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Appen (APXYY) Gross-Profit-to-Asset % : 152.45% (As of Jun. 2024)


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What is Appen Gross-Profit-to-Asset %?

Gross-Profit-to-Asset % is calculated as Gross Profit divided by its average Total Assets over a certain period of time. Appen's annualized Gross Profit for the quarter that ended in Jun. 2024 was $226.9 Mil. Appen's average Total Assets over the quarter that ended in Jun. 2024 was $148.8 Mil. Therefore, Appen's annualized Gross-Profit-to-Asset % for the quarter that ended in Jun. 2024 was 152.45%.


Appen Gross-Profit-to-Asset % Historical Data

The historical data trend for Appen's Gross-Profit-to-Asset % can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

* Premium members only.

Appen Gross-Profit-to-Asset % Chart

Appen Annual Data
Trend Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Gross-Profit-to-Asset %
Get a 7-Day Free Trial Premium Member Only 122.54 101.78 93.11 102.97 133.14

Appen Semi-Annual Data
Jun15 Dec15 Jun16 Dec16 Jun17 Dec17 Jun18 Dec18 Jun19 Dec19 Jun20 Dec20 Jun21 Dec21 Jun22 Dec22 Jun23 Dec23 Jun24
Gross-Profit-to-Asset % Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only 74.99 112.28 110.69 133.30 152.45

Competitive Comparison of Appen's Gross-Profit-to-Asset %

For the Information Technology Services subindustry, Appen's Gross-Profit-to-Asset %, along with its competitors' market caps and Gross-Profit-to-Asset % data, can be viewed below:

* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.


Appen's Gross-Profit-to-Asset % Distribution in the Software Industry

For the Software industry and Technology sector, Appen's Gross-Profit-to-Asset % distribution charts can be found below:

* The bar in red indicates where Appen's Gross-Profit-to-Asset % falls into.



Appen Gross-Profit-to-Asset % Calculation

Appen's annualized Gross-Profit-to-Asset % for the fiscal year that ended in Dec. 2023 is calculated as:

Gross-Profit-to-Asset %=Gross Profit (A: Dec. 2023 )/( (Total Assets (A: Dec. 2022 )+Total Assets (A: Dec. 2023 ))/ count )
=273.012/( (254.941+155.158)/ 2 )
=273.012/205.0495
=133.14 %

Appen's annualized Gross-Profit-to-Asset % for the quarter that ended in Jun. 2024 is calculated as:

Gross-Profit-to-Asset %=Gross Profit (Q: Jun. 2024 )/( (Total Assets (Q: Dec. 2023 )+Total Assets (Q: Jun. 2024 ))/ count )
=226.854/( (155.158+142.462)/ 2 )
=226.854/148.81
=152.45 %

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

In the calculation of annual Gross-Profit-to-Asset %, the Gross Profit of the last fiscal year and the average total assets over the fiscal year are used. In calculating the quarterly data, the Gross Profit data used here is two times the semi-annual (Jun. 2024) data. Gross-Profit-to-Asset % is displayed in the 30-year financial page.


Appen Gross-Profit-to-Asset % Related Terms

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Appen Business Description

Industry
Traded in Other Exchanges
Address
9 Help Street, Level 6, Chatswood, Sydney, NSW, AUS, 2067
Appen Ltd is engaged in the provision of quality data solutions and services for machine learning and artificial intelligence applications for technology companies, auto manufacturers, government agencies among others. The company's business segments are Global services and New markets. It generates maximum revenue from the Global services segment which represents the services that it provides to technology customers using the customers' data annotation platforms and tools. The majority of projects comprise large, at-scale deep learning (model evaluation) programs. Geographically, it derives a majority of its revenue from the United States of America.