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POET Technologies (POET Technologies) Debt-to-EBITDA : -0.03 (As of Dec. 2023)


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What is POET Technologies Debt-to-EBITDA?

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

POET Technologies's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $0.24 Mil. POET Technologies's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $0.31 Mil. POET Technologies's annualized EBITDA for the quarter that ended in Dec. 2023 was $-19.81 Mil. POET Technologies's annualized Debt-to-EBITDA for the quarter that ended in Dec. 2023 was -0.03.

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 POET Technologies's Debt-to-EBITDA or its related term are showing as below:

POET' s Debt-to-EBITDA Range Over the Past 10 Years
Min: -0.31   Med: -0.03   Max: -0.02
Current: -0.03

During the past 13 years, the highest Debt-to-EBITDA Ratio of POET Technologies was -0.02. The lowest was -0.31. And the median was -0.03.

POET's Debt-to-EBITDA is ranked worse than
100% of 706 companies
in the Semiconductors industry
Industry Median: 1.595 vs POET: -0.03

POET Technologies Debt-to-EBITDA Historical Data

The historical data trend for POET Technologies'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.

POET Technologies Debt-to-EBITDA Chart

POET Technologies Annual Data
Trend Dec14 Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
Debt-to-EBITDA
Get a 7-Day Free Trial Premium Member Only Premium Member Only -0.31 -0.25 -0.03 -0.02 -0.03

POET Technologies 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 -0.01 -0.01 -0.03 -0.02 -0.03

Competitive Comparison of POET Technologies's Debt-to-EBITDA

For the Semiconductors subindustry, POET Technologies'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.


POET Technologies's Debt-to-EBITDA Distribution in the Semiconductors Industry

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

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



POET Technologies Debt-to-EBITDA Calculation

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

POET Technologies'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
=(0.235 + 0.307) / -18.275
=-0.03

POET Technologies'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
=(0.235 + 0.307) / -19.808
=-0.03

* 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.


POET Technologies  (NAS:POET) 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.


POET Technologies Debt-to-EBITDA Related Terms

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


POET Technologies (POET Technologies) Business Description

Traded in Other Exchanges
Address
120 Eglinton Avenue East, Suite 1107, Toronto, ON, CAN, M4P 1E2
POET Technologies Inc offers integration solutions based on the POET Optical Interposer, a novel platform for the seamless integration of electronic and photonic devices into a single module using advanced wafer-level manufacturing techniques and packaging methods. The company operates in a single segment of design, manufacture, and sale of semiconductor products and services for commercial applications. Its products have applications in Data Centers, Telecommunications, the Internet of Things & Industrial Sensing, Automotive LIDAR, and On-Board Optics. Its geographical segments are Asia, the United States, and Canada.