This module uses fundamental data of GreenFirst Forest to approximate the value of its Beneish M Score. GreenFirst Forest M Score tells investors if the company management is likely to be manipulating earnings. The score is calculated using eight financial indicators that are adjusted by a specific multiplier. Please note, the M Score is a probabilistic model and cannot detect companies that manipulate their earnings with 100% accuracy. Check out Risk vs Return Analysis to better understand how to build diversified portfolios, which includes a position in GreenFirst Forest Products. 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.
GreenFirst
Beneish M Score
Market Cap
Enterprise Value
Ptb Ratio
Book Value Per Share
Free Cash Flow Yield
Operating Cash Flow Per Share
Average Payables
Capex To Depreciation
Pb Ratio
Free Cash Flow Per Share
Roic
Inventory Turnover
Net Income Per Share
Days Of Inventory On Hand
Payables Turnover
Cash Per Share
Pocfratio
Interest Coverage
Capex To Operating Cash Flow
Pfcf Ratio
Days Payables Outstanding
Income Quality
Roe
Ev To Operating Cash Flow
Pe Ratio
Return On Tangible Assets
Ev To Free Cash Flow
Earnings Yield
Net Debt To E B I T D A
Current Ratio
Tangible Book Value Per Share
Graham Number
Shareholders Equity Per Share
Debt To Equity
Capex Per Share
Graham Net Net
Average Receivables
Interest Debt Per Share
Debt To Assets
Enterprise Value Over E B I T D A
Price Earnings Ratio
Price Book Value Ratio
Price Earnings To Growth Ratio
Days Of Payables Outstanding
Price To Operating Cash Flows Ratio
Price To Free Cash Flows Ratio
Ebt Per Ebit
Effective Tax Rate
Company Equity Multiplier
Long Term Debt To Capitalization
Total Debt To Capitalization
Return On Capital Employed
Debt Equity Ratio
Quick Ratio
Dividend Paid And Capex Coverage Ratio
Net Income Per E B T
Cash Ratio
Days Of Inventory Outstanding
Free Cash Flow Operating Cash Flow Ratio
Cash Flow Coverage Ratios
Price To Book Ratio
Capital Expenditure Coverage Ratio
Price Cash Flow Ratio
Enterprise Value Multiple
Debt Ratio
Cash Flow To Debt Ratio
Return On Assets
Price Fair Value
Return On Equity
Change In Cash
Free Cash Flow
Change In Working Capital
Begin Period Cash Flow
Other Cashflows From Financing Activities
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Capital Expenditures
Total Cash From Operating Activities
Net Income
Total Cash From Financing Activities
End Period Cash Flow
Sale Purchase Of Stock
Stock Based Compensation
Change To Account Receivables
Total Cashflows From Investing Activities
Other Cashflows From Investing Activities
Investments
Net Borrowings
Change To Netincome
Change To Liabilities
Total Assets
Total Current Liabilities
Total Stockholder Equity
Property Plant And Equipment Net
Net Debt
Retained Earnings
Accounts Payable
Cash
Non Current Assets Total
Cash And Short Term Investments
Net Receivables
Common Stock Shares Outstanding
Short Term Investments
Liabilities And Stockholders Equity
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Total Current Assets
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Non Currrent Assets Other
Accumulated Other Comprehensive Income
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Common Stock
Inventory
Long Term Debt Total
Short Term Debt
Net Tangible Assets
Net Invested Capital
Long Term Investments
Capital Stock
Net Working Capital
Short Long Term Debt Total
Long Term Debt
Capital Lease Obligations
Property Plant And Equipment Gross
Property Plant Equipment
Depreciation And Amortization
Gross Profit
Other Operating Expenses
Operating Income
Ebit
Ebitda
Cost Of Revenue
Total Operating Expenses
Income Before Tax
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Income Tax Expense
Interest Expense
Selling General Administrative
Interest Income
Total Revenue
Net Income Applicable To Common Shares
Net Income From Continuing Ops
Tax Provision
Net Interest Income
Probability Of Bankruptcy
At this time, GreenFirst Forest's Net Debt is very stable compared to the past year. As of the 29th of November 2024, Long Term Debt Total is likely to grow to about 57.3 M, while Short and Long Term Debt is likely to drop about 1.5 M. At this time, GreenFirst Forest's Shareholders Equity Per Share is very stable compared to the past year.
At this time, GreenFirst Forest's M Score is inapplicable. The earnings manipulation may begin if GreenFirst Forest's top management creates an artificial sense of financial success, forcing the stock price to be traded at a high price-earnings multiple than it should be. In general, excessive earnings management by GreenFirst Forest executives may lead to removing some of the operating profits from subsequent periods to inflate earnings in the following periods. This way, the manipulation of GreenFirst Forest's earnings can lead to misrepresentations of actual financial condition, taking the otherwise loyal stakeholders on to the path of questionable ethical practices and plain fraud.
The cure to earnings manipulation is the transparency of financial reporting. It will typically remove the temptation of the top executives to inflate earnings (i.e., to promote the idea of 'winning at any cost'). Because a healthy internal audit department can enhance transparency, the board should promote the auditors' access to all the record-keeping systems across the enterprise. For example, if GreenFirst Forest'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.
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 detect the potential manipulation of earnings. Understanding the correlation between GreenFirst Forest's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards GreenFirst Forest in a much-optimized way. Analyzing correlations between earnings drivers directly associated with dollar figures is the most effective way to find GreenFirst Forest's degree of accounting gimmicks and manipulations.
M-Score is one of many grading techniques for value stocks. It was developed by Professor M. Daniel Beneish of the Kelley School of Business at Indiana University and published in 1999 under the paper titled The Detection of Earnings Manipulation. The Beneish score is a multi-factor model that utilizes financial identifiers to compile eight variables used to classify whether a company has manipulated its reported earnings. The variables are built from the officially filed financial statements to create a final score call 'M Score.' The score helps to identify companies that are likely to manipulate their profits if they show deteriorating gross margins, operating expenses, and leverage against growing revenue.
The Macroaxis Fundamental Analysis modules help investors analyze GreenFirst Forest Products's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of GreenFirst Forest using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of GreenFirst Forest Products 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.
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 GreenFirst Forest 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 GreenFirst Forest will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to GreenFirst Forest could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace GreenFirst Forest 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 GreenFirst Forest - 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 GreenFirst Forest Products to buy it.
The correlation of GreenFirst Forest 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 GreenFirst Forest moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if GreenFirst Forest 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 GreenFirst Forest 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.
Other Information on Investing in GreenFirst Stock
GreenFirst Forest financial ratios help investors to determine whether GreenFirst 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 GreenFirst with respect to the benefits of owning GreenFirst Forest security.