Hyperscale Data, Stock Price To Earning
| GPUS Stock | 6.36 0.54 9.28% |
Hyperscale Data, fundamentals help investors to digest information that contributes to Hyperscale Data,'s financial success or failures. It also enables traders to predict the movement of Hyperscale Stock. The fundamental analysis module provides a way to measure Hyperscale Data,'s intrinsic value by examining its available economic and financial indicators, including the cash flow records, the balance sheet account changes, the income statement patterns, and various microeconomic indicators and financial ratios related to Hyperscale Data, stock.
Hyperscale | Price To Earning |
Hyperscale Data, Company Price To Earning Analysis
Hyperscale Data,'s Price to Earnings ratio is typically used for current valuation of a company and is one of the most popular ratios that investors monitor daily. Holding a low PE stock is less risky because when a company's profitability falls, it is likely that earnings will also go down as well. In other words, if you start from a lower position, your downside risk is limited. There are also some investors who believe that low Price to Earnings ratio reflects the low pricing because a given company is in trouble. On the other hand, a higher PE ratio means that investors are paying more for each unit of profit.
Hyperscale Price To Earning Driver Correlations
Understanding the fundamental principles of building solid financial models for Hyperscale Data, is extremely important. It helps to project a fair market value of Hyperscale Stock properly, considering its historical fundamentals such as Price To Earning. Since Hyperscale Data,'s main accounts across its financial reports are all linked and dependent on each other, it is essential to analyze all possible correlations between related accounts. However, instead of reviewing all of Hyperscale Data,'s historical financial statements, investors can examine the correlated drivers to determine its overall health. This can be effectively done using a conventional correlation matrix of Hyperscale Data,'s interrelated accounts and indicators.
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Generally speaking, the Price to Earnings ratio gives investors an idea of what the market is willing to pay for the company's current earnings.
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Hyperscale Retained Earnings
Retained Earnings |
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Based on the latest financial disclosure, Hyperscale Data, has a Price To Earning of 0.0 times. This is 100.0% lower than that of the Internet Software & Services (discontinued effective close of September 28, 2018) sector and 100.0% lower than that of the Information Technology industry. The price to earning for all United States stocks is 100.0% higher than that of the company.
Hyperscale Price To Earning Peer Comparison
Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Hyperscale Data,'s direct or indirect competition against its Price To Earning to detect undervalued stocks with similar characteristics or determine the stocks which would be a good addition to a portfolio. Peer analysis of Hyperscale Data, could also be used in its relative valuation, which is a method of valuing Hyperscale Data, by comparing valuation metrics of similar companies.Hyperscale Data, is currently under evaluation in price to earning category among its peers.
Hyperscale Fundamentals
| Return On Equity | -2.09 | ||||
| Return On Asset | -0.12 | ||||
| Profit Margin | (0.99) % | ||||
| Operating Margin | (0.67) % | ||||
| Current Valuation | 131.57 M | ||||
| Shares Outstanding | 38.85 M | ||||
| Shares Owned By Insiders | 0.10 % | ||||
| Shares Owned By Institutions | 1.81 % | ||||
| Number Of Shares Shorted | 1.25 M | ||||
| Price To Book | 0.31 X | ||||
| Price To Sales | 0.05 X | ||||
| Revenue | 156.44 M | ||||
| EBITDA | (38.33 M) | ||||
| Net Income | (231.03 M) | ||||
| Total Debt | 27 M | ||||
| Book Value Per Share | 0.74 X | ||||
| Cash Flow From Operations | (5.43 M) | ||||
| Short Ratio | 1.03 X | ||||
| Earnings Per Share | 1,982 X | ||||
| Number Of Employees | 587 | ||||
| Beta | 3.44 | ||||
| Market Capitalization | 8.36 M | ||||
| Total Asset | 299.19 M | ||||
| Retained Earnings | (567.47 M) | ||||
| Working Capital | (66.34 M) | ||||
| Net Asset | 299.19 M |
About Hyperscale Data, Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Hyperscale Data,'s financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Hyperscale Data, using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Hyperscale Data, 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.
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Additional Tools for Hyperscale Stock Analysis
When running Hyperscale Data,'s price analysis, check to measure Hyperscale Data,'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 Hyperscale Data, is operating at the current time. Most of Hyperscale Data,'s value examination focuses on studying past and present price action to predict the probability of Hyperscale Data,'s future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Hyperscale Data,'s price. Additionally, you may evaluate how the addition of Hyperscale Data, to your portfolios can decrease your overall portfolio volatility.