Talk:High frequency data

Wiki Education Foundation-supported course assignment

This article is or was the subject of a Wiki Education Foundation-supported course assignment. Further details are available on the course page. Student editor(s): Donatozleone. Peer reviewers: Louise Yang, Gooddigitalcitizen, Michael paul72.

Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT (talk) 22:20, 17 January 2022 (UTC)

Cappa's Peer Review

First, what does the article do well? Is there anything from your review that impressed you? Any turn of phrase that described the subject in a clear way?

Excellent work Donaldo, simply excellent. The article encapsulates high frequency data as a whole, what its specific uses are, what the criteria and forms are that define high frequency data, and the specific work of Robert F. Engle that has contributed substantially to the field. This was an excellent overview of high frequency data; nearly ready for official publishing I'd say.

What changes would you suggest the author apply to the article? Why would those changes be an improvement?

Perhaps for your final draft, include some sort of info graphic that nicely outlines the high frequency forms, as well as a chart with Engle's contributions to the field. I'd also include a section with some notable players in this industry (data brokers, big banks, etc.), as well as a picture of Engle.

What's the most important thing the author could do to improve the article?

Some infographics and illustrations would really put this article above and beyond the rest.

Did you notice anything about the article you reviewed that could be applicable to your own article? Let them know!

Your article was very concise and objective thus far, which is good! This is something I 100% need to apply to my article as mine reads more as original scholarship than an objective account of the issue, which is the main standard of Wikipedia's dogma/standards.

Michael paul72contribs) 7:28am, 9 November 2017 (UTC)

Liv's Peer Review

What does the article do well? Is there anything from your review that impressed you? Any turn of phrase that described the subject in a clear way?

The draft demonstrates a clear understanding of the concept of high frequency data. Considering that high frequency data is an extremely technical subject that is difficult for even some professionals to grasp, this is an enormous feat. The article also does an excellent job of detailing the different uses and contexts of which high frequency data are a part of. Furthermore, the author did a good job in keeping the wording neutral and encyclopedia-like, the draft did not read as if it were an argumentative paper.

What changes would you suggest the author apply to the article? Why would those changes be an improvement?

Overall, there are not many changes I would suggest for the article. Perhaps it may be interesting to glean some connections from the Wikipedia page for high-frequency trading and talk a little bit about the algorithms involved on a basic level (nothing extremely technical). It might also be interesting to include one more case for high frequency data if such exists (Is there anything in science?) or any sort of issues that surround high frequency data (Is there any privacy or security concerns associated with it? Any ethical issues?). These suggestions would help to create a more all-encompassing article and provide an opportunity for different people to contribute to the page (if the suggestions are valid).

What's the most important thing the author could do to improve the article?

The most important thing to do to improve the article at this point is to add a few more sources and fix a few typos (Properties in Economic Analysis, High frequency data are [instead of "is"]). Gooddigitalcitizen (talk) 00:50, 9 November 2017 (UTC)

Peer Review from Louise Yang

* Is everything in the article relevant to the article topic? Is there anything that distracted you?

The topic is expanded in a clear structure with everything mentioned associative to the main theme. Nothing distracted me when reading the page.

* Is the article neutral? Are there any claims, or frames, that appear heavily biased toward a particular position?

The article tends to be neutral and objective, and I can see efforts made by the editor to tell both advantages and disadvantages of different High Frequency Forms. I’m also looking forward to some of the negative facts of using High Frequency Data.

* Are there viewpoints that are overrepresented, or underrepresented?

I’m expecting to see more information on the introduction of High Frequency Forms, and it would be better if the editor can add some case studies examples to each for the forms, such as big companies who use each form.

* Check the citations. Do the links work? Does the source support the claims in the article?

References are stated as “Studies using High Frequency Data” in a separated section, and the possible sources listed are also reasonable. However, this might arouse confusion for people visiting the page. The citations all support the statements of the editor, although none of them are links that I could click on (most are journal articles with a DOI number).

* Is each fact supported by an appropriate, reliable reference? Where does the information come from? Are these neutral sources? If biased, is that bias noted?

Some statements in the article still need references, such as the leading part. Most sources are published journal articles, and some of the ideas are introduced by famous scholars in the field that have earned credibility globally, so I consider the sources as reliable. These sources cover different aspects of the topic and are considered neutral in my opinion.

* Is any information out of date? Is anything missing that should be added?

All information is relevant to the current nature of the topic, and references are also up to date. Some details can still be added to inform amateurs or people who are not so familiar with this topic, such as the difference between “Trade Data” and “Trade and Quote Data”. — Preceding unsigned comment added by Louise Yang (talk • contribs) 01:46, 9 November 2017 (UTC)