Modelling the dynamics of the limit order book in financial markets

dc.contributor.advisor Dunsmuir, William en_US
dc.contributor.advisor Peters, Gareth en_US Richards, Kylie-Anne en_US 2022-03-15T12:16:49Z 2022-03-15T12:16:49Z 2019 en_US
dc.description.abstract This thesis develops models and methods for the statistical properties of the limit order book for financial markets, a complex dynamical system of orders and cancellations, in continuous time and at multiple price levels. Initially, the heavy tailed features of limit order book volumes, aggregated to short, evenly spaced time intervals are investigated. These are found to require heavy tailed distributional models to adequately capture their statistical features. A novel process to transform the physically operating order book into data suitable for analysis is presented. Limitations for point process modelling, such as events frequently occurring at the same time, are established. The marked Hawkes process is identified as a suitable model for event clustering. This overcomes many data constraints by aggregating events, allowing additional information potentially impacting the intensity, to be incorporated in marks attached to these events. Marks are identified by empirical research, which is guided by available literature. A detailed description, methods of simulation, and parameter estimation of the univariate Hawkes process with multivariate marks is presented. This incorporates dependence features via copula models, with heavy tailed marginal distributions and requires substantial MATLAB implementation. Joint estimation via maximum likelihood, with the number and complexity of identified marks, necessitates the development of a method for screening marks that is computationally straightforward to implement. This new approach is based on the score test, which only requires the single fitting of the unboosted Hawkes process to the sequence of observed event times, together with the estimates of the moments of the functions of marks under assessment. The moments can be obtained parametrically, or non-parametrically. The test has an asymptotic chi-squared distribution under the null hypothesis that the marks do not impact the intensity. Extensive simulations confirm the power and utility of the test under realistic models and sample sizes. Application of the score test is made to futures data, and the identified serial dependence of the marks, leads to the new decoupled approximate method of likelihood estimation. This reduces model assumptions on statistical properties of the marks and leads to good performance of Hawkes process parameter estimation. en_US
dc.language English
dc.language.iso EN en_US
dc.publisher UNSW, Sydney en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri en_US
dc.subject.other Screening marks en_US
dc.subject.other Marked Hawkes point process en_US
dc.subject.other Score test statistic en_US
dc.subject.other High frequency financial data en_US
dc.subject.other Heavy tailed distributions en_US
dc.subject.other Futures en_US
dc.subject.other Limit order book en_US
dc.title Modelling the dynamics of the limit order book in financial markets en_US
dc.type Thesis en_US
dcterms.accessRights open access
dcterms.rightsHolder Richards, Kylie-Anne
dspace.entity.type Publication en_US
unsw.accessRights.uri 2021-04-01 en_US
unsw.description.embargoNote Embargoed until 2021-04-01
unsw.relation.faculty Science
unsw.relation.originalPublicationAffiliation Richards, Kylie-Anne, Mathematics & Statistics, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Dunsmuir, William, Mathematics & Statistics, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Peters, Gareth, Heriot-Watt University en_US School of Mathematics & Statistics *
unsw.thesis.degreetype PhD Doctorate en_US
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
public version.pdf
10.62 MB
Resource type