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Meta Data (Meta Data) Piotroski F-Score : 7 (As of Apr. 25, 2024)


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What is Meta Data Piotroski F-Score?

Good Sign:

Piotroski F-Score is 7, indicates a very healthy situation.

The zones of discrimination were as such:

Good or high score = 7, 8, 9
Bad or low score = 0, 1, 2, 3

Meta Data has an F-score of 7. It is a good or high score, which usually indicates a very healthy situation.

The historical rank and industry rank for Meta Data's Piotroski F-Score or its related term are showing as below:

AIU' s Piotroski F-Score Range Over the Past 10 Years
Min: 2   Med: 3   Max: 7
Current: 7

During the past 9 years, the highest Piotroski F-Score of Meta Data was 7. The lowest was 2. And the median was 3.


Meta Data Piotroski F-Score Historical Data

The historical data trend for Meta Data's Piotroski F-Score 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.

Meta Data Piotroski F-Score Chart

Meta Data Annual Data
Trend Aug15 Aug16 Aug17 Aug18 Aug19 Aug20 Aug21 Aug22 Aug23
Piotroski F-Score
Get a 7-Day Free Trial Premium Member Only 3.00 3.00 3.00 2.00 7.00

Meta Data Semi-Annual Data
Aug15 Aug16 Feb17 Aug17 Feb18 Aug18 Feb19 Aug19 Feb20 Aug20 Feb21 Aug21 Feb22 Aug22 Feb23 Aug23
Piotroski F-Score 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 3.00 6.00 2.00 5.00 7.00

Competitive Comparison of Meta Data's Piotroski F-Score

For the Education & Training Services subindustry, Meta Data's Piotroski F-Score, along with its competitors' market caps and Piotroski F-Score 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's Piotroski F-Score Distribution in the Education Industry

For the Education industry and Consumer Defensive sector, Meta Data's Piotroski F-Score distribution charts can be found below:

* The bar in red indicates where Meta Data's Piotroski F-Score falls into.


How is the Piotroski F-Score calculated?

* 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.

This Year (Aug23) TTM:Last Year (Aug22) TTM:
Net Income was $694.50 Mil.
Cash Flow from Operations was $13.36 Mil.
Revenue was $32.43 Mil.
Gross Profit was $15.42 Mil.
Average Total Assets from the begining of this year (Aug22)
to the end of this year (Aug23) was (49.58 + 121.144) / 2 = $85.362 Mil.
Total Assets at the begining of this year (Aug22) was $49.58 Mil.
Long-Term Debt & Capital Lease Obligation was $1.21 Mil.
Total Current Assets was $121.12 Mil.
Total Current Liabilities was $115.14 Mil.
Net Income was $-168.90 Mil.

Revenue was $2.12 Mil.
Gross Profit was $0.26 Mil.
Average Total Assets from the begining of last year (Aug21)
to the end of last year (Aug22) was (77.691 + 49.58) / 2 = $63.6355 Mil.
Total Assets at the begining of last year (Aug21) was $77.69 Mil.
Long-Term Debt & Capital Lease Obligation was $35.00 Mil.
Total Current Assets was $49.58 Mil.
Total Current Liabilities was $796.03 Mil.

*Note: If the latest quarterly/semi-annual/annual total assets data is 0, then we will use previous quarterly/semi-annual/annual data for all the items in the balance sheet.

Profitability

Question 1. Return on Assets (ROA)

Net income before extraordinary items for the year divided by Total Assets at the beginning of the year.

Score 1 if positive, 0 if negative.

Meta Data's current Net Income (TTM) was 694.50. ==> Positive ==> Score 1.

Question 2. Cash Flow Return on Assets (CFROA)

Net cash flow from operating activities (operating cash flow) divided by Total Assets at the beginning of the year.

Score 1 if positive, 0 if negative.

Meta Data's current Cash Flow from Operations (TTM) was 13.36. ==> Positive ==> Score 1.

Question 3. Change in Return on Assets

Compare this year's return on assets (1) to last year's return on assets.

Score 1 if it's higher, 0 if it's lower.

ROA (This Year)=Net Income/Total Assets (Aug22)
=694.495/49.58
=14.00756353

ROA (Last Year)=Net Income/Total Assets (Aug21)
=-168.903/77.691
=-2.1740356

Meta Data's return on assets of this year was 14.00756353. Meta Data's return on assets of last year was -2.1740356. ==> This year is higher. ==> Score 1.

Question 4. Quality of Earnings (Accrual)

Compare Cash flow return on assets (2) to return on assets (1)

Score 1 if CFROA > ROA, 0 if CFROA <= ROA.

Meta Data's current Net Income (TTM) was 694.50. Meta Data's current Cash Flow from Operations (TTM) was 13.36. ==> 13.36 <= 694.50 ==> CFROA <= ROA ==> Score 0.

Funding

Question 5. Change in Gearing or Leverage

Compare this year's gearing (long-term debt divided by average total assets) to last year's gearing.

