Article “Reverse Leveraged Buy-Out” in French Wikipedia has 3.4 points for quality (as of July 1, 2025). The article contains 0 references and 4 sections.
Since the creation of article “Reverse Leveraged Buy-Out”, its content was written by 13 registered users of French Wikipedia and edited by 13 registered Wikipedia users in all languages.
The article is cited 2 times in French Wikipedia and cited 2 times in all languages.
The highest Authors Interest rank from 2001:
The highest popularity rank from 2008:
There is 1 language version for this article in the WikiRank database (of the considered 55 Wikipedia language editions).
The quality and popularity assessment was based on Wikipédia dumps from July 1, 2025 (including revision history and pageviews for previous years).
| Best Rank | French: #376679 10.2008 |
Global: #3180429 10.2008 |
| Best Rank | French: #30971 01.2009 |
Global: #510775 01.2009 |
On 16 March 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: 98th Academy Awards, Michael B. Jordan, Sinners, Jessie Buckley, Paul Thomas Anderson, Sean Penn, One Battle After Another, Amy Madigan, Hamnet, Timothée Chalamet.
In French Wikipedia the most popular articles on that day were: Bruno Salomone, 98e cérémonie des Oscars, Sarah Knafo, Stéphane Audran, Une bataille après l'autre, Michael B. Jordan, Élections municipales de 2026 à Paris, Emmanuel Grégoire, Les Noces rouges, Sinners (film).
The WikiRank project is intended for automatic relative evaluation of the articles in the various language versions of Wikipedia. At the moment the service allows to compare over 44 million Wikipedia articles in 55 languages. Quality scores of articles are based on Wikipedia dumps from July, 2025. When calculating current popularity and AI of articles data from June 2025 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2025... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(1.78+0+0+15.38+0)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
