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Performance of information criteria for selection of Hawkes process models of financial data

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posted on 2023-06-09, 08:38 authored by J M Chen, A G Hawkes, Enrico Scalas, M Trinh
We test three common information criteria (IC) for selecting the order of a Hawkes process with an intensity kernel that can be expressed as a mixture of exponential terms. These processes find application in high-frequency financial data modelling. The information criteria are Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and the Hannan-Quinn criterion (HQ). Since we work with simulated data, we are able to measure the performance of model selection by the success rate of the IC in selecting the model that was used to generate the data. In particular, we are interested in the relation between correct model selection and underlying sample size. The analysis includes realistic sample sizes and parameter sets from recent literature where parameters were estimated using empirical financial intra-day data. We compare our results to theoretical predictions and similar empirical findings on the asymptotic distribution of model selection for consistent and inconsistent IC.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Quantitative Finance

ISSN

1469-7688

Publisher

Taylor & Francis

Issue

2

Volume

18

Page range

225-235

Department affiliated with

  • Mathematics Publications

Research groups affiliated with

  • Probability and Statistics Research Group Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2017-11-06

First Open Access (FOA) Date

2019-06-19

First Compliant Deposit (FCD) Date

2017-11-06

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