Meta Data Stock Analysis

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 Stock
  

USD 1.03  0.03  3.00%   

The newest Meta Data price drop could raise concerns from private investors as the firm is trading at a share price of 1.03 on 14,700 in volume. The company executives were unable to exploit market volatilities in September. However, diversifying your overall positions with Meta Data can protect your principal portfolio during market swings. The stock standard deviation of daily returns for 90 days investing horizon is currently 5.26. The very high volatility is mostly attributed to the latest market swings and not very good earnings reports from some of the Meta Data partners.
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The Meta Data stock analysis report makes it easy to digest most publicly released information about Meta Data and get updates on important government artifacts, including earning estimates, SEC corporate filings, and announcements. Meta Data Stock analysis module also helps to analyze the Meta Data price relationship with some important fundamental indicators such as market cap and management efficiency.

Meta Data Stock Analysis Notes

The company recorded a loss per share of 112.54. Meta Data had not issued any dividends in recent years. The entity had a split on the 24th of January 2022. Meta Data Limited provides tutoring services for the students of kindergarten and primary, middle, and high schools in the Peoples Republic of China. Meta Data Limited was founded in 2007 and is headquartered in Shanghai, the Peoples Republic of China. Meta Data operates under Education Training Services classification in the United States and is traded on New York Stock Exchange. It employs 13497 people. For more info on Meta Data please contact the company at 86 21 2250 5999 or go to https://ir.onesmart.org.

Meta Data Investment Alerts

Many investors view ongoing market volatility as an opportunity to purchase more stocks at a favorable price or short it to generate a bearish trend profit opportunity. If you are one of those investors, make sure you clearly understand the position you are entering. Meta Data's investment alerts are automatically generated signals that are significant enough to either complement your investing judgment regarding Meta Data or challenge it. These alerts can help you understand what you are buying and avoid costly mistakes.
Meta Data generated a negative expected return over the last 90 days
Meta Data has high historical volatility and very poor performance
Meta Data has some characteristics of a very speculative penny stock
Meta Data has high likelihood to experience some financial distress in the next 2 years
The company has 1.37 B in debt. Meta Data has a current ratio of 0.1, suggesting that it has not enough short term capital to pay financial commitments when the payables are due. Debt can assist Meta Data until it has trouble settling it off, either with new capital or with free cash flow. So, Meta Data's shareholders could walk away with nothing if the company can't fulfill its legal obligations to repay debt. However, a more frequent occurrence is when companies like Meta Data sell additional shares at bargain prices, diluting existing shareholders. Debt, in this case, can be an excellent and much better tool for Meta Data to invest in growth at high rates of return. When we think about Meta Data's use of debt, we should always consider it together with cash and equity.
The entity reported the last year's revenue of 3.42 B. Reported Net Loss for the year was (4.99 B) with profit before taxes, overhead, and interest of 1.33 B.
Latest headline from www.nasdaq.com: US STOCKS-Futures edge higher ahead of key inflation data - Nasdaq

Meta Data SEC Filings

SEC filings are important regulatory documents required of all public companies to provide to potential investors. Meta Data prospectus issued under the guidelines of SEC is a legal declaration of facts and statements to ensure that Meta Data investors are not misled. SEC filings are required by law to meet strict transparency standards and other important legal constraints. Although many companies may choose careful wording to disguise some material information, SEC filings make crucial Meta Data specific information freely available to individual and institutional investors to make a timely investment decision.
2nd of September 2022
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23rd of August 2022
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11th of August 2022
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2nd of May 2022
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29th of March 2022
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16th of February 2022
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14th of February 2022
Unclassified Corporate Event
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11th of February 2022
Unclassified Corporate Event
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Meta Data Thematic Classifications

In addition to having Meta Data stock in your portfolios, you can add positions using our predefined set of ideas and optimize them against your very unique investing style. A single investing idea is a collection of funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of investment themes. After you determine your favorite investment opportunity, you can then obtain an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility. If you are a result-oriented investor, you can benefit from optimizing one of our existing themes to build an efficient portfolio against your specific investing outlook.
Education
Tutoring, learning, and education services

Meta Data Stock Institutional Investors

Have you ever been surprised when a price of an equity instrument such as Meta Data is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Meta Data backward and forwards among themselves. Meta Data's institutional investor refers to the entity that pools money to purchase Meta Data's securities or originate loans. Institutional investors include commercial and private banks, credit unions, insurance companies, pension funds, hedge funds, endowments, and mutual funds. Operating companies that invest excess capital in these types of assets may also be included in the term and may influence corporate governance by exercising voting rights in their investments.
Security TypeSharesValue
Goldman Sachs Group IncCommon Shares31.9 M319.2 M
Yiheng Capital Management LpCommon Shares7.4 MM
Keenan Capital LlcCommon Shares3.2 M1.3 M
Nuveen Asset Management LlcCommon Shares77.7 K626 K
Morgan StanleyCommon SharesM409 K
Blackrock IncCommon Shares1.6 M373 K
State Street CorpCommon Shares484 K194 K
Note, although Meta Data's institutional investors appear to be way more sophisticated than retail investors, it remains unclear if professional active investment managers can reliably enhance risk-adjusted returns by an amount that exceeds fees and expenses.

