Meta Data Profitability Analysis
| AIU Stock | USD 0.55 0.06 9.84% |
Net Income | First Reported 2016-11-30 | Previous Quarter -348 K | Current Value 698 M | Quarterly Volatility 1.3 B |
| Current Value | Last Year | Change From Last Year | 10 Year Trend | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Gross Profit Margin | 0.47 | 0.55 |
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For Meta Data profitability analysis, we use financial ratios and fundamental drivers that measure the ability of Meta Data to generate income relative to revenue, assets, operating costs, and current equity. These fundamental indicators attest to how well Meta Data utilizes its assets to generate profit and value for its shareholders. The profitability module also shows relationships between Meta Data's most relevant fundamental drivers. It provides multiple suggestions of what could affect the performance of Meta Data over time as well as its relative position and ranking within its peers.
Meta |
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 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.
Earnings Share 0.24 | Revenue Per Share 0.743 | Quarterly Revenue Growth 8.155 | Return On Assets 0.0996 |
The market value of Meta Data is measured differently than its book value, which is the value of Meta 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 if Meta Data is a good investment 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.
Meta Data Profit Margin vs. Return On Asset Fundamental Analysis
Comparative valuation techniques use various fundamental indicators to help in determining Meta Data's current stock value. Our valuation model uses many indicators to compare Meta Data value to that of its competitors to determine the firm's financial worth. Meta Data is number one stock in return on asset category among related companies. It is number one stock in profit margin category among related companies fabricating about 215.04 of Profit Margin per Return On Asset. At this time, Meta Data's Net Profit Margin is comparatively stable compared to the past year.Comparative valuation analysis is a catch-all model that can be used if you cannot value Meta Data by discounting back its dividends or cash flows. This model doesn't attempt to find an intrinsic value for Meta Data's Stock. Still, instead, it compares the stock's price multiples to a benchmark or nearest competition to determine if the stock is relatively undervalued or overvalued. The reason why the comparable model can be used in almost all circumstances is due to the vast number of multiples that can be utilized, such as the price-to-earnings (P/E), price-to-book (P/B), price-to-sales (P/S), price-to-cash flow (P/CF), and many others. The P/E ratio is the most commonly used of these ratios because it focuses on the Meta Data's earnings, one of the primary drivers of an investment's value.Meta Profit Margin vs. Return On Asset
Return on Asset or ROA shows how effective is the management of the company in generating income from utilizing all of the assets at their disposal. It is a useful ratio to evaluate the performance of different departments of a company as well as to understand management performance over time.
Meta Data |
| = | 0.0996 |
Return on Asset measures overall efficiency of a company in generating profits from its total assets. It is expressed as the percentage of profits earned per dollar of Asset. A low ROA typically means that a company is asset-intensive and therefore will needs more money to continue generating revenue in the future.
Profit Margin measures overall efficiency of a company and shows its ability to withstand competition as well as defend against adverse conditions such as rising costs, falling prices, decline in sales or management distress. Profit margin tells investors how well the company executes on its overall pricing strategies as well as how effective the company in controlling its costs.
Meta Data |
| = | 21.42 % |
In a nutshell, Profit Margin indicator shows the amount of money the company makes from total sales or revenue. It can provide a good insight into companies in the same sector, as well as help to identify trends of a company from year to year.
Meta Profit Margin Comparison
Meta Data is currently under evaluation in profit margin category among related companies.
Meta Data Profitability Projections
The most important aspect of a successful company is its ability to generate a profit. For investors in Meta Data, profitability is also one of the essential criteria for including it into their portfolios because, without profit, Meta Data will eventually generate negative long term returns. The profitability progress is the general direction of Meta Data's change in net profit over the period of time. It can combine multiple indicators of Meta Data, where stable trends show no significant progress. An accelerating trend is seen as positive, while a decreasing one is unfavorable. A rising trend means that profits are rising, and operational efficiency may be rising as well. A decreasing trend is a sign of poor performance and may indicate upcoming losses.
