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QuickLogic (STU:QKL1) LT-Debt-to-Total-Asset : 0.02 (As of Mar. 2024)


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What is QuickLogic LT-Debt-to-Total-Asset?

LT Debt to Total Assets is a measurement representing the percentage of a corporation's assets that are financed with loans and financial obligations lasting more than one year. The ratio provides a general measure of the financial position of a company, including its ability to meet financial requirements for outstanding loans. It is calculated as a company's Long-Term Debt & Capital Lease Obligationdivide by its Total Assets. QuickLogic's long-term debt to total assests ratio for the quarter that ended in Mar. 2024 was 0.02.

QuickLogic's long-term debt to total assets ratio increased from Mar. 2023 (0.02) to Mar. 2024 (0.02). It may suggest that QuickLogic is progressively becoming more dependent on debt to grow their business.


QuickLogic LT-Debt-to-Total-Asset Historical Data

The historical data trend for QuickLogic's LT-Debt-to-Total-Asset 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.

QuickLogic LT-Debt-to-Total-Asset Chart

QuickLogic Annual Data
Trend Dec14 Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
LT-Debt-to-Total-Asset
Get a 7-Day Free Trial Premium Member Only Premium Member Only 0.05 0.07 0.03 0.02 0.02

QuickLogic Quarterly Data
Jun19 Sep19 Dec19 Mar20 Jun20 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23 Mar24
LT-Debt-to-Total-Asset 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 0.01 0.01 0.02 0.02

QuickLogic LT-Debt-to-Total-Asset Calculation

QuickLogic's Long-Term Debt to Total Asset Ratio for the fiscal year that ended in Dec. 2023 is calculated as

LT Debt to Total Assets (A: Dec. 2023 )=Long-Term Debt & Capital Lease Obligation (A: Dec. 2023 )/Total Assets (A: Dec. 2023 )
=1.047/43.825
=0.02

QuickLogic's Long-Term Debt to Total Asset Ratio for the quarter that ended in Mar. 2024 is calculated as

LT Debt to Total Assets (Q: Mar. 2024 )=Long-Term Debt & Capital Lease Obligation (Q: Mar. 2024 )/Total Assets (Q: Mar. 2024 )
=0.999/47.775
=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.


QuickLogic  (STU:QKL1) LT-Debt-to-Total-Asset Explanation

LT Debt to Total Asset is a measurement representing the percentage of a corporation's assets that are financed with loans and financial obligations lasting more than one year. The ratio provides a general measure of the financial position of a company, including its ability to meet financial requirements for outstanding loans. A year-over-year decrease in this metric would suggest the company is progressively becoming less dependent on debt to grow their business.


QuickLogic LT-Debt-to-Total-Asset Related Terms

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QuickLogic (STU:QKL1) Business Description

Traded in Other Exchanges
Address
2220 Lundy Avenue, San Jose, CA, USA, 95131
QuickLogic Corp is engaged in the development and marketing of semiconductor and software algorithm solutions for mobile and portable electronics. The company's products enable smartphone, wearable and IoT device Original Equipment Manufacturers, or OEMs, to deliver long battery life for their customers. Its solutions fall into one of four categories: Sensor Processing, eFPGA IP and its associated Tools, Display, and Smart Connectivity. Geographically, it has a presence in the Asia Pacific, Europe, and North America. It also works with mobile processor manufacturers, sensor manufacturers, sensor fusion, and context awareness algorithm developers in the development of reference designs.

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