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One Stop Systems (One Stop Systems) Debt-to-EBITDA : 18.25 (As of Dec. 2023)


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What is One Stop Systems Debt-to-EBITDA?

Debt-to-EBITDA measures a company's ability to pay off its debt.

One Stop Systems's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $2.47 Mil. One Stop Systems's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $1.77 Mil. One Stop Systems's annualized EBITDA for the quarter that ended in Dec. 2023 was $0.23 Mil. One Stop Systems's annualized Debt-to-EBITDA for the quarter that ended in Dec. 2023 was 18.25.

A high Debt-to-EBITDA ratio generally means that a company may spend more time to paying off its debt. According to Joel Tillinghast's BIG MONEY THINKS SMALL: Biases, Blind Spots, and Smarter Investing, a ratio of Debt-to-EBITDA exceeding four is usually considered scary unless tangible assets cover the debt.

The historical rank and industry rank for One Stop Systems's Debt-to-EBITDA or its related term are showing as below:

OSS' s Debt-to-EBITDA Range Over the Past 10 Years
Min: -1.19   Med: 1.98   Max: 19.33
Current: -0.92

During the past 9 years, the highest Debt-to-EBITDA Ratio of One Stop Systems was 19.33. The lowest was -1.19. And the median was 1.98.

OSS's Debt-to-EBITDA is ranked worse than
100% of 1733 companies
in the Hardware industry
Industry Median: 1.75 vs OSS: -0.92

One Stop Systems Debt-to-EBITDA Historical Data

The historical data trend for One Stop Systems's Debt-to-EBITDA 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.

One Stop Systems Debt-to-EBITDA Chart

One Stop Systems Annual Data
Trend Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Debt-to-EBITDA
Get a 7-Day Free Trial Premium Member Only 1.98 3.48 0.75 1.26 -0.92

One Stop Systems Quarterly Data
Mar19 Jun19 Sep19 Dec19 Mar20 Jun20 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23
Debt-to-EBITDA 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 0.92 6.03 -0.55 -0.35 18.25

Competitive Comparison of One Stop Systems's Debt-to-EBITDA

For the Computer Hardware subindustry, One Stop Systems's Debt-to-EBITDA, along with its competitors' market caps and Debt-to-EBITDA 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.


One Stop Systems's Debt-to-EBITDA Distribution in the Hardware Industry

For the Hardware industry and Technology sector, One Stop Systems's Debt-to-EBITDA distribution charts can be found below:

* The bar in red indicates where One Stop Systems's Debt-to-EBITDA falls into.



One Stop Systems Debt-to-EBITDA Calculation

Debt-to-EBITDA measures a company's ability to pay off its debt.

One Stop Systems's Debt-to-EBITDA for the fiscal year that ended in Dec. 2023 is calculated as

Debt-to-EBITDA=Total Debt / EBITDA
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / EBITDA
=(2.469 + 1.766) / -4.594
=-0.92

One Stop Systems's annualized Debt-to-EBITDA for the quarter that ended in Dec. 2023 is calculated as

Debt-to-EBITDA=Total Debt / EBITDA
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / EBITDA
=(2.469 + 1.766) / 0.232
=18.25

* 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.

In the calculation of annual Debt-to-EBITDA, the EBITDA of the last fiscal year is used. In calculating the annualized quarterly data, the EBITDA data used here is four times the quarterly (Dec. 2023) EBITDA data.


One Stop Systems  (NAS:OSS) Debt-to-EBITDA Explanation

In the calculation of Debt-to-EBITDA, we use the total of Short-Term Debt & Capital Lease Obligation and Long-Term Debt & Capital Lease Obligation divided by EBITDA. In some calculations, Total Liabilities is used to for calculation.


Be Aware

A high Debt-to-EBITDA ratio generally means that a company may spend more time to paying off its debt.

According to Joel Tillinghast's BIG MONEY THINKS SMALL: Biases, Blind Spots, and Smarter Investing, a ratio of Debt-to-EBITDA exceeding four is usually considered scary unless tangible assets cover the debt.


One Stop Systems Debt-to-EBITDA Related Terms

Thank you for viewing the detailed overview of One Stop Systems's Debt-to-EBITDA provided by GuruFocus.com. Please click on the following links to see related term pages.


One Stop Systems (One Stop Systems) Business Description

Traded in Other Exchanges
Address
2235 Enterprise Street, Suite 110, Escondido, CA, USA, 92029
One Stop Systems Inc designs and manufactures innovative Artificial intelligence (AI) Transportable edge computing modules and systems, including ruggedized servers, compute accelerators, expansion systems, flash storage arrays and Ion Accelerator SAN, NAS and data recording software for AI workflows. These products are used for AI data set capture, training, and large-scale inference in the defense, oil and gas, mining, autonomous vehicles and rugged entertainment applications. The company enables AI on the Fly by bringing AI datacenter performance to the edge, especially on mobile platforms, and by addressing the entire AI workflow, from high-speed data acquisition to deep learning, training and inference. Its products are available directly or through global distributors.
Executives
Steve D Cooper director, 10 percent owner, officer: President, CEO 2235 ENTERPRISE ST STE 110, ESCONDIDO CA 92029
Michael J. Dumont director 2235 ENTERPRISE STREET #110, ESCONDIDO CA 92029
Michael Knowles officer: Chief Executive Officer 9333 BALBOA AVENUE, SAN DIEGO CA 92123
Gregory W Matz director 1 WHITE OAK WAY, NOVATO CA 94949
David Raun director 870 MAUDE AVENUE, SUNNVALE CA 94085
James M Reardon officer: President, CDI 2235 ENTERPRISE ST STE 110, ESCONDIDO CA 92029
Teresita M. Lowman director 2235 ENTERPRISE STREET #110, ESCONDIDO CA 92029
Kenneth F Potashner director C/O MAXWELL TECHNOLOGIES INC, 9244 BALBOA AVE, SAN DIEGO CA 92123
Gioia Messinger director VICON INDUSTRIES, INC., 135 FELL COURT, HAUPPAUGE NY 11788
Jack Harrison director 2235 ENTERPRISE STREET STE 110, ESCONDIDO CA 92029
John Ralph Reardon director 2114 OPAL RIDGE, VISTA CA 92081
Barbara D'amato director 6445 SOUTH TENAYA WAY, B-130, LAS VEGAS NV 89113
Jim Ison officer: Vice President of Sales 2235 ENTERPRISE STREET STE 110, ESCONDIDO CA 92029
Kimberly C. Sentovich director 2235 ENTERPRISE ST SUITE 110, ESCONDIDO CA 92029
Josef Bressner officer: Managing Director, Bressner 2235 ENTERPRISE ST SUITE 110, ESCONDIDO CA 92029