Meta Data Market Capitalization

The company currently falls under 'Micro-Cap' category with total capitalization of 18.92 M. Market capitalization usually refers to the total value of a company's stock within the entire market. To calculate Meta Data's market, we take the total number of its shares issued and multiply it by Meta Data's current market price. To manage market risk and economic uncertainty, many investors today build portfolios that are diversified across equities with different market capitalizations. However, as a general rule, conservative investors tend to hold large-cap stocks, and these looking for more risk prefer small-cap and mid-cap equities.

Meta Data Profitablity

Meta Data's profitability indicators refer to fundamental financial ratios that showcase Meta Data's ability to generate income relative to its revenue or operating costs. If, let's say, Meta Data is currently losing money, the management's focus should be on how to reverse that trend. However, when revenue exceeds expenses, Meta Data's executives or investors may be in less hurry to break that information down - which is where profitability analysis comes into play. Gaining a greater understanding of Meta Data's profitability requires more research than a typical breakdown of Meta Data's financial statements. By doing a profitability analysis, companies can identify areas needing attention, and investors can make a profitable trade.
The company has Net Profit Margin of (145.69) %, which means that it does not effectively control expenditures or properly executes on its pricing strategies. This is way below average. In the same way, it shows Net Operating Margin of (80.02) %, which entails that for every $100 of revenue, it lost -0.8.

Management Efficiency

The entity has Return on Asset of (40.76) % which means that on every $100 spent on asset, it lost $40.76. This is way below average. Meta Data management efficiency ratios could be used to measure how well meta data manages its routine affairs as well as how well it operates its assets and liabilities.

Technical Drivers

As of the 2nd of October, Meta Data secures the risk adjusted performance of (0.10), and Mean Deviation of 3.78. Meta Data technical analysis lets you operate historical price patterns with an objective to determine a pattern that forecasts the direction of the firm's future prices. Strictly speaking, you can use this information to find out if the firm will indeed mirror its model of past prices, or the prices will eventually revert. We were able to collect and analyze data for nineteen technical drivers for Meta Data, which can be compared to its peers in the industry. Please verify Meta Data variance, value at risk, as well as the relationship between the Value At Risk and skewness to decide if Meta Data is priced some-what accurately, providing market reflects its recent price of 1.03 per share. Given that Meta Data is a hitting penny stock territory we strongly suggest to closely look at its total risk alpha.

Meta Data Price Movement Analysis

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Meta Data Predictive Daily Indicators

Meta Data intraday indicators are useful technical analysis tools used by many experienced traders. Just like the conventional technical analysis, daily indicators help intraday investors to analyze the price movement with the timing of Meta Data stock daily movement. By combining multiple daily indicators into a single trading strategy, you can limit your risk while still earning strong returns on your managed positions.

Meta Data Forecast Models

Meta Data time-series forecasting models is one of many Meta Data's stock analysis techniquest aimed to predict future share value based on previously observed values. Time-series forecasting models ae widely used for non-stationary data. Non-stationary data are called the data whose statistical properties e.g. the mean and standard deviation are not constant over time but instead, these metrics vary over time. These non-stationary Meta Data's historical data is usually called time-series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the market movement and maximize returns from investment trading.

About Meta Data Stock Analysis

Stock analysis is the technique used by a trader or investor to examine and evaluate how Meta Data prices is reacting to, or reflecting on a current market direction and economic conditions. It can be used to make informed decisions about market timing, and when buying or selling Meta Data shares will generate the highest return on investment. We also built our stock analysis module to help investors to gain an insight into the world economy as a whole, the stock market, thematic ideas, a specific sector, or an individual Stock such as Meta Data. By using and applying Meta Data Stock analysis, traders can create a robust methodology for identifying Meta Data entry and exit points for their positions.
Meta Data Limited provides tutoring services for the students of kindergarten and primary, middle, and high schools in the Peoples Republic of China. Meta Data Limited was founded in 2007 and is headquartered in Shanghai, the Peoples Republic of China. Meta Data operates under Education Training Services classification in the United States and is traded on New York Stock Exchange. It employs 13497 people.

Be your own money manager

As an investor, your ultimate goal is to build wealth. Optimizing your investment portfolio is an essential element in this goal. Using our stock analysis tools, you can find out how much better you can do when adding Meta Data to your portfolios without increasing risk or reducing expected return.

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Please continue to Trending Equities. You can also try Global Correlations module to find global opportunities by holding instruments from different markets.

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When running Meta Data price analysis, check to measure Meta Data's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Meta Data is operating at the current time. Most of Meta Data's value examination focuses on studying past and present price action to predict the probability of Meta Data's future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move Meta Data's price. Additionally, you may evaluate how the addition of Meta Data to your portfolios can decrease your overall portfolio volatility.
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Is Meta Data's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Meta Data. If investors know Meta Data will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Meta Data listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
The market value of Meta Data is measured differently than its book value, which is the value of Meta Data that is recorded on the company's balance sheet. Investors also form their own opinion of Meta Data's value that differs from its market value or its book value, called intrinsic value, which is Meta Data's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Meta Data's market value can be influenced by many factors that don't directly affect Meta Data's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Meta Data's value and its price as these two are different measures arrived at by different means. Investors typically determine Meta Data value by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Meta Data's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.