryk University
CY - Brno
SN - 9788021079625
KW - market microstructure noise
KW - optimal sampling
KW - LM test
N2 - Volatility patterns and its dynamics are the core measures of risk in the financial theory. However, given the algorithmic nature of modern securities trading, frequently used parametric volatility models should be used with great caution when applied on high frequency data. Modelling volatility in high frequency data is fairly complex since such data contains a disruptive volatility component, which only occurs in this kind of data and is not observable in lower frequency data. This phenomenon is usually called market microstructure noise. It is mostly caused by bid ask bounce, so its presence is not so significant in assets with lower spreads. This paper focuses on the comparison of two approaches and simulations to identify market microstructure noise and derive optimal samples for measuring volatility. These tests are implemented on the high frequency trading data from the German Stock Exchange. Our paper provides high-frequency data optimal sampling solutions for risk managers and active investors.
ER -
HRUŠKA, Juraj a Oleg DEEV. Optimal Sampling for the Detection of Market Microstructure Noise. In \textit{European Financial Systems 2015. Proceedings of the 12th International Scientific Conference}. Brno: Masaryk University, 2015, s.~211-217. ISBN~978-80-210-7962-5.
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