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NVIDIA (CHIX:NVDD) Retained Earnings : €49,526 Mil (As of Oct. 2024)


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What is NVIDIA Retained Earnings?

Retained earnings is the accumulated portion of net income that is not distributed to shareholders. NVIDIA's retained earnings for the quarter that ended in Oct. 2024 was €49,526 Mil.

NVIDIA's quarterly retained earnings increased from Apr. 2024 (€34,109 Mil) to Jul. 2024 (€42,376 Mil) and increased from Jul. 2024 (€42,376 Mil) to Oct. 2024 (€49,526 Mil).

NVIDIA's annual retained earnings declined from Jan. 2022 (€14,352 Mil) to Jan. 2023 (€9,439 Mil) but then increased from Jan. 2023 (€9,439 Mil) to Jan. 2024 (€27,372 Mil).


NVIDIA Retained Earnings Historical Data

The historical data trend for NVIDIA's Retained Earnings 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 Retained Earnings Chart

NVIDIA Annual Data
Trend Jan15 Jan16 Jan17 Jan18 Jan19 Jan20 Jan21 Jan22 Jan23 Jan24
Retained Earnings
Get a 7-Day Free Trial Premium Member Only Premium Member Only 13,488.87 15,523.47 14,351.74 9,438.69 27,372.01

NVIDIA Quarterly Data
Jan20 Apr20 Jul20 Oct20 Jan21 Apr21 Jul21 Oct21 Jan22 Apr22 Jul22 Oct22 Jan23 Apr23 Jul23 Oct23 Jan24 Apr24 Jul24 Oct24
Retained Earnings Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only 19,280.92 27,372.01 34,109.34 42,376.04 49,526.10

NVIDIA Retained Earnings Calculation

Retained Earnings is the accumulated portion of net income that is not distributed to shareholders. Because the net income was not distributed to shareholders, shareholders' equity is increased by the same amount.

Of course, if a company loses, it is called retained losses, or accumulated losses.


NVIDIA  (CHIX:NVDd) Retained Earnings Explanation

Historically profitable companies sometimes have negative retained earnings. This is because they have cumulatively paid out more to shareholders than they reported in profits.

For example, in 2011, Microsoft had negative retained earnings. This does not mean the company lost more money than it made over the years. It just means it paid out more money than it earned.

If a company has negative retained earnings, investors should check the 10-year financial results. They should not assume that negative retained earnings prove a company has generally lost money in the past.

Of course, many companies with negative retained earnings have indeed lost money in the past.

Retained Earnings: Warren Buffett's Secret.

One of the most important indicators of durable competitive advantage. Net earnings can be paid out as dividends, used to buy back shares or retained for growth.

If the company loses more than it has accumulated, retained earnings is negative.

If a company isn't adding to its retained earnings, it isn't growing its net worth.

Rate of growth of retained earnings is good indicator whether it's benefiting from a competitive advantage.

Microsoft is negative because it chose to buyback stock and pay dividends.

The more earnings retained, the faster it grows and increases growth rate for future earnings.


NVIDIA Business Description

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

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