Stella Diagnostics (Stella Diagnostics) Inventory Turnover : 0.00 (As of Sep. 2023)

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What is Stella Diagnostics Inventory Turnover?

Inventory Turnover measures how fast the company turns over its inventory within a year. It is calculated as Cost of Goods Sold divided by Total Inventories. Stella Diagnostics's Cost of Goods Sold for the three months ended in Sep. 2023 was $0.00 Mil. Stella Diagnostics's Average Total Inventories for the quarter that ended in Sep. 2023 was $0.00 Mil.

Days Inventory indicates the number of days of goods in sales that a company has in the inventory.

Inventory-to-Revenue determines the ability of a company to manage their inventory levels. It measures the percentage of Inventories the company currently has on hand to support the current amount of Revenue.

Stella Diagnostics Inventory Turnover Historical Data

The historical data trend for Stella Diagnostics's Inventory Turnover 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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Stella Diagnostics Inventory Turnover Chart

Stella Diagnostics Annual Data

Trend

Inventory Turnover

Stella Diagnostics Quarterly Data
	Sep22	Sep23
Inventory Turnover	-	-

Stella Diagnostics Inventory Turnover Calculation

Stella Diagnostics's Inventory Turnover for the fiscal year that ended in . 20 is calculated as

	Inventory Turnover (A: . 20 )
=	Cost of Goods Sold	/	Average Total Inventories
=	Cost of Goods Sold (A: . 20 )	/ (	(Total Inventories (A: . 20 )	+	Total Inventories (A: . 20 ))	/	count )
=		/ (	(	+	)	/	1 )
=		/	0
=	N/A

Stella Diagnostics's Inventory Turnover for the quarter that ended in Sep. 2023 is calculated as

	Inventory Turnover (Q: Sep. 2023 )
=	Cost of Goods Sold	/	Average Total Inventories
=	Cost of Goods Sold (Q: Sep. 2023 )	/ (	(Total Inventories (Q: Sep. 2022 )	+	Total Inventories (Q: Sep. 2023 ))	/	count )
=	0	/ (	(0	+	0)	/	1 )
=	0	/	0
=	N/A

Stella Diagnostics (OTCPK:SLDX) Inventory Turnover Explanation

Inventory Turnover measures how fast the company turns over its inventory within a year. A higher Inventory Turnover means the company has light inventory. Therefore the company spends less money on storage, write downs, and obsolete inventory. If the inventory is too light, it may affect sales because the company may not have enough to meet demand.

1. Days Inventory indicates the number of days of goods in sales that a company has in the inventory.

Stella Diagnostics's Days Inventory for the three months ended in Sep. 2023 is calculated as:

Days Inventory	=	Average Total Inventories (Q: Sep. 2023 )	/	Cost of Goods Sold (Q: Sep. 2023 )	*	Days in Period
	=	0	/	0	*	365 / 4
	=

2. Inventory-to-Revenue determines the ability of a company to manage their inventory levels. It measures the percentage of Inventories the company currently has on hand to support the current amount of Revenue.

Stella Diagnostics's Inventory to Revenue for the quarter that ended in Sep. 2023 is calculated as

Inventory-to-Revenue	=	Average Total Inventories (Q: Sep. 2023 )	/	Revenue (Q: Sep. 2023 )
	=	0	/	0
	=

Be Aware

Usually retailers pile up their inventories at holiday seasons to meet the stronger demand. Therefore, the inventory of a particular quarter of a year should not be used to calculate Inventory Turnover. An average inventory is a better indication.

Stella Diagnostics Inventory Turnover Related Terms

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Stella Diagnostics (Stella Diagnostics) Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Healthcare » Medical Diagnostics & Research » Stella Diagnostics Inc (OTCPK:SLDX) » Definitions » Inventory Turnover

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Traded in Other Exchanges

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Address

50 West Broadway, Suite 300, Salt Lake City, UT, USA, 84104

Website

https://www.stelladx.com

Stella Diagnostics Inc is a molecular diagnostics-based organization focused on improving patient management strategies for people living with severe esophageal disease. It is developing first-line diagnostic tools that provide superior molecular information for providers as compared to the current standard screening protocols.