Modeling non-stationarities in high-frequency financial time series
AbstractWe study tick-by-tick financial returns belonging to the FTSE MIB index of the Italian Stock Exchange (Borsa Italiana). We find that non-stationarities detected in other markets in the past are still there. Moreover, scaling properties reported in the previous literature for other high-frequency financial data are approximately valid as well. Finally, we propose a simple method for describing non-stationary returns, based on a non-homogeneous normal compound Poisson process and we test this model against the empirical findings. It turns out that the model can reproduce several stylized facts of high-frequency financial time series.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1212.0479.
Date of creation: Dec 2012
Date of revision: Mar 2013
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-12-10 (All new papers)
- NEP-ECM-2012-12-10 (Econometrics)
- NEP-ETS-2012-12-10 (Econometric Time Series)
- NEP-MST-2012-12-10 (Market Microstructure)
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