Cipher Mining Stock Piotroski F Score

CIFR Stock  USD 6.45  0.33  4.87%   
This module uses fundamental data of Cipher Mining to approximate its Piotroski F score. Cipher Mining F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Cipher Mining. 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 Cipher Mining financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Cipher Mining Altman Z Score, Cipher Mining Correlation, Cipher Mining Valuation, as well as analyze Cipher Mining Alpha and Beta and Cipher Mining Hype Analysis.
To learn how to invest in Cipher Stock, please use our How to Invest in Cipher Mining guide.
  
At this time, Cipher Mining's Short and Long Term Debt Total is relatively stable compared to the past year. As of 11/26/2024, Interest Debt Per Share is likely to grow to 0.03, while Net Debt is likely to drop (67.3 M). At this time, Cipher Mining's Enterprise Value Multiple is relatively stable compared to the past year. As of 11/26/2024, Price Fair Value is likely to grow to 2.23, while Free Cash Flow Yield is likely to drop (0.15).
At this time, it appears that Cipher Mining'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..
3.0
Piotroski F Score - Frail
Current Return On Assets

Negative

Focus
Change in Return on Assets

Decreased

Focus
Cash Flow Return on Assets

Negative

Focus
Current Quality of Earnings (accrual)

Decreasing

Focus
Asset Turnover Growth

Increase

Focus
Current Ratio Change

Decrease

Focus
Long Term Debt Over Assets Change

Lower Leverage

Focus
Change In Outstending Shares

Increase

Focus
Change in Gross Margin

Increase

Focus

Cipher Mining Piotroski F Score Drivers

The critical factor to consider when applying the Piotroski F Score to Cipher Mining is to make sure Cipher is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Cipher Mining'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 Cipher Mining's financial numbers are properly reported.
Current ValueLast YearChange From Last Year 10 Year Trend
Asset Turnover0.240.224
Notably Up
Slightly volatile
Gross Profit Margin0.750.6034
Fairly Up
Slightly volatile
Total Current Liabilities20.6 M33.8 M
Way Down
Slightly volatile
Non Current Liabilities Total21 M41 M
Way Down
Slightly volatile
Total Assets368.2 M566.1 M
Way Down
Slightly volatile
Total Current Assets117.8 M155.5 M
Way Down
Slightly volatile

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

About Cipher Mining 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

0.99

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

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

About Cipher Mining Fundamental Analysis

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

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

Moving together with Cipher Stock

  0.77V Visa Class APairCorr
  0.68DHIL Diamond Hill InvestmentPairCorr
  0.85DIST Distoken AcquisitionPairCorr
  0.84AB AllianceBernsteinPairCorr
  0.79AC Associated CapitalPairCorr

Moving against Cipher Stock

  0.61PT Pintec TechnologyPairCorr
The ability to find closely correlated positions to Cipher Mining could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Cipher Mining 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 Cipher Mining - 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 Cipher Mining to buy it.
The correlation of Cipher Mining 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 Cipher Mining moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Cipher Mining 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 Cipher Mining 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 Cipher Stock Analysis

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