| DTSTW Stock | | | USD 0.40 0.02 5.26% |
This module uses fundamental data of Data Storage to approximate the value of its Beneish M Score. Data Storage 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
Data Storage Piotroski F Score and
Data Storage Altman Z Score analysis.
For more information on how to buy Data Stock please use our
How to Invest in Data Storage guide.
At this time, Data Storage's
Short Term Debt is fairly stable compared to the past year.
Long Term Debt is likely to climb to about 105.9
K in 2024, whereas
Short and Long Term Debt Total is likely to drop slightly above 571.4
K in 2024. At this time, Data Storage's
Average Inventory is fairly stable compared to the past year.
Cash Per Share is likely to climb to 1.96 in 2024, whereas
PTB Ratio is likely to drop 0.66 in 2024.
At this time, it appears that Data Storage is an unlikely manipulator. The earnings manipulation may begin if Data Storage'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 Data Storage 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 Data Storage'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.
-3.59
Beneish M Score - Unlikely Manipulator
| Elasticity of Receivables | |
| Financial Leverage Condition | |
Data Storage Beneish M-Score Indicator Trends
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 Data Storage'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.
Data Storage Beneish M-Score Driver Matrix
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 Data Storage's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Data Storage in a much-optimized way. Analyzing correlations between earnings drivers directly associated with dollar figures is the most effective way to find Data Storage's degree of accounting gimmicks and manipulations.
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About Data Storage Beneish M Score
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.
Data Storage 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 Data Storage. 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.
About Data Storage Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Data Storage's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Data Storage using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of Data Storage 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.
Please read more on our
fundamental analysis page.
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Additional Tools for Data Stock Analysis
When running Data Storage's price analysis, check to
measure Data Storage'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 Data Storage is operating at the current time. Most of Data Storage's value examination focuses on studying past and present price action to
predict the probability of Data Storage's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Data Storage's price. Additionally, you may evaluate how the addition of Data Storage to your portfolios can decrease your overall portfolio volatility.