EconPapers    
Economics at your fingertips  
 

Modeling non-stationarities in high-frequency financial time series

Linda Ponta, Mailan Trinh, Marco Raberto (), Enrico Scalas () and Silvano Cincotti ()

Papers from arXiv.org

Abstract: We study tick-by-tick financial returns belonging to the FTSE MIB index of the Italian Stock Exchange (Borsa Italiana). We can confirm previously detected non-stationarities. However, scaling properties reported in the previous literature for other high-frequency financial data are only approximately valid. As a consequence of the empirical analyses, we propose a simple method for describing non-stationary returns, based on a non-homogeneous normal compound Poisson process. We test this model against the empirical findings and it turns out that the model can approximately reproduce several stylized facts of high-frequency financial time series. Moreover, using Monte Carlo simulations, we analyze order selection for this model class using three information criteria: Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and the Hannan-Quinn information criterion (HQ). For comparison, we also perform a similar Monte Carlo experiment for the ACD (autoregressive conditional duration) model. Our results show that the information criteria work best for small parameter numbers for the compound Poisson type models, whereas for the ACD model the model selection procedure does not work well in certain cases.

Date: 2012-12, Revised 2017-02
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://arxiv.org/pdf/1212.0479 Latest version (application/pdf)

Related works:
Journal Article: Modeling non-stationarities in high-frequency financial time series (2019) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1212.0479

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().

 
Page updated 2021-10-24
Handle: RePEc:arx:papers:1212.0479