Double Standard (TSE:3925) Debt-to-Revenue : 0.00 (As of Dec. 2023)

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What is Double Standard Debt-to-Revenue?

Debt-to-Revenue measures a company's ability to pay off its debt.

Double Standard's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was 円0 Mil. Double Standard's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was 円0 Mil. Double Standard's annualized Revenue for the quarter that ended in Dec. 2023 was 円7,273 Mil. Double Standard's annualized Debt-to-Revenue for the quarter that ended in Dec. 2023 was 0.00.

Double Standard Debt-to-Revenue Historical Data

The historical data trend for Double Standard's Debt-to-Revenue 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.

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Double Standard Debt-to-Revenue Chart

Double Standard Annual Data

Trend

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Mar21

Mar22

Mar23

Debt-to-Revenue

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Double Standard Quarterly Data
	Mar19	Jun19	Sep19	Dec19	Mar20	Jun20	Sep20	Dec20	Mar21	Jun21	Sep21	Dec21	Mar22	Jun22	Sep22	Dec22	Mar23	Jun23	Sep23	Dec23
Debt-to-Revenue	Get a 7-Day Free Trial															-	-	-	-	-

Competitive Comparison of Double Standard's Debt-to-Revenue

For the Information Technology Services subindustry, Double Standard's Debt-to-Revenue, along with its competitors' market caps and Debt-to-Revenue 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.

Double Standard's Debt-to-Revenue Distribution in the Software Industry

For the Software industry and Technology sector, Double Standard's Debt-to-Revenue distribution charts can be found below:

* The bar in red indicates where Double Standard's Debt-to-Revenue falls into.

Double Standard Debt-to-Revenue Calculation

Debt-to-Revenue measures a company's ability to pay off its debt.

Double Standard's Debt-to-Revenue for the fiscal year that ended in Mar. 2023 is calculated as

Debt-to-Revenue	=	Total Debt			/	Revenue
	=	(Short-Term Debt & Capital Lease Obligation	+	Long-Term Debt & Capital Lease Obligation)	/	Revenue
	=	(0	+	0)	/	6911.071
	=	0.00

Double Standard's annualized Debt-to-Revenue for the quarter that ended in Dec. 2023 is calculated as

Debt-to-Revenue	=	Total Debt			/	Revenue
	=	(Short-Term Debt & Capital Lease Obligation	+	Long-Term Debt & Capital Lease Obligation)	/	Revenue
	=	(0	+	0)	/	7272.728
	=	0.00

In the calculation of annual Debt-to-Revenue, the Revenue of the last fiscal year is used. In calculating the annualized quarterly data, the Revenue data used here is four times the quarterly (Dec. 2023) Revenue data.

Double Standard Debt-to-Revenue Related Terms

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Double Standard (TSE:3925) Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Technology » Software » Double Standard Inc (TSE:3925) » Definitions » Debt-to-Revenue

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Address

3-3-3 Akasaka, 4th Floor, Sumitomo Life Akasaka Building, Minato-ku, Tokyo, JPN, 107-0052

Website

http://www.double-std.com

Double Standard Inc is a business support company, engages in the generation and provision of enterprise big data. It also provides service planning and system development services using technology developed in the data generation process. The company operates through two business divisions: Big Data related business and the Services Planning Development business. The Big Data related business mainly provides customers the data related to the operation support and business reduction, as well as the high utilization value content, among others. The Services Planning Development business mainly provides services based on the research of the way of customer and enterprise business process, using the information collection, processing and matching, as well as the data cleansing technology.

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