BI Matrix Co (XKRX:413640) EPS (Basic) : ₩511.00 (TTM As of Dec. 2024)

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What is BI Matrix Co EPS (Basic)?

BI Matrix Co's basic earnings per share (Basic EPS) for the three months ended in Dec. 2024 was ₩318.00. Its basic earnings per share (Basic EPS) for the trailing twelve months (TTM) ended in Dec. 2024 was ₩511.00.

BI Matrix Co's EPS (Diluted) for the three months ended in Dec. 2024 was ₩318.00. Its EPS (Diluted) for the trailing twelve months (TTM) ended in Dec. 2024 was ₩511.00.

BI Matrix Co's EPS without NRI for the three months ended in Dec. 2024 was ₩318.00. Its EPS without NRIearnings per share without non-recurring items for the trailing twelve months (TTM) ended in Dec. 2024 was 511.00.

During the past 3 years, the average EPS without NRI Growth Rate was -53.30% per year. Please click Growth Rate Calculation Example (GuruFocus) to see how GuruFocus calculates Wal-Mart Stores Inc (WMT)'s revenue growth rate. You can apply the same method to get the EPS without NRI Growth Rate using EPS without NRI data.

During the past 5 years, BI Matrix Co's highest 3-Year average EPS without NRI Growth Rate was -53.30% per year. The lowest was -53.30% per year. And the median was -53.30% per year.

BI Matrix Co EPS (Basic) Historical Data

The historical data trend for BI Matrix Co's EPS (Basic) 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.

BI Matrix Co EPS (Basic) Chart

BI Matrix Co Annual Data

Trend

Dec20

Dec21

Dec22

Dec23

Dec24

EPS (Basic)

2,709.00

4,825.00

618.00

-292.00

511.00

BI Matrix Co Quarterly Data
	Jun22	Dec22	Mar23	Jun23	Sep23	Dec23	Mar24	Jun24	Sep24	Dec24
EPS (Basic)	Get a 7-Day Free Trial					-148.00	-215.00	197.00	211.00	318.00

BI Matrix Co EPS (Basic) Calculation

EPS (Basic) is a rough measurement of the amount of a company's profit that can be allocated to one share of its stock. Basic earnings per share (EPS) do not factor in the dilutive effects on convertible securities.

BI Matrix Co's Basic EPS for the fiscal year that ended in Dec. 2024 is calculated as

Basic EPS (A: Dec. 2024 )	=	(Net Income	-	Preferred Dividends)	/	Shares Outstanding (Basic Average)
	=	(3683.027	-	0)	/	7.207
	=	511.03

BI Matrix Co's Basic EPS for the quarter that ended in Dec. 2024 is calculated as

Basic EPS (Q: Dec. 2024 )	=	(Net Income	-	Preferred Dividends)	/	Shares Outstanding (Basic Average)
	=	(2291.704	-	0)	/	7.203
	=	318.16

EPS (Basic) for the trailing twelve months (TTM) ended in Dec. 2024 adds up the quarterly data reported by the company within the most recent 12 months, which was ₩511.00

BI Matrix Co (XKRX:413640) EPS (Basic) Explanation

EPS is the single most important variable used by Wall Street in determining the earnings power of a company. But investors need to be aware that Earnings per Share can be easily manipulated by adjusting depreciation and amortization rate or non-recurring items. That's why GuruFocus lists EPS without NRI, which better reflects the company's underlying performance.

Be Aware

Compared with Earnings per share, a company's cash flow is better indicator of the company's earnings power.

If a company's earnings per share is less than cash flow per share over long term, investors need to be cautious and find out why.

BI Matrix Co EPS (Basic) Related Terms

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BI Matrix Co Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Technology » Software » BI Matrix Co Ltd (XKRX:413640) » Definitions » EPS (Basic)

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Traded in Other Exchanges

N/A

Address

433 Seolleung-ro, 17th floor, Sebang New Building, Gangnam-gu, Seoul, KOR, 06212

Website

https://www.bimatrix.co.kr

BI Matrix Co Ltd is ??an intelligence solution specialist with core technologies in the areas of Artificial Intelligence, Business Intelligence and Collaboration Intelligence, Big Data, Data Mining, and SW Robotics.

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