| Last Reported | Projected for Next Year | ||
| Accumulated Other Comprehensive Income | 125.5 M | 86.1 M | |
| Operating Income | 12.2 M | 12.9 M | |
| Income Before Tax | 9.5 M | 10 M | |
| Total Other Income Expense Net | -3.6 K | -3.8 K | |
| Net Income | 625 M | 656.3 M | |
| Income Tax Expense | -612.1 M | -581.5 M | |
| Interest Income | 680.4 K | 646.4 K | |
| Net Income Applicable To Common Shares | 625 M | 656.3 M | |
| Net Interest Income | -2.8 M | -2.9 M | |
| Net Income From Continuing Ops | 9.5 M | 10 M | |
| Change To Netincome | -786.5 M | -747.2 M | |
| Net Income Per Share | 0.02 | 0.02 | |
| Income Quality | 0.02 | 0.02 | |
| Net Income Per E B T | 59.34 | 62.30 |
Meta Profitability Driver Comparison
Profitability drivers are factors that can directly affect your investment outlook on Meta Data. Investors often realize that things won't turn out the way they predict. There are maybe way too many unforeseen events and contingencies during the holding period of Meta Data position where the market behavior may be hard to predict, tax policy changes, gold or oil price hikes, calamities change, and many others. The question is, are you prepared for these unexpected events? Although some of these situations are obviously beyond your control, you can still follow the important profit indicators to know where you should focus on when things like this occur. Below are some of the Meta Data's important profitability drivers and their relationship over time.
Meta Data Profitability Trends
Meta Data profitability trend refers to the progression of profit or loss within a business. An upward trend means that Meta Data's profit has generally increased over time, and a downward profitability trend means profits are declining. Recognizing problems early in profitability trends allows investors to address revenue and cost issues in advance. Investors and analysts usually monitor three types of profitability trends: gross, operating, and net. Gross profit is the difference between revenue and costs of goods sold. Operating profit is Meta Data's gross profit minus its overhead. After you account for other unusual revenue, expenses, and costs, you get net profit. Gross profit trends are often a good indicator of future profitability. If you have high gross profit margins, you have a better chance to cover overhead and make money.
Meta Data Profitability Drivers Correlations
One of the toughest challenges investors face today is learning how to quickly synthesize and read into endless financial statements and information provided by the company, SEC reporting, and various external parties. Understanding the correlation between Meta Data different financial indicators related to revenue and profit generation helps investors identify and prioritize their investing strategies towards Meta Data in a much-optimized way. Analyzing correlations between profit drivers that are directly associated with dollar figures is the most effective way to break down Meta Data's future profitability.
Click cells to compare fundamentals
Use Meta Data in pair-trading
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Meta Data position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Meta Data will appreciate offsetting losses from the drop in the long position's value.Meta Data Pair Trading
Meta Data Pair Trading Analysis
The ability to find closely correlated positions to Meta Data could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Meta Data when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Meta Data - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Meta Data to buy it.
The correlation of Meta Data is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Meta Data moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Meta Data moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Meta Data can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Use Investing Themes to Complement your Meta Data position
In addition to having Meta Data in your portfolios, you can quickly 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 investment opportunity, you can then find an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility.Did You Try This Idea?
Run Money Funds Thematic Idea Now
Money Funds
Funds or Etfs that invest most if their asset in companies from financial sector such as commercial banks, insurance companies, investment funds, and real estate. The Money Funds theme has 31 constituents at this time.
You can either use a buy-and-hold strategy to lock in the entire theme or actively trade it to take advantage of the short-term price volatility of individual constituents. Macroaxis can help you discover thousands of investment opportunities in different asset classes. In addition, you can partner with us for reliable portfolio optimization as you plan to utilize Money Funds Theme or any other thematic opportunities.
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Check out Trending Equities. For more information on how to buy Meta Stock please use our How to Invest in Meta Data guide.You can also try the Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
Complementary Tools for Meta Stock analysis
When running Meta Data's 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 the 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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To fully project Meta Data's future profitability, investors should examine all historical financial statements. These statements provide investors with a comprehensive snapshot of the financial position of Meta Data at a specified time, usually calculated after every quarter, six months, or one year. Three primary documents fall into the category of financial statements. These documents include Meta Data's income statement, its balance sheet, and the statement of cash flows.