2017
DOI: 10.1016/j.jedc.2017.04.004
|View full text |Cite
|
Sign up to set email alerts
|

Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data

Abstract: This study examine the theoretical and empirical perspectives of the symmetric Hawkes model of the price tick structure. Combined with the maximum likelihood estimation, the model provides a proper method of volatility estimation specialized in ultra-high-frequency analysis. Empirical studies based on the model using the ultra-high-frequency data of stocks in the S&P 500 are performed. The performance of the volatility measure, intraday estimation, and the dynamics of the parameters are discussed. A new approa… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

2
9
0

Year Published

2017
2017
2024
2024

Publication Types

Select...
7

Relationship

4
3

Authors

Journals

citations
Cited by 14 publications
(11 citation statements)
references
References 52 publications
(48 reference statements)
2
9
0
Order By: Relevance
“…We formally test jump propagation using the Hawkes process (Hawkes, 1971). 21 This process is a self-excited point process whose intensity depends on the path followed by the point process and has been extensively used in different domains such as seismology and neurology, but only recently in finance to model the dynamics of microstructure prices (Lee and Seo, 2017), trading activity, and asset jumps in financial markets (Ait-Sahalia et al, 2015;Bormetti et al, 2015). For example, Ait-Sahalia et al The univariate Hawkes process we use to capture the time clustering of intraday jumps for each of the ETFs is given by:…”
Section: Time and Space Clustering Of Intraday Jumpsmentioning
confidence: 99%
“…We formally test jump propagation using the Hawkes process (Hawkes, 1971). 21 This process is a self-excited point process whose intensity depends on the path followed by the point process and has been extensively used in different domains such as seismology and neurology, but only recently in finance to model the dynamics of microstructure prices (Lee and Seo, 2017), trading activity, and asset jumps in financial markets (Ait-Sahalia et al, 2015;Bormetti et al, 2015). For example, Ait-Sahalia et al The univariate Hawkes process we use to capture the time clustering of intraday jumps for each of the ETFs is given by:…”
Section: Time and Space Clustering Of Intraday Jumpsmentioning
confidence: 99%
“…As a pioneering work, Bowsher (2007) introduce a bivariate Hawkes processes to model the joint dynamics of trades and mid-price changes in NYSE stocks. After that, many studies related to high-frequency finance have employed Hawkes processes (Bacry et al, 2012;Bacry et al, 2013;Da Fonseca and Zaatour, 2014;Bacry et al, 2015;Lee and Seo, 2017).…”
Section: The Hawkes Flocking Modelmentioning
confidence: 99%
“…Bacry and Muzy (2016) Bacry and Muzy (2014) to explain the behaviour of swap rates. Lee and Seo (2017) examines the theoretical and empirical perspectives for the symmetric Hawkes model of the price tick structure.…”
Section: Introductionmentioning
confidence: 99%