This module uses fundamental data of Uber Technologies to approximate the value of its Beneish M Score. Uber Technologies 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 Uber Technologies Piotroski F Score and Uber Technologies Altman Z Score analysis.
At this time, Uber Technologies' Short and Long Term Debt is relatively stable compared to the past year. As of 11/30/2024, Net Debt is likely to grow to about 6.7 B, while Short Term Debt is likely to drop slightly above 263.4 M. At this time, Uber Technologies' EV To Sales is relatively stable compared to the past year. As of 11/30/2024, Free Cash Flow Per Share is likely to grow to 1.73, while Capex To Depreciation is likely to drop 0.26.
At this time, it appears that Uber Technologies is an unlikely manipulator. The earnings manipulation may begin if Uber Technologies' 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 Uber Technologies 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 Uber Technologies' 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 Uber Technologies' 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 Uber Technologies' different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Uber Technologies in a much-optimized way. Analyzing correlations between earnings drivers directly associated with dollar figures is the most effective way to find Uber Technologies' 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.
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 Uber Technologies. 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, Uber Technologies' sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Uber Technologies' managers, analysts, and investors.
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About Uber Technologies Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Uber Technologies's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Uber Technologies using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Uber Technologies 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 Uber Technologies 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 Uber Technologies will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Uber Technologies could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Uber Technologies 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 Uber Technologies - 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 Uber Technologies to buy it.
The correlation of Uber Technologies 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 Uber Technologies moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Uber Technologies 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 Uber Technologies 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 Uber Technologies' price analysis, check to measure Uber Technologies' 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 Uber Technologies is operating at the current time. Most of Uber Technologies' value examination focuses on studying past and present price action to predict the probability of Uber Technologies' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Uber Technologies' price. Additionally, you may evaluate how the addition of Uber Technologies to your portfolios can decrease your overall portfolio volatility.