DigitalCube Co (TSE:263A) EV-to-EBIT : (As of May. 27, 2025)

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What is DigitalCube Co EV-to-EBIT?

EV-to-EBIT is calculated as Enterprise Value divided by its EBIT. As of today, DigitalCube Co's Enterprise Value is 円368.2 Mil. DigitalCube Co does not have enough years/quarters to calculate its EBIT for the trailing twelve months (TTM) ended in Mar. 2024. Therefore, GuruFocus does not calculate DigitalCube Co's EV-to-EBIT at this moment.

The historical rank and industry rank for DigitalCube Co's EV-to-EBIT or its related term are showing as below:

TSE:263A' s EV-to-EBIT Range Over the Past 10 Years
Min: 0 Med: 0 Max: 30.7
Current: 30.7

During the past 2 years, the highest EV-to-EBIT of DigitalCube Co was 30.70. The lowest was 0.00. And the median was 0.00.

TSE:263A's EV-to-EBIT is not ranked
in the Software industry.
Industry Median: 17.16 vs TSE:263A: 30.70

Joel Greenblatt calls the inversion of this ratio Earnings Yield (Joel Greenblatt) %. DigitalCube Co's Enterprise Value for the quarter that ended in Mar. 2024 was 円0.0 Mil. DigitalCube Co does not have enough years/quarters to calculate its EBIT for the trailing twelve months (TTM) ended in Mar. 2024. Therefore, GuruFocus does not calculate DigitalCube Co's Earnings Yield (Joel Greenblatt) % at this moment.

DigitalCube Co EV-to-EBIT Historical Data

The historical data trend for DigitalCube Co's EV-to-EBIT 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.

DigitalCube Co EV-to-EBIT Chart

DigitalCube Co Annual Data

Trend

Mar23

Mar24

EV-to-EBIT

DigitalCube Co Semi-Annual Data
	Mar23	Mar24
EV-to-EBIT	-	-

Competitive Comparison of DigitalCube Co's EV-to-EBIT

For the Information Technology Services subindustry, DigitalCube Co's EV-to-EBIT, along with its competitors' market caps and EV-to-EBIT 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.

DigitalCube Co's EV-to-EBIT Distribution in the Software Industry

For the Software industry and Technology sector, DigitalCube Co's EV-to-EBIT distribution charts can be found below:

* The bar in red indicates where DigitalCube Co's EV-to-EBIT falls into.

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DigitalCube Co EV-to-EBIT Calculation

DigitalCube Co's EV-to-EBIT for today is calculated as:

EV-to-EBIT	=	Enterprise Value (Today)	/	EBIT (TTM)
	=	368.221	/
	=

DigitalCube Co (TSE:263A) EV-to-EBIT Explanation

This is a more accurate valuation of companies' operation because it considers the debt and cash on its balance sheet, and non-operating items such as interest payment, tax, and one-time items are not included in the Operating Income.

Joel Greenblatt calls the inversion of this ratio Earnings Yield (Joel Greenblatt) %.

DigitalCube Co's Earnings Yield (Joel Greenblatt) % for the quarter that ended in Mar. 2024 is calculated as:

Earnings Yield (Joel Greenblatt) % (Q: Mar. 2024 )	=	EBIT	/	Enterprise Value (Q: Mar. 2024 )
	=		/	0
	=	%

DigitalCube Co EV-to-EBIT Related Terms

Thank you for viewing the detailed overview of DigitalCube Co's EV-to-EBIT provided by GuruFocus.com. Please click on the following links to see related term pages.

DigitalCube Co Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Technology » Software » DigitalCube Co Ltd (TSE:263A) » Definitions » EV-to-EBIT

Comparable Companies

Traded in Other Exchanges

N/A

Address

5 Kaigandori, Chuo-ku, Hyogo, Kobe, JPN, 650-0024

Website

https://www.digitalcube.jp

DigitalCube Co Ltd is engaged in managing website hosting, design, maintenance, production and maintenance of AI, machine learning systems in cloud transition.

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