Shopify Stock Piotroski F Score

SHOP Stock  USD 106.48  2.54  2.44%   
This module uses fundamental data of Shopify to approximate its Piotroski F score. Shopify F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Shopify. 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 Shopify financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Shopify Altman Z Score, Shopify Correlation, Shopify Valuation, as well as analyze Shopify Alpha and Beta and Shopify Hype Analysis.
To learn how to invest in Shopify Stock, please use our How to Invest in Shopify guide.
  
At this time, Shopify's Long Term Debt To Capitalization is relatively stable compared to the past year. As of 11/22/2024, Total Debt To Capitalization is likely to grow to 0.10, while Net Debt is likely to drop (276.1 M). At this time, Shopify's Free Cash Flow Per Share is relatively stable compared to the past year. As of 11/22/2024, ROIC is likely to grow to 0.02, while Capex To Depreciation is likely to drop 0.53.
At this time, it appears that Shopify's Piotroski F Score is Strong. 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..
8.0
Piotroski F Score - Strong
Current Return On Assets

Positive

Focus
Change in Return on Assets

Increased

Focus
Cash Flow Return on Assets

Positive

Focus
Current Quality of Earnings (accrual)

Improving

Focus
Asset Turnover Growth

Increase

Focus
Current Ratio Change

Increase

Focus
Long Term Debt Over Assets Change

Higher Leverage

Focus
Change In Outstending Shares

Decrease

Focus
Change in Gross Margin

Increase

Focus

Shopify Piotroski F Score Drivers

The critical factor to consider when applying the Piotroski F Score to Shopify is to make sure Shopify is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Shopify'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 Shopify's financial numbers are properly reported.
Current ValueLast YearChange From Last Year 10 Year Trend
Asset Turnover0.670.6248
Notably Up
Pretty Stable
Gross Profit Margin0.640.4979
Significantly Up
Slightly volatile
Total Current Liabilities942.9 M898 M
Sufficiently Up
Slightly volatile
Non Current Liabilities Total1.4 B1.3 B
Sufficiently Up
Slightly volatile
Total Assets11.9 B11.3 B
Sufficiently Up
Slightly volatile
Total Current Assets3.4 B6.3 B
Way Down
Slightly volatile

Shopify 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 Shopify's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Shopify in a much-optimized way.

About Shopify 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.

Book Value Per Share

7.43

At this time, Shopify's Book Value Per Share is relatively stable compared to the past year.

Shopify Current Valuation Drivers

We derive many important indicators used in calculating different scores of Shopify from analyzing Shopify's financial statements. These drivers represent accounts that assess Shopify's ability to generate profits relative to its revenue, operating costs, and shareholders' equity. Below are some of Shopify's important valuation drivers and their relationship over time.
201920202021202220232024 (projected)
Market Cap44.9B135.3B171.7B44.0B99.8B52.4B
Enterprise Value44.4B133.6B170.4B43.7B99.6B51.9B

Shopify 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, Shopify's sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Shopify's managers, analysts, and investors.
Environmental
Governance
Social

About Shopify Fundamental Analysis

The Macroaxis Fundamental Analysis modules help investors analyze Shopify's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Shopify using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Shopify 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 Shopify

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 Shopify 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 Shopify will appreciate offsetting losses from the drop in the long position's value.

Moving together with Shopify Stock

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Moving against Shopify Stock

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The ability to find closely correlated positions to Shopify could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Shopify 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 Shopify - 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 Shopify to buy it.
The correlation of Shopify 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 Shopify moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Shopify 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 Shopify 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.
Pair CorrelationCorrelation Matching

Additional Tools for Shopify Stock Analysis

When running Shopify's price analysis, check to measure Shopify'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 Shopify is operating at the current time. Most of Shopify's value examination focuses on studying past and present price action to predict the probability of Shopify's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Shopify's price. Additionally, you may evaluate how the addition of Shopify to your portfolios can decrease your overall portfolio volatility.