This module uses fundamental data of Aurora Innovation to approximate its Piotroski F score. Aurora Innovation F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Aurora Innovation. 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 Aurora Innovation financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Aurora Innovation Altman Z Score, Aurora Innovation Correlation, Aurora Innovation Valuation, as well as analyze Aurora Innovation Alpha and Beta and Aurora Innovation Hype Analysis.
As of 11/22/2024, Short and Long Term Debt Total is likely to drop to about 114.8 M. In addition to that, Net Debt is likely to drop to about (397.9 M). At this time, Aurora Innovation's PTB Ratio is relatively stable compared to the past year. As of 11/22/2024, PB Ratio is likely to grow to 3.07, while Book Value Per Share is likely to drop 1.02.
At this time, it appears that Aurora Innovation's Piotroski F Score is Poor. 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 Aurora Innovation is to make sure Aurora is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Aurora Innovation'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 Aurora Innovation'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 Aurora Innovation's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Aurora Innovation 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.
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, Aurora Innovation's sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Aurora Innovation's managers, analysts, and investors.
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About Aurora Innovation Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Aurora Innovation's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Aurora Innovation using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Aurora Innovation 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 Aurora Innovation 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 Aurora Innovation will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Aurora Innovation could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Aurora Innovation 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 Aurora Innovation - 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 Aurora Innovation to buy it.
The correlation of Aurora Innovation 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 Aurora Innovation moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Aurora Innovation 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 Aurora Innovation 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.
When running Aurora Innovation's price analysis, check to measure Aurora Innovation'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 Aurora Innovation is operating at the current time. Most of Aurora Innovation's value examination focuses on studying past and present price action to predict the probability of Aurora Innovation's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Aurora Innovation's price. Additionally, you may evaluate how the addition of Aurora Innovation to your portfolios can decrease your overall portfolio volatility.