Generation Mining Stock Piotroski F Score

GENM Stock  CAD 0.14  0.01  6.67%   
This module uses fundamental data of Generation Mining to approximate its Piotroski F score. Generation Mining F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Generation 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 Generation Mining financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Risk vs Return Analysis to better understand how to build diversified portfolios, which includes a position in Generation Mining. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors.
  
At this time, Generation Mining's Debt Equity Ratio is very stable compared to the past year. At this time, Generation Mining's Current Ratio is very stable compared to the past year. As of the 30th of December 2024, Debt To Equity is likely to grow to 0.17, though PTB Ratio is likely to grow to (1.40).
At this time, it appears that Generation Mining's Piotroski F Score is Inapplicable. 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 - Inapplicable
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)

Improving

Focus
Asset Turnover Growth

No Change

Focus
Current Ratio Change

Increase

Focus
Long Term Debt Over Assets Change

Lower Leverage

Focus
Change In Outstending Shares

Decrease

Focus
Change in Gross Margin

No Change

Focus

Generation Mining Piotroski F Score Drivers

The critical factor to consider when applying the Piotroski F Score to Generation Mining is to make sure Generation is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Generation 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 Generation Mining's financial numbers are properly reported.
Current ValueLast YearChange From Last Year 10 Year Trend
Total Assets21.2 M20.2 M
Sufficiently Up
Slightly volatile
Total Current Assets8.4 M16.7 M
Way Down
Slightly volatile

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

About Generation 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

(0.15)

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

Generation Mining Current Valuation Drivers

We derive many important indicators used in calculating different scores of Generation Mining from analyzing Generation Mining's financial statements. These drivers represent accounts that assess Generation Mining's ability to generate profits relative to its revenue, operating costs, and shareholders' equity. Below are some of Generation Mining's important valuation drivers and their relationship over time.
201920202021202220232024 (projected)
Market Cap18.7M99.4M150.1M138.9M43.4M47.2M
Enterprise Value17.9M87.9M144.9M123.4M29.5M42.1M

About Generation Mining Fundamental Analysis

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

Moving together with Generation Stock

  0.75AG First Majestic SilverPairCorr
  0.67IE Ivanhoe EnergyPairCorr
  0.74ORE Orezone Gold CorpPairCorr
  0.63FDY Faraday Copper CorpPairCorr
  0.66INFM Infinico Metals CorpPairCorr

Moving against Generation Stock

  0.85ERE-UN European Residential RealPairCorr
  0.85TCS TECSYS IncPairCorr
  0.84DBO D Box TechnologiesPairCorr
  0.76ENS-PA E Split CorpPairCorr
  0.74FFH Fairfax FinancialPairCorr
The ability to find closely correlated positions to Generation 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 Generation 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 Generation 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 Generation Mining to buy it.
The correlation of Generation 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 Generation Mining moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Generation 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 Generation 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

Other Information on Investing in Generation Stock

Generation Mining financial ratios help investors to determine whether Generation Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Generation with respect to the benefits of owning Generation Mining security.