This module uses fundamental data of Datasea to approximate the value of its Beneish M Score. Datasea M Score tells investors if the company management is likely to be manipulating earnings. The score is calculated using eight financial indicators that are adjusted by a specific multiplier. Please note, the M Score is a probabilistic model and cannot detect companies that manipulate their earnings with 100% accuracy. Check out Datasea Piotroski F Score and Datasea Altman Z Score analysis.
At this time, Datasea's Short and Long Term Debt Total is comparatively stable compared to the past year. Net Debt is likely to gain to about 2.6 M in 2024, despite the fact that Net Debt To EBITDA is likely to grow to (0.26). At this time, Datasea's Graham Number is comparatively stable compared to the past year.
At this time, Datasea's M Score is unavailable. The earnings manipulation may begin if Datasea's top management creates an artificial sense of financial success, forcing the stock price to be traded at a high price-earnings multiple than it should be. In general, excessive earnings management by Datasea executives may lead to removing some of the operating profits from subsequent periods to inflate earnings in the following periods. This way, the manipulation of Datasea's earnings can lead to misrepresentations of actual financial condition, taking the otherwise loyal stakeholders on to the path of questionable ethical practices and plain fraud.
The cure to earnings manipulation is the transparency of financial reporting. It will typically remove the temptation of the top executives to inflate earnings (i.e., to promote the idea of 'winning at any cost'). Because a healthy internal audit department can enhance transparency, the board should promote the auditors' access to all the record-keeping systems across the enterprise. For example, if Datasea's auditors report directly to the board (not management), the managers will be reluctant to manipulate simply due to the fear of punishment. On the other hand, the auditors will be free to investigate the ledgers properly because they know that the board has their back.
One of the toughest challenges investors face today is learning how to quickly synthesize historical financial statements and information provided by the company, SEC reporting, and various external parties in order to detect the potential manipulation of earnings. Understanding the correlation between Datasea's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Datasea in a much-optimized way. Analyzing correlations between earnings drivers directly associated with dollar figures is the most effective way to find Datasea's degree of accounting gimmicks and manipulations.
M-Score is one of many grading techniques for value stocks. It was developed by Professor M. Daniel Beneish of the Kelley School of Business at Indiana University and published in 1999 under the paper titled The Detection of Earnings Manipulation. The Beneish score is a multi-factor model that utilizes financial identifiers to compile eight variables used to classify whether a company has manipulated its reported earnings. The variables are built from the officially filed financial statements to create a final score call 'M Score.' The score helps to identify companies that are likely to manipulate their profits if they show deteriorating gross margins, operating expenses, and leverage against growing revenue.
Total Assets
3.19 Million
At this time, Datasea's Total Assets are comparatively stable compared to the past year.
Datasea Earnings Manipulation Drivers
Although earnings manipulation is typically not the result of intentional misconduct by the c-level executives, it is still a widespread practice by the senior management of public companies such as Datasea. It is usually done by a series of misrepresentations of various accounting rules and operating activities across multiple financial cycles. The best way to spot the manipulation is to examine the historical financial statement to find inconsistencies in earning reports to find trends in assets or liabilities that are not sustainable in the future.
Some studies have found that companies with high sustainability scores are getting higher valuations than competitors with lower social-engagement activities. While most ESG disclosures are voluntary and do not directly affect the long term financial condition, Datasea's sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Datasea's managers, analysts, and investors.
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About Datasea Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Datasea's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Datasea using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Datasea based on its fundamental data. In general, a quantitative approach, as applied to this company, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.
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 Datasea 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 Datasea will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Datasea could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Datasea 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 Datasea - 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 Datasea to buy it.
The correlation of Datasea 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 Datasea moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Datasea 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 Datasea 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.
When running Datasea's price analysis, check to measure Datasea'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 Datasea is operating at the current time. Most of Datasea's value examination focuses on studying past and present price action to predict the probability of Datasea's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Datasea's price. Additionally, you may evaluate how the addition of Datasea to your portfolios can decrease your overall portfolio volatility.