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Powermatic Data Systems (SGX:BCY) Debt-to-EBITDA : 0.02 (As of Sep. 2023)


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What is Powermatic Data Systems Debt-to-EBITDA?

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

Powermatic Data Systems's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Sep. 2023 was S$0.12 Mil. Powermatic Data Systems's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Sep. 2023 was S$0.18 Mil. Powermatic Data Systems's annualized EBITDA for the quarter that ended in Sep. 2023 was S$14.63 Mil. Powermatic Data Systems's annualized Debt-to-EBITDA for the quarter that ended in Sep. 2023 was 0.02.

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 Powermatic Data Systems's Debt-to-EBITDA or its related term are showing as below:

SGX:BCY' s Debt-to-EBITDA Range Over the Past 10 Years
Min: 0.01   Med: 0.02   Max: 0.03
Current: 0.02

During the past 13 years, the highest Debt-to-EBITDA Ratio of Powermatic Data Systems was 0.03. The lowest was 0.01. And the median was 0.02.

SGX:BCY's Debt-to-EBITDA is ranked better than
98.45% of 1738 companies
in the Hardware industry
Industry Median: 1.8 vs SGX:BCY: 0.02

Powermatic Data Systems Debt-to-EBITDA Historical Data

The historical data trend for Powermatic Data 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.

Powermatic Data Systems Debt-to-EBITDA Chart

Powermatic Data Systems Annual Data
Trend Mar14 Mar15 Mar16 Mar17 Mar18 Mar19 Mar20 Mar21 Mar22 Mar23
Debt-to-EBITDA
Get a 7-Day Free Trial Premium Member Only Premium Member Only - 0.03 0.01 0.01 0.03

Powermatic Data Systems Semi-Annual Data
Mar14 Sep14 Mar15 Sep15 Mar16 Sep16 Mar17 Sep17 Mar18 Sep18 Mar19 Sep19 Mar20 Sep20 Mar21 Sep21 Mar22 Sep22 Mar23 Sep23
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 - 0.02 - 0.03 0.02

Competitive Comparison of Powermatic Data Systems's Debt-to-EBITDA

For the Communication Equipment subindustry, Powermatic Data 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.


Powermatic Data Systems's Debt-to-EBITDA Distribution in the Hardware Industry

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

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



Powermatic Data Systems Debt-to-EBITDA Calculation

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

Powermatic Data Systems's Debt-to-EBITDA for the fiscal year that ended in Mar. 2023 is calculated as

Debt-to-EBITDA=Total Debt / EBITDA
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / EBITDA
=(0.239 + 0.181) / 12.483
=0.03

Powermatic Data Systems's annualized Debt-to-EBITDA for the quarter that ended in Sep. 2023 is calculated as

Debt-to-EBITDA=Total Debt / EBITDA
=(Short-Term Debt & Capital Lease Obligation + Long-Term Debt & Capital Lease Obligation) / EBITDA
=(0.116 + 0.181) / 14.634
=0.02

* 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 two times the quarterly (Sep. 2023) EBITDA data.


Powermatic Data Systems  (SGX:BCY) 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.


Powermatic Data Systems Debt-to-EBITDA Related Terms

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


Powermatic Data Systems (SGX:BCY) Business Description

Traded in Other Exchanges
N/A
Address
No. 9 Harrison Road, No. 05-01, Harrison Industrial Building, Singapore, SGP, 369651
Powermatic Data Systems Ltd operates in the communication equipment business. The company's operating segment includes Wireless connectivity products; Property and Corporate holding and others. It generates maximum revenue from the Wireless connectivity products segment. The Wireless connectivity products segment comprises the manufacturing, sales, marketing, and distribution of wireless connectivity products. Geographically, it derives a majority of revenue from Europe.

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