Persistence in High Frequency Financial Data

Guglielmo Maria Caporale and Alex Plastun

No 10045, CESifo Working Paper Series from CESifo

Abstract: This paper investigates persistence in high-frequency, intraday data (and also daily and monthly ones) in the case of the EuroStoxx 50 futures over the period from 2002 to 2018 (720 million trade records) using R/S analysis and the Hurst exponent as a measure of persistence. The results indicate that persistence is sensitive to the data frequency. More specifically, monthly data are highly persistent, daily ones follow a random walk, and intraday ones are anti-persistent. In addition, persistence varies over time. These findings imply that the Efficient Market Hypothesis (EMH) only holds in the case of daily data, whilst it is possible to make abnormal profits using trading strategies based on reversal strategies at the intraday frequency.

Keywords: persistence; long memory; R/S analysis; high-frequency data (search for similar items in EconPapers)
JEL-codes: C22 G12 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.cesifo.org/DocDL/cesifo1_wp10045.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 503 Service Unavailable

Related works:
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:ces:ceswps:_10045

Access Statistics for this paper

More papers in CESifo Working Paper Series from CESifo Contact information at EDIRC.
Bibliographic data for series maintained by Klaus Wohlrabe ().