59 Pages Posted: 26 Sep 2015 Last revised: 27 Feb 2017
Date Written: February 24, 2017
In this paper we use an autoregressive conditional intensity approach to estimate local high-frequency volatility and examine to what extent a large universe of market microstructure variables affects local volatility. Our findings support the Mixture-of-Distribution hypothesis on a high-frequency level since we show that contemporaneous trading volume is positively related to local volatility. The use of a penalized likelihood method allows us to obtain a ranking in terms of the relative importance of all market microstructure variables considered. We find that, in a descending order, contemporaneous order flow, number of transactions, bid-ask spread and volume carry the most important information for local volatility modelling.
Keywords: High-Frequency Volatility Estimation, Market Microstructure Effects, Volume-Volatility Relationship, ACI Model
JEL Classification: C58, C52, C41, G12
Suggested Citation: Suggested Citation
Li, Yifan and Nolte, Ingmar and Nolte (Lechner), Sandra, High-Frequency Volatility Estimation and the Relative Importance of Market Microstructure Variables: An Autoregressive Conditional Intensity Approach (February 24, 2017). Available at SSRN: https://ssrn.com/abstract=2665639 or http://dx.doi.org/10.2139/ssrn.2665639