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Axilion Smart Mobility (XTAE:AILN) ROCE % : -68.37% (As of Dec. 2023)


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What is Axilion Smart Mobility ROCE %?

ROCE % measures how well a company generates profits from its capital. It is calculated as EBIT divided by Capital Employed, where Capital Employed is calculated as Total Assets minus Total Current Liabilities. Axilion Smart Mobility's annualized ROCE % for the quarter that ended in Dec. 2023 was -68.37%.


Axilion Smart Mobility ROCE % Historical Data

The historical data trend for Axilion Smart Mobility's ROCE % 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.

Axilion Smart Mobility ROCE % Chart

Axilion Smart Mobility Annual Data
Trend Dec14 Dec15 Dec16 Dec17 Dec18 Dec19 Dec20 Dec21 Dec22 Dec23
ROCE %
Get a 7-Day Free Trial Premium Member Only Premium Member Only -17.43 -1,014.96 -53.25 -35.64 -56.09

Axilion Smart Mobility Semi-Annual Data
Dec14 Dec15 Jun16 Dec16 Jun17 Dec17 Jun18 Dec18 Jun19 Dec19 Jun20 Dec20 Jun21 Dec21 Jun22 Dec22 Jun23 Dec23
ROCE % 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 -34.27 -28.71 -43.48 -45.98 -68.37

Axilion Smart Mobility ROCE % Calculation

Axilion Smart Mobility's annualized ROCE % for the fiscal year that ended in Dec. 2023 is calculated as:

ROCE %=EBIT/( (Capital Employed+Capital Employed)/ count )
(A: Dec. 2023 )  (A: Dec. 2022 )(A: Dec. 2023 )
=EBIT/( ( (Total Assets - Total Current Liabilities)+(Total Assets - Total Current Liabilities) )/ count )
(A: Dec. 2023 )  (A: Dec. 2022 )(A: Dec. 2023 )
=-23.964/( ( (56.916 - 3.128) + (35.249 - 3.596) )/ 2 )
=-23.964/( (53.788+31.653)/ 2 )
=-23.964/42.7205
=-56.09 %

Axilion Smart Mobility's ROCE % of for the quarter that ended in Dec. 2023 is calculated as:

ROCE %=EBIT (1)/( (Capital Employed+Capital Employed)/ count )
(Q: Dec. 2023 )  (Q: Jun. 2023 )(Q: Dec. 2023 )
=EBIT/( ( (Total Assets - Total Current Liabilities)+(Total Assets - Total Current Liabilities) )/ count )
(Q: Dec. 2023 )  (Q: Jun. 2023 )(Q: Dec. 2023 )
=-25.614/( ( (46.438 - 3.164) + (35.249 - 3.596) )/ 2 )
=-25.614/( ( 43.274 + 31.653 )/ 2 )
=-25.614/37.4635
=-68.37 %

(1) Note: The EBIT data used here is two times the semi-annual (Dec. 2023) EBIT data.

* 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.


Axilion Smart Mobility  (XTAE:AILN) ROCE % Explanation

ROCE % can be especially useful when comparing the performance of capital-intensive companies. Unlike ROE %, which indicates the profitability of Shareholders Equity, ROCE % also considers long-term debt in Capital Employed. This can be helpful when analyzing companies with significant debt, as the result is neutralized by taking debt into consideration.

Generally speaking, a higher ROCE % indicates a stonger profitability for a company. Moreover, it is important to look at the ratio from a long term perspective. Investors tend to favor companies with stable and rising ROCE % trend over those with volatile ones.


Axilion Smart Mobility ROCE % Related Terms

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Axilion Smart Mobility (XTAE:AILN) Business Description

Traded in Other Exchanges
N/A
Address
Tel Aviv, Tel Aviv, ISR
Axilion Smart Mobility Ltd is an artificial intelligence-based software company. The company is focused on developing, applying, and implementing software systems (SaaS) based on artificial intelligence, which enables cities to manage their entire mobility system optimally. Its solutions optimize traffic light systems' timing using a comprehensive analysis of the traffic light network, road users, and network demand. These solutions help in reducing air pollution, prioritize public transit, and improve road-user safety.

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