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ACM Research (ACM Research) Debt-to-EBITDA : 0.72 (As of Dec. 2023)


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What is ACM Research Debt-to-EBITDA?

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

ACM Research's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $40.9 Mil. ACM Research's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $58.2 Mil. ACM Research's annualized EBITDA for the quarter that ended in Dec. 2023 was $136.8 Mil. ACM Research's annualized Debt-to-EBITDA for the quarter that ended in Dec. 2023 was 0.72.

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 ACM Research's Debt-to-EBITDA or its related term are showing as below:

ACMR' s Debt-to-EBITDA Range Over the Past 10 Years
Min: 0.78   Med: 1.14   Max: 22.85
Current: 0.78

During the past 9 years, the highest Debt-to-EBITDA Ratio of ACM Research was 22.85. The lowest was 0.78. And the median was 1.14.

ACMR's Debt-to-EBITDA is ranked better than
63.79% of 707 companies
in the Semiconductors industry
Industry Median: 1.61 vs ACMR: 0.78

ACM Research Debt-to-EBITDA Historical Data

The historical data trend for ACM Research'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.

ACM Research Debt-to-EBITDA Chart

ACM Research Annual Data
Trend Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Debt-to-EBITDA
Get a 7-Day Free Trial Premium Member Only 0.86 2.35 0.85 1.07 0.78

ACM Research 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 1.06 1.49 0.46 0.64 0.72

Competitive Comparison of ACM Research's Debt-to-EBITDA

For the Semiconductor Equipment & Materials subindustry, ACM Research'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.


ACM Research's Debt-to-EBITDA Distribution in the Semiconductors Industry

For the Semiconductors industry and Technology sector, ACM Research's Debt-to-EBITDA distribution charts can be found below:

* The bar in red indicates where ACM Research's Debt-to-EBITDA falls into.



ACM Research Debt-to-EBITDA Calculation

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

ACM Research'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
=(40.882 + 58.214) / 126.989
=0.78

ACM Research'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
=(40.882 + 58.214) / 136.78
=0.72

* 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.


ACM Research  (NAS:ACMR) 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.


ACM Research Debt-to-EBITDA Related Terms

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


ACM Research (ACM Research) Business Description

Traded in Other Exchanges
Address
42307 Osgood Road, Suite I, Fremont, CA, USA, 94539
ACM Research Inc is an us-based company. It is engaged in developing, manufacturing, and selling single-wafer wet cleaning equipment, which is used by semiconductor manufacturers in numerous manufacturing steps to remove particles, contaminants, and other random defects to improve product yield, in fabricating integrated circuits, or chips. The company offers space alternated phase shift which employs alternating phases of megasonic waves to deliver megasonic energy to flat and patterned wafer surfaces on a microscopic level; and Timely Energized Bubble Oscillation technology which provides effective, damage-free cleaning for both conventional two and three-dimensional patterned wafers at process nodes.
Executives
Mark Mckechnie officer: See remarks ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Lisa Feng officer: See remarks ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Tracy Liu director C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
David H Wang director, 10 percent owner, officer: See Remarks C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Haiping Dun director C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Fuping Chen officer: See Remarks ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Sotheara Cheav officer: See Remarks C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Shanghai Pudong Science & Technology Investment Group Co., Ltd. 10 percent owner, other: Possible member of 10% group FLOOR 16-17, #118 RONGKE ROAD, PUDONG DISTRICT, SHANGHAI F4 200120
Shanghai Science & Technology Venture Capital (group) Co., Ltd. 10 percent owner, other: Possible member of 10% group FLOOR 16-17, #118 RONGKE ROAD, PUDONG DISTRICT, SHANGHAI F4 201203
Xiao Xing director C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREEMONT CA 94539
Yinan Xiang director C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Chenming Hu director 2060 PEBBLE DRIVE, ALAMO CA 94507
Jian Wang officer: See Remarks C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539
Zhengfan Yang director XINXIN (HONGKONG) CAPITAL CO., LIMITED, 3RD FLOOR NORTH, NO. 7 FINANCIAL STREET, XICHENG DISTRICT, BEIJING F4 100033
Fufa Chen officer: See Remarks C/O ACM RESEARCH, INC., 42307 OSGOOD ROAD, SUITE I, FREMONT CA 94539