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SMS Co (TSE:2175) Gross-Profit-to-Asset % : 56.87% (As of Dec. 2023)


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What is SMS Co 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. SMS Co's annualized Gross Profit for the quarter that ended in Dec. 2023 was 円40,892 Mil. SMS Co's average Total Assets over the quarter that ended in Dec. 2023 was 円71,909 Mil. Therefore, SMS Co's annualized Gross-Profit-to-Asset % for the quarter that ended in Dec. 2023 was 56.87%.


SMS Co Gross-Profit-to-Asset % Historical Data

The historical data trend for SMS Co'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.

SMS Co Gross-Profit-to-Asset % Chart

SMS Co Annual Data
Trend Mar15 Mar16 Mar17 Mar18 Mar19 Mar20 Mar21 Mar22 Mar23 Mar24
Gross-Profit-to-Asset %
Get a 7-Day Free Trial Premium Member Only Premium Member Only 63.15 63.73 64.97 65.91 69.12

SMS Co Quarterly Data
Jun19 Sep19 Dec19 Mar20 Jun20 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23 Mar24
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 Premium Member Only 64.45 82.35 60.44 56.87 71.39

Competitive Comparison of SMS Co's Gross-Profit-to-Asset %

For the Health Information Services subindustry, SMS Co'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.


SMS Co's Gross-Profit-to-Asset % Distribution in the Healthcare Providers & Services Industry

For the Healthcare Providers & Services industry and Healthcare sector, SMS Co's Gross-Profit-to-Asset % distribution charts can be found below:

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



SMS Co Gross-Profit-to-Asset % Calculation

SMS Co's annualized Gross-Profit-to-Asset % for the fiscal year that ended in Mar. 2024 is calculated as:

Gross-Profit-to-Asset %=Gross Profit (A: Mar. 2024 )/( (Total Assets (A: Mar. 2023 )+Total Assets (A: Mar. 2024 ))/ count )
=47543/( (65098+72475)/ 2 )
=47543/68786.5
=69.12 %

SMS Co's annualized Gross-Profit-to-Asset % for the quarter that ended in Dec. 2023 is calculated as:

Gross-Profit-to-Asset %=Gross Profit (Q: Dec. 2023 )/( (Total Assets (Q: Sep. 2023 )+Total Assets (Q: Dec. 2023 ))/ count )
=40892/( (72727+71090)/ 2 )
=40892/71908.5
=56.87 %

* 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 four times the quarterly (Dec. 2023) data. Gross-Profit-to-Asset % is displayed in the 30-year financial page.


SMS Co Gross-Profit-to-Asset % Related Terms

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SMS Co (TSE:2175) Business Description

Traded in Other Exchanges
Address
Sumitomo Fudosan Shiba-koen Tower, 2-11-1 Shiba-koen, Minato-ku, Tokyo, JPN, 105-0011
SMS Co Ltd is a Japanese company involved in providing various services targeting information infrastructure for the aging society. The company divides its search service by the following segments: nursing care, medical care, career, healthcare/senior life, and global.

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