Richard Sloan from the University of Michigan was first to document what is referred to as the "accrual anomaly". His 1996 paper found that shares of companies with small or negative accruals vastly outperform (+10%) those of companies with large ones.
NVIDIA's Sloan Ratio for the quarter that ended in Jan. 2024 was 18.61%.
As of Jan. 2024, NVIDIA has a Sloan Ratio of 18.61%, indicating there is a warning stage of accrual build up.
NVIDIA Sloan Ratio % Historical Data
The historical data trend for NVIDIA's Sloan Ratio % 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.
For the Semiconductors subindustry, NVIDIA's Sloan Ratio %, along with its competitors' market caps and Sloan Ratio % 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.
NVIDIA Sloan Ratio % Distribution
For the Semiconductors industry and Technology sector, NVIDIA's Sloan Ratio % distribution charts can be found below:
* The bar in red indicates where NVIDIA's Sloan Ratio % falls into.
NVIDIA Sloan Ratio % Calculation
Earnings contain a lot of non cash earnings which is called accruals. The Sloan ratio is a way to identify firms with low non-cash or accrual-derived earnings relative to their cash flow.
NVIDIA's Sloan Ratio for the fiscal year that ended in Jan. 2024 is calculated as
NVIDIA's Net Income for the trailing twelve months (TTM) ended in Jan. 2024 was 2043 (Apr. 2023 ) + 6188 (Jul. 2023 ) + 9243 (Oct. 2023 ) + 12285 (Jan. 2024 ) = $29,759 Mil.
NVIDIA's Cash Flow from Operations for the trailing twelve months (TTM) ended in Jan. 2024 was 2911 (Apr. 2023 ) + 6348 (Jul. 2023 ) + 7332 (Oct. 2023 ) + 11499 (Jan. 2024 ) = $28,090 Mil.
NVIDIA's Cash Flow from Investing for the trailing twelve months (TTM) ended in Jan. 2024 was -841 (Apr. 2023 ) + -446 (Jul. 2023 ) + -3170 (Oct. 2023 ) + -6109 (Jan. 2024 ) = $-10,566 Mil.
* 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.
NVIDIA (NAS:NVDA) Sloan Ratio % Explanation
A former University of Michigan researcher, Richard Sloan's 1996 paper found that shares of companies with small or negative accruals vastly outperform (+10%) those of companies with large ones. In fact, for the 40-year period between 1962 and 2001, buying the lowest accrual companies and shorting the highest accrual companies resulted in an average annual compounded return of 18%, more than double the S&P 500's 7.4% annual return over the same period.
If the Sloan Ratio is between -10% and 10%, the company is in the safe zone and there is no funny business with accruals.
If the Sloan Ratio is less than between -25% and -10% on the negative side, and between 10% and 25% on the positive side, this is a warning stage of accrual build up.
If the Sloan Ratio is less than -25% or greater than 25%, and this ratio is consistent over several quarters or even years, be careful. Earnings are highly likely to be made up of accruals.
As of Jan. 2024, NVIDIA has a Sloan Ratio of 18.61%, indicating there is a warning stage of accrual build up.
NVIDIA Sloan Ratio % Related Terms
Thank you for viewing the detailed overview of NVIDIA's Sloan Ratio % provided by GuruFocus.com. Please click on the following links to see related term pages.
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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