| QUBT Stock | | | USD 8.63 0.61 7.61% |
This module uses fundamental data of Quantum Computing to approximate its Piotroski F score. Quantum Computing F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Quantum Computing. 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 Quantum Computing financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out
Quantum Computing Altman Z Score,
Quantum Computing Correlation,
Quantum Computing Valuation, as well as analyze
Quantum Computing Alpha and Beta and
Quantum Computing Hype Analysis.
For more information on how to buy Quantum Stock please use our
How to Invest in Quantum Computing guide.
At this time, it appears that Quantum Computing's Piotroski F Score is Frail. 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..
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Piotroski F Score - Frail
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Quantum Computing Piotroski F Score Drivers
The critical factor to consider when applying the Piotroski F Score to Quantum Computing is to make sure Quantum is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Quantum Computing'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 Quantum Computing's financial numbers are properly reported.
About Quantum Computing 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.
About Quantum Computing Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Quantum Computing's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Quantum Computing using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of Quantum Computing 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.
Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
Additional Tools for Quantum Stock Analysis
When running Quantum Computing's price analysis, check to
measure Quantum Computing'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 Quantum Computing is operating at the current time. Most of Quantum Computing's value examination focuses on studying past and present price action to
predict the probability of Quantum Computing's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Quantum Computing's price. Additionally, you may evaluate how the addition of Quantum Computing to your portfolios can decrease your overall portfolio volatility.