Score 0 if this year's gearing is higher, 1 otherwise.

Gearing (This Year: Aug23)=Long-Term Debt & Capital Lease Obligation/Average Total Assets from Aug22 to Aug23
=1.212/85.362
=0.01419836

Gearing (Last Year: Aug22)=Long-Term Debt & Capital Lease Obligation/Average Total Assets from Aug21 to Aug22
=35/63.6355
=0.55000746

Meta Data's gearing of this year was 0.01419836. Meta Data's gearing of last year was 0.55000746. ==> This year is lower or equal to last year. ==> Score 1.

Question 6. Change in Working Capital (Liquidity)

Compare this year's current ratio (current assets divided by current liabilities) to last year's current ratio.

Score 1 if this year's current ratio is higher, 0 if it's lower

Current Ratio (This Year: Aug23)=Total Current Assets/Total Current Liabilities
=121.12/115.138
=1.05195505

Current Ratio (Last Year: Aug22)=Total Current Assets/Total Current Liabilities
=49.58/796.034
=0.06228377

Meta Data's current ratio of this year was 1.05195505. Meta Data's current ratio of last year was 0.06228377. ==> This year's current ratio is higher. ==> Score 1.

Question 7. Change in Shares in Issue

Compare the number of shares in issue this year, to the number in issue last year.

Score 0 if there is larger number of shares in issue this year, 1 otherwise.

Meta Data's number of shares in issue this year was 43.647. Meta Data's number of shares in issue last year was 11.083. ==> There is larger number of shares in issue this year. ==> Score 0.

Efficiency

Question 8. Change in Gross Margin

Compare this year's gross margin (Gross Profit divided by sales) to last year's.

Score 1 if this year's gross margin is higher, 0 if it's lower.

Gross Margin (This Year: TTM)=Gross Profit/Revenue
=15.421/32.426
=0.47557516

Gross Margin (Last Year: TTM)=Gross Profit/Revenue
=0.264/2.12
=0.1245283

Meta Data's gross margin of this year was 0.47557516. Meta Data's gross margin of last year was 0.1245283. ==> This year's gross margin is higher. ==> Score 1.

Question 9. Change in asset turnover

Compare this year's asset turnover (total sales for the year divided by total assets at the beginning of the year) to last year's asset turnover ratio.

Score 1 if this year's asset turnover ratio is higher, 0 if it's lower

Asset Turnover (This Year)=Revenue/Total Assets at the Beginning of This Year (Aug22)
=32.426/49.58
=0.65401372

Asset Turnover (Last Year)=Revenue/Total Assets at the Beginning of Last Year (Aug21)
=2.12/77.691
=0.02728759

Meta Data's asset turnover of this year was 0.65401372. Meta Data's asset turnover of last year was 0.02728759. ==> This year's asset turnover is higher. ==> Score 1.

Evaluation

Piotroski F-Score= Que. 1+ Que. 2+ Que. 3+Que. 4+Que. 5+Que. 6+Que. 7+Que. 8+Que. 9
=1+1+1+0+1+1+0+1+1
=7

Good or high score = 7, 8, 9
Bad or low score = 0, 1, 2, 3

Meta Data has an F-score of 7. It is a good or high score, which usually indicates a very healthy situation.

Meta Data  (NYSE:AIU) Piotroski F-Score Explanation

The developer of the system is Joseph D. Piotroski is relatively unknown accounting professor who shuns publicity and rarely gives interviews.

He graduated from the University of Illinois with a B.S. in accounting in 1989, received an M.B.A. from Indiana University in 1994. Five years later, in 1999, after earning a Ph.D. in accounting from the University of Michigan, he became an associate professor of accounting at the University of Chicago.

In 2000, he wrote a research paper called "Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers" (pdf).

He wanted to see if he can develop a system (using a simple nine-point scoring system) that can increase the returns of a strategy of investing in low price to book (referred to in the paper as high book to market) value companies.

What he found was something that exceeded his most optimistic expectations.

Buying only those companies that scored highest (8 or 9) on his nine-point scale, or F-Score as he called it, over the 20 year period from 1976 to 1996 led to an average out-performance over the market of 13.4%.

Even more impressive were the results of a strategy of investing in the highest F-Score companies (8 or 9) and shorting companies with the lowest F-Score (0 or 1).

Over the same period from 1976 to 1996 (20 years) this strategy led to an average yearly return of 23%, substantially outperforming the average S&P 500 index return of 15.83% over the same period.


Meta Data Piotroski F-Score Related Terms

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Meta Data (Meta Data) Business Description

Traded in Other Exchanges
Address
45-47 Au Pui Wan Street, Flat H 3/F, Haribest Industrial Building, Sha Tin New Territorie, Hong Kong, HKG
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.
Executives
Yiheng Capital, Llc 10 percent owner 101 CALIFORNIA STREET, SUITE 2880, San Francisco CA 94111

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