RELX (RELX) Debt-to-Asset : 0.44 (As of Dec. 2023)

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What is RELX Debt-to-Asset?

RELX's Short-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $1,662 Mil. RELX's Long-Term Debt & Capital Lease Obligation for the quarter that ended in Dec. 2023 was $6,562 Mil. RELX's Long-Term Debt & Capital Lease ObligationTotal Assets for the quarter that ended in Dec. 2023 was $18,882 Mil. RELX's debt to asset for the quarter that ended in Dec. 2023 was 0.44.

RELX Debt-to-Asset Historical Data

The historical data trend for RELX's Debt-to-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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RELX Debt-to-Asset Chart

RELX Annual Data

Trend

Dec14

Dec15

Dec16

Dec17

Dec18

Dec19

Dec20

Dec21

Dec22

Dec23

Debt-to-Asset

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0.47

0.50

0.45

0.43

0.44

RELX Semi-Annual Data
	Jun14	Dec14	Jun15	Dec15	Jun16	Dec16	Jun17	Dec17	Jun18	Dec18	Jun19	Dec19	Jun20	Dec20	Jun21	Dec21	Jun22	Dec22	Jun23	Dec23
Debt-to-Asset	Get a 7-Day Free Trial															0.45	0.45	0.43	0.46	0.44

Competitive Comparison of RELX's Debt-to-Asset

For the Specialty Business Services subindustry, RELX's Debt-to-Asset, along with its competitors' market caps and Debt-to-Asset data, can be viewed below:

* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.

RELX's Debt-to-Asset Distribution in the Business Services Industry

For the Business Services industry and Industrials sector, RELX's Debt-to-Asset distribution charts can be found below:

* The bar in red indicates where RELX's Debt-to-Asset falls into.

RELX Debt-to-Asset Calculation

Debt to Asset measures the financial leverage a company has.

RELX's Debt-to-Asset for the fiscal year that ended in Dec. 2023 is calculated as

Debt-to-Asset	=	Total Debt			/	Total Assets
	=	(Short-Term Debt & Capital Lease Obligation	+	Long-Term Debt & Capital Lease Obligation)	/	Total Assets
	=	(1662.025	+	6562.025)	/	18882.278
	=	0.44

RELX's Debt-to-Asset for the quarter that ended in Dec. 2023 is calculated as

Debt-to-Asset	=	Total Debt			/	Total Assets
	=	(Short-Term Debt & Capital Lease Obligation	+	Long-Term Debt & Capital Lease Obligation)	/	Total Assets
	=	(1662.025	+	6562.025)	/	18882.278
	=	0.44

RELX (NYSE:RELX) Debt-to-Asset Explanation

In the calculation of Debt-to-Asset, we use the total of Short-Term Debt & Capital Lease Obligation and Long-Term Debt & Capital Lease Obligation divided by Total Assets.

RELX Debt-to-Asset Related Terms

Thank you for viewing the detailed overview of RELX's Debt-to-Asset provided by GuruFocus.com. Please click on the following links to see related term pages.

RELX (RELX) Business Description

Industry

GURUFOCUS.COM » STOCK LIST » Industrials » Business Services » RELX PLC (NYSE:RELX) » Definitions » Debt-to-Asset

Comparable Companies

Traded in Other Exchanges

RLXXF:USA REN:Netherlands REL:Mexico RELl:UK REL:UK RDEB:Germany R1EL34:Brazil

Address

1-3 Strand, London, GBR, WC2N 5JR

Website

https://www.relx.com

RELX PLC is a diversified information and analytics company. The firm operates across four main areas: scientific, technical, and medical; risk; legal; and exhibitions. It generates maximum revenue from the Scientific, Technical and Medical and Risk segment. Scientific, Technical and Medical segment provides information and analytics that help institutions and professionals progress science, advance healthcare and improve performance. Risk segment provides customers with information-based analytics and decision tools that combine public and industry-specific content with advanced technology and algorithms to assist them in evaluating and predicting risk and enhancing operational efficiency.