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Artiza Networks (TSE:6778) LT-Debt-to-Total-Asset : 0.03 (As of Jan. 2025)


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What is Artiza Networks 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. Artiza Networks's long-term debt to total assests ratio for the quarter that ended in Jan. 2025 was 0.03.

Artiza Networks's long-term debt to total assets ratio declined from Oct. 2023 (0.05) to Jan. 2025 (0.03). It may suggest that Artiza Networks is progressively becoming less dependent on debt to grow their business.


Artiza Networks LT-Debt-to-Total-Asset Historical Data

The historical data trend for Artiza Networks'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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Artiza Networks LT-Debt-to-Total-Asset Chart

Artiza Networks Annual Data
Trend Jul15 Jul16 Jul17 Jul18 Jul19 Jul20 Jul21 Jul22 Jul23 Jul24
LT-Debt-to-Total-Asset
Get a 7-Day Free Trial Premium Member Only Premium Member Only 0.05 0.05 0.04 0.05 0.03

Artiza Networks Quarterly Data
Jan20 Apr20 Jul20 Oct20 Jan21 Apr21 Jul21 Oct21 Jan22 Apr22 Jul22 Oct22 Jan23 Apr23 Jul23 Oct23 Jan24 Apr24 Jul24 Jan25
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 0.05 0.04 0.04 0.03 0.03

Artiza Networks LT-Debt-to-Total-Asset Calculation

Artiza Networks's Long-Term Debt to Total Asset Ratio for the fiscal year that ended in Jul. 2024 is calculated as

LT Debt to Total Assets (A: Jul. 2024 )=Long-Term Debt & Capital Lease Obligation (A: Jul. 2024 )/Total Assets (A: Jul. 2024 )
=294.118/8924.798
=0.03

Artiza Networks's Long-Term Debt to Total Asset Ratio for the quarter that ended in Jan. 2025 is calculated as

LT Debt to Total Assets (Q: Jan. 2025 )=Long-Term Debt & Capital Lease Obligation (Q: Jan. 2025 )/Total Assets (Q: Jan. 2025 )
=219.6/8529.647
=

* 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.


Artiza Networks  (TSE:6778) 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.


Artiza Networks LT-Debt-to-Total-Asset Related Terms

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Artiza Networks Business Description

Traded in Other Exchanges
N/A
Address
2-36-2, Akebono-cho, Tachikawa-shi, Tokyo, JPN, 190-0012
Artiza Networks Inc is engaged in the development and sale of network management systems for maintenance and operation management of communication measuring instruments and communication infrastructure. It is also engaged in the development and sale of various communication equipments. The company offers LTE eNodeB testing products, such as Duo SIM- advanced load testers, functional testers, and environmental simulators; hardware blades; QoE optimization and packet capture tools.

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