| COUR Stock | | | USD 7.11 0.13 1.86% |
This module uses fundamental data of Coursera to approximate its Piotroski F score. Coursera F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Coursera. These three categories are profitability, efficiency, and funding. Some research analysts and sophisticated value traders use Piotroski F Score to find opportunities outside of the conventional market and financial statement analysis.They believe that some of the new information about Coursera financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out
Coursera Altman Z Score,
Coursera Correlation,
Coursera Valuation, as well as analyze
Coursera Alpha and Beta and
Coursera Hype Analysis.
To learn how to invest in Coursera Stock, please use our
How to Invest in Coursera guide.
At this time, Coursera's
Net Debt To EBITDA is relatively stable compared to the past year. As of 11/22/2024,
Debt To Equity is likely to grow to 0.01, while
Short Term Debt is likely to drop slightly above 12.2
M. At this time, Coursera's
Inventory Turnover is relatively stable compared to the past year. As of 11/22/2024,
Payables Turnover is likely to grow to 3.96, while
Book Value Per Share is likely to drop 2.53.
At this time, it appears that Coursera's Piotroski F Score is Poor. Although some professional money managers and academia have recently criticized
Piotroski F-Score model, we still consider it an effective method of
predicting the state of the financial strength of any organization that is not predisposed to accounting gimmicks and manipulations. Using this score on the criteria to originate an efficient long-term portfolio can help investors filter out the purely speculative stocks or equities playing fundamental games by manipulating their earnings..
4.0
Piotroski F Score - Poor
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| Cash Flow Return on Assets | |
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Coursera Piotroski F Score Drivers
The critical factor to consider when applying the Piotroski F Score to Coursera is to make sure Coursera is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Coursera'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. Below are the main accounts that are used in the Piotroski F Score model. By analyzing the historical trends of the mains drivers, investors can determine if Coursera's financial numbers are properly reported.
Coursera F 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 project the various growth rates. Understanding the correlation between Coursera's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Coursera in a much-optimized way.
Click cells to compare fundamentals
About Coursera Piotroski F Score
F-Score is one of many stock grading techniques developed by Joseph Piotroski, a professor of accounting at the Stanford University Graduate School of Business. It was published in 2002 under the paper titled
Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Piotroski F Score is based on binary analysis strategy in which stocks are given one point for passing 9 very simple fundamental tests, and zero point otherwise. According to Mr. Piotroski's analysis, his F-Score binary model can help to predict the performance of low price-to-book stocks.
Coursera ESG Sustainability
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, Coursera's sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Coursera's managers, analysts, and investors.
About Coursera Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Coursera's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Coursera using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of Coursera 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.
Pair Trading with Coursera
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 Coursera 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 Coursera will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Coursera could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Coursera 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 Coursera - 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 Coursera to buy it.
The correlation of Coursera 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 Coursera moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Coursera 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 Coursera 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.
Additional Tools for Coursera Stock Analysis
When running Coursera's price analysis, check to
measure Coursera'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 Coursera is operating at the current time. Most of Coursera's value examination focuses on studying past and present price action to
predict the probability of Coursera's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Coursera's price. Additionally, you may evaluate how the addition of Coursera to your portfolios can decrease your overall portfolio volatility.