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Leonardo DRS (STU:2VZ) LT-Debt-to-Total-Asset : 0.10 (As of Dec. 2024)


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What is Leonardo DRS 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. Leonardo DRS's long-term debt to total assests ratio for the quarter that ended in Dec. 2024 was 0.10.

Leonardo DRS's long-term debt to total assets ratio declined from Dec. 2023 (0.11) to Dec. 2024 (0.10). It may suggest that Leonardo DRS is progressively becoming less dependent on debt to grow their business.


Leonardo DRS LT-Debt-to-Total-Asset Historical Data

The historical data trend for Leonardo DRS'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.

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Leonardo DRS LT-Debt-to-Total-Asset Chart

Leonardo DRS Annual Data
Trend Dec18 Dec19 Dec20 Dec21 Dec22 Dec23 Dec24
LT-Debt-to-Total-Asset
Get a 7-Day Free Trial 0.15 0.14 0.12 0.11 0.10

Leonardo DRS Quarterly Data
Mar20 Jun20 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23 Mar24 Jun24 Sep24 Dec24
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 0.11 0.11 0.11 0.11 0.10

Leonardo DRS LT-Debt-to-Total-Asset Calculation

Leonardo DRS's Long-Term Debt to Total Asset Ratio for the fiscal year that ended in Dec. 2024 is calculated as

LT Debt to Total Assets (A: Dec. 2024 )=Long-Term Debt & Capital Lease Obligation (A: Dec. 2024 )/Total Assets (A: Dec. 2024 )
=387.73/3995.72
=0.10

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

LT Debt to Total Assets (Q: Dec. 2024 )=Long-Term Debt & Capital Lease Obligation (Q: Dec. 2024 )/Total Assets (Q: Dec. 2024 )
=387.73/3995.72
=0.10

* 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.


Leonardo DRS  (STU:2VZ) 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.


Leonardo DRS LT-Debt-to-Total-Asset Related Terms

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Leonardo DRS Business Description

Traded in Other Exchanges
Address
2345 Crystal Drive, Suite 1000, Arlington, VA, USA, 22202
Leonardo DRS Inc is a provider of defense products and technologies that are used across land, air, sea, space, and cyber domains. The company is in the design, development, and manufacture of Advanced sensing, network computing, force protection, and electric power and propulsion technologies and solutions. The company has two segments: Advanced Sensing and Computing, which generates the majority of revenue, and the Integrated Mission Systems segment. The Advanced Sensing and Computing segment is engaged in designing, developing, and manufacturing sensing and network computing technology that enables real-time situational awareness required for enhanced operational decision-making and execution by the customers.

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