Resqunit AB (OSTO:RESQ) Scaled Net Operating Assets : 0.61 (As of Jun. 2023)

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What is Resqunit AB Scaled Net Operating Assets?

Scaled Net Operating Assets (SNOA) is calculated as the difference between operating assets and operating liabilities, scaled by lagged total assets.

Resqunit AB's operating assets for the quarter that ended in Jun. 2023 was kr10.91 Mil. Resqunit AB's operating liabilities for the quarter that ended in Jun. 2023 was kr1.06 Mil. Resqunit AB's Total Assets for the quarter that ended in Dec. 2022 was kr16.26 Mil. Therefore, Resqunit AB's scaled net operating assets (SNOA) for the quarter that ended in Jun. 2023 was 0.61.

Resqunit AB Scaled Net Operating Assets Historical Data

The historical data trend for Resqunit AB's Scaled Net Operating Assets 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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Resqunit AB Scaled Net Operating Assets Chart

Resqunit AB Annual Data

Trend

Dec21

Dec22

Scaled Net Operating Assets

0.32

0.65

Resqunit AB Semi-Annual Data
	Jun21	Jun22	Dec22	Jun23
Scaled Net Operating Assets	-	-	1.03	0.61

Competitive Comparison of Resqunit AB's Scaled Net Operating Assets

For the Pollution & Treatment Controls subindustry, Resqunit AB's Scaled Net Operating Assets, along with its competitors' market caps and Scaled Net Operating Assets 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.

Resqunit AB's Scaled Net Operating Assets Distribution in the Industrial Products Industry

For the Industrial Products industry and Industrials sector, Resqunit AB's Scaled Net Operating Assets distribution charts can be found below:

* The bar in red indicates where Resqunit AB's Scaled Net Operating Assets falls into.

Resqunit AB Scaled Net Operating Assets Calculation

Scaled Net Operating Assets (SNOA) is calculated as the difference between operating assets and operating liabilities, scaled by lagged total assets.

Resqunit AB's Scaled Net Operating Assets (SNOA) for the fiscal year that ended in Dec. 2022 is calculated as

	Scaled Net Operating Assets (SNOA)		(A: Dec. 2022 )
=	(Operating Assets (A: Dec. 2022 )	-	Operating Liabilities (A: Dec. 2022 ))	/	Total Assets (A: Dec. 2021 )
=	(12.305	-	2.635)	/	14.777
=	0.65

where

	Operating Assets		(A: Dec. 2022 )
=	Total Assets	-	Cash, Cash Equivalents, Marketable Securities
=	16.256	-	3.951
=	12.305

	Operating Liabilities		(A: Dec. 2022 )
=	Total Liabilities	-	Long-Term Debt & Capital Lease Obligation	-	Short-Term Debt & Capital Lease Obligation
=	12.228	-	5.286	-	4.307
=	2.635

Resqunit AB's Scaled Net Operating Assets (SNOA) for the quarter that ended in Jun. 2023 is calculated as

	Scaled Net Operating Assets (SNOA)		(Q: Jun. 2023 )
=	(Operating Assets (Q: Jun. 2023 )	-	Operating Liabilities (Q: Jun. 2023 ))	/	Total Assets (Q: Dec. 2022 )
=	(10.907	-	1.055)	/	16.256
=	0.61

where

	Operating Assets		(Q: Jun. 2023 )
=	Total Assets	-	Cash, Cash Equivalents, Marketable Securities
=	11.988	-	1.081
=	10.907

	Operating Liabilities		(Q: Jun. 2023 )
=	Total Liabilities	-	Long-Term Debt & Capital Lease Obligation	-	Short-Term Debt & Capital Lease Obligation
=	9.161	-	5.048	-	3.058
=	1.055

Resqunit AB Scaled Net Operating Assets Related Terms

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Resqunit AB (OSTO:RESQ) Business Description

Industry

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Comparable Companies

Traded in Other Exchanges

N/A

Address

Grenseveien 21, Sandnes, NOR, 4313

Website

https://www.resqunit.com

Resqunit AB is an ocean tech company developing innovative equipment to disarm and retrieve lost fishing gear. Through sensor data collection and software, the company aims to increase knowledge about the oceans and increase catch predictability.

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