This module uses fundamental data of Amotiv to approximate its Piotroski F score. Amotiv F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Amotiv Limited. 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 Amotiv financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Trending Equities to better understand how to build diversified portfolios, which includes a position in Amotiv Limited. 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.
Amotiv
Piotroski F Score
Sale Purchase Of Stock
Change To Inventory
Investments
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Stock Based Compensation
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Total Cash From Financing Activities
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Net Income Applicable To Common Shares
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Interest Income
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Reconciled Depreciation
Probability Of Bankruptcy
At this time, Amotiv's Net Debt is very stable compared to the past year. As of the 23rd of December 2024, Long Term Debt Total is likely to grow to about 69.4 M, while Short Term Debt is likely to drop about 17.3 M.
At this time, it appears that Amotiv'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..
The critical factor to consider when applying the Piotroski F Score to Amotiv is to make sure Amotiv is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Amotiv'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 Amotiv's financial numbers are properly reported.
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 Amotiv's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Amotiv in a much-optimized way.
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.
Net Debt
3.26 Million
At this time, Amotiv's Net Debt is very stable compared to the past year.
About Amotiv Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Amotiv Limited's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Amotiv using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Amotiv Limited 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 Amotiv 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 Amotiv will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Amotiv could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Amotiv 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 Amotiv - 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 Amotiv Limited to buy it.
The correlation of Amotiv 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 Amotiv moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Amotiv Limited 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 Amotiv 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.
Amotiv financial ratios help investors to determine whether Amotiv 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 Amotiv with respect to the benefits of owning Amotiv security.