HIGH FREQUENCY TRADING

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dc.contributor.advisor Cruciani, Caterina it_IT
dc.contributor.author Mazzer, Eva <1996> it_IT
dc.date.accessioned 2021-05-18 it_IT
dc.date.accessioned 2021-07-22T08:51:33Z
dc.date.available 2021-07-22T08:51:33Z
dc.date.issued 2021-06-11 it_IT
dc.identifier.uri http://hdl.handle.net/10579/19441
dc.description.abstract This paper is going to discuss the role of High Frequency Trading (HTF) in financial market and whether it helps the economy or if it is obstructing other agents in the market. HFT is a subset of the algorithmic trading (‘AT’) distinguished by the speed at which it processes and determines plays in the market. This is due to the sophisticated technology components that are reducing the latency, the time occurring between when the order is placed and when it is executed. The analysis starts from current knowledge of HFT and why its introduction was so revolutionary in the way trading is done today, changing its perception over time. HFT is not just algorithms that help execute orders, but brains that think on their own, making decisions in milliseconds backed by machine learning based on proprietary strategies programmed by a firm. Characterizing the HFT strategies could give an insight into the motives for trading, which could impact market quality, also providing evidence on intraday return predictability. The regulatory and real effects on the market, taking into consideration the so-called flash-crash, particularly the one that occurred on May 6, 2010, will be discussed further in this paper. Ultimately, after the analysis of pros and cons are evaluated, this paper will conclude with the implications surrounding HFT and fairness in the market – which is the main crux of this paper. Human beings are supposed to know what it is right and what it is wrong but trying to put a border between the two of them is not definitively clear with regards to HFT. Using this assumption, a study will be conducted to see if the assumption holds true and whether fairness in the market is adversely affected by HFT. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Eva Mazzer, 2021 it_IT
dc.title HIGH FREQUENCY TRADING it_IT
dc.title.alternative High Frequency Trading and Fairness it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Economia e finanza it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear Sessione-straordinaria-2021_2° finestra_appello_010621 it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 857162 it_IT
dc.subject.miur SECS-S/06 METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend it_IT
dc.provenance.upload Eva Mazzer (857162@stud.unive.it), 2021-05-18 it_IT
dc.provenance.plagiarycheck Caterina Cruciani (cruciani@unive.it), 2021-06-01 it_IT


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