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A high Debt-to-EBITDA ratio generally means that a company may spend more time to paying off its debt. According to Joel Tillinghast's BIG MONEY THINKS SMALL: Biases, Blind Spots, and Smarter Investing, a ratio of Debt-to-EBITDA exceeding four is usually considered scary unless tangible assets cover the debt.
The historical rank and industry rank for Meta Data's Debt-to-EBITDA or its related term are showing as below:
STU:OSM's Debt-to-EBITDA is not ranked *
in the Education industry.
Industry Median: 1.45 * Ranked among companies with meaningful Debt-to-EBITDA only.
A high Debt-to-EBITDA ratio generally means that a company may spend more time to paying off its debt.
According to Joel Tillinghast's BIG MONEY THINKS SMALL: Biases, Blind Spots, and Smarter Investing, a ratio of Debt-to-EBITDA exceeding four is usually considered scary unless tangible assets cover the debt.
Meta Data Debt-to-EBITDA Related Terms
Meta Data Debt-to-EBITDA Historical Data
* Premium members only.
The historical data trend for Meta Data's Debt-to-EBITDA 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.
STU:OSM vs EDU, TAL, LOPE: Debt-to-EBITDA Comparison
For the Education & Training Services subindustry, Meta Data's Debt-to-EBITDA, along with its competitors' market caps and Debt-to-EBITDA 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.
Meta Data Debt-to-EBITDA vs Education Industry
For the Education industry and Consumer Defensive sector, Meta Data's Debt-to-EBITDA distribution charts can be found below:
* The bar in red indicates where Meta Data's Debt-to-EBITDA falls into.
* 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.
In the calculation of annual Debt-to-EBITDA, the EBITDA of the last fiscal year is used. In calculating the annualized quarterly data,
the EBITDA data used here is two times the quarterly (Aug. 2023) EBITDA data.
Meta Data (STU:OSM) has a Debt-to-EBITDA of 3.78 as of Aug. 2023. Debt-to-EBITDA ratio represents the ratio of total debt to total earnings before interest, taxes, depreciation and amortization. View historical data on Meta Data.
Is Meta Data's Debt-to-EBITDA too high?
Meta Data's current Debt-to-EBITDA is 3.78. The Education industry median Debt-to-EBITDA is 1.45. Meta Data's value of 3.78 is 160.7% above this industry median. Overall, Meta Data has a GF Score™ of 10/100, reflecting its overall financial health beyond just this single metric.
How does Meta Data's Debt-to-EBITDA compare to EDU and TAL?
Meta Data's Debt-to-EBITDA of 3.78 can be compared against companies in the Education industry. The industry median Debt-to-EBITDA is 1.45. Meta Data's value of 3.78 is 160.7% above this benchmark. See the competitive comparison table and distribution chart on this page for a detailed peer-by-peer breakdown.
What is a good Debt-to-EBITDA for an Education company?
The median Debt-to-EBITDA among Education companies is 1.45, based on 187 companies in the industry. Companies in the top quartile (top 25%) have a Debt-to-EBITDA significantly above this median, while those in the bottom quartile fall well below. However, Debt-to-EBITDA should not be evaluated in isolation — investors should consider it alongside profitability, growth, and financial strength metrics. Meta Data's current Debt-to-EBITDA of 3.78 is 160.7% above the industry median. Use the industry distribution chart on this page to see where any company falls relative to its peers.
What does a high Debt-to-EBITDA mean?
A high Debt-to-EBITDA can signal that a stock is expensive relative to its fundamentals. Debt-to-EBITDA ratio represents the ratio of total debt to total earnings before interest, taxes, depreciation and amortization. View historical data on Meta Data. For the Education industry, the median Debt-to-EBITDA is 1.45 — values significantly above this may indicate overvaluation, while values below may suggest a bargain or underlying issues. Meta Data's current Debt-to-EBITDA is 3.78. However, context matters — high-growth companies often justify higher valuations. Always evaluate alongside other metrics like GF Score™ and GF Value™.
Is Meta Data stock overvalued right now?
Meta Data (STU:OSM) has a current Debt-to-EBITDA of 3.78. The current Debt-to-EBITDA is 3.78 and 160.7% above the Education industry median of 1.45. Meta Data's overall GF Score™ is 10/100. Investors should evaluate multiple metrics — including profitability, growth, and financial strength — before making a decision.
How is Debt-to-EBITDA calculated?
Debt-to-EBITDA is calculated from a company's financial statements. For Meta Data (STU:OSM), the current Debt-to-EBITDA is 3.78 as of Aug. 2023. GuruFocus calculates this using data sourced from SEC filings and annual reports. See the calculation section and 30-year financial data on this page for the full breakdown.
Meta Data Ltd is engaged in artificial intelligent education service (AIE) and artificial intelligent universe (AIU) IAAS service. AIE is to build an intelligent training system based on intelligent training plat-from to provide the maximum immersive experience and the technical foundation for learning, and implementation in RT3D with 360-degree landscape. AIU IAAS service provides software & hardware infrastructure (IAAS) to Metaverse business operator or individual users. Company classified business segment into Artificial Intelligent Education (AIE) service and Artificial Intelligent Universe (AIU) IAAS service. The company generates all of its revenue in the PRC.
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