NVIDIA (LIM:NVDA) Change In Working Capital

: $-3,722 Mil (TTM As of Jan. 2024)

View and export this data going back to 2019. Start your Free Trial

NVIDIA's change in working capital for the quarter that ended in Jan. 2024 was $-1,719 Mil.

NVIDIA's change in working capital for the fiscal year that ended in Jan. 2024 was $-3,722 Mil.

It is calculated by adding the items under "Change in operating assets and liabilities" (may refer to a different name for different company) section in Cash Flow Statement. Not by calculating the number changes in each periods' working capital (Total Current Assets minus Total Current Liabilities).

NVIDIA Change In Working Capital Historical Data

The historical data trend for NVIDIA's Change In Working Capital 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.

NVIDIA Annual Data

Trend

Jan15

Jan16

Jan17

Jan18

Jan19

Jan20

Jan21

Jan22

Jan23

Jan24

Change In Working Capital

Get a 7-Day Free Trial

717.00

-703.00

-3,363.00

-2,207.00

-3,722.00

NVIDIA Quarterly Data
	Apr19	Jul19	Oct19	Jan20	Apr20	Jul20	Oct20	Jan21	Apr21	Jul21	Oct21	Jan22	Apr22	Jul22	Oct22	Jan23	Apr23	Jul23	Oct23	Jan24
Change In Working Capital	Get a 7-Day Free Trial															287.00	904.00	-174.00	-2,733.00	-1,719.00

NVIDIA Change In Working Capital Calculation

Change In Working Capital for the trailing twelve months (TTM) ended in Jan. 2024 adds up the quarterly data reported by the company within the most recent 12 months, which was $-3,722 Mil.

Working Capital is a measure of a company's short term liquidity or its ability to cover short term liabilities. It is defined as the difference between a company's current assets and current liabilities.

Changes in Working Capital is reported in the cash flow statement since it is one of the major ways in which net income can differ from operating cash flow. It is calculated by adding the items under "Change in operating assets and liabilities" (may refer to a different name for different company) section in Cash Flow Statement.

Use Wal-Mart Stores Inc (Jan 2014, Annual Data) as an example: Source: Wal-Mart Stores Inc 2014-01-31 10-K from SEC

Consolidated Statements of Cash Flows	Fiscal Years Ended	January 31,	(Amounts in millions)
Cash flows from operating activities:	2014	2013	2012
Changes in certain assets and liabilities, net of effects of acquisitions:
Receivables, net	(566)	(614)	(796)
Inventories	(1,667)	(2,759)	(3,727)
Accounts payable	531	1,061	2,687
Accrued liabilities	103	271	(935)
Accrued income taxes	(1,224)	981	994

For 2014-01-31, add all the items under 2014 collum together, Change in Working Capital was (566) + (1,667) + 531 + 103 + (1,224) = $ (2,823) Mil.

NVIDIA Change In Working Capital Related Terms

Thank you for viewing the detailed overview of NVIDIA's Change In Working Capital provided by GuruFocus.com. Please click on the following links to see related term pages.

NVIDIA (LIM:NVDA) Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Technology » Semiconductors » NVIDIA Corp (LIM:NVDA) » Definitions » Change In Working Capital

Comparable Companies

Traded in Other Exchanges

NVDA:USA NVDA:Mexico NVDA_KZ:Kazakhstan NVDA:Italy NVDd:UK 0R1I:UK NVD:Germany NVDA:Canada NVDC34:Brazil NVDA:Austria NVDA:Argentina

Address

2788 San Tomas Expressway, Santa Clara, CA, USA, 95051

Website

https://www.nvidia.com

Nvidia is a leading developer of graphics processing units. Traditionally, GPUs were used to enhance the experience on computing platforms, most notably in gaming applications on PCs. GPU use cases have since emerged as important semiconductors used in artificial intelligence. Nvidia not only offers AI GPUs, but also a software platform, Cuda, used for AI model development and training. Nvidia is also expanding its data center networking solutions, helping to tie GPUs together to handle complex workloads.