Hyperscale Data Net Income
| GPUS Stock | 0.19 0.01 5.56% |
As of the 19th of February, Hyperscale Data retains the Standard Deviation of 10.69, risk adjusted performance of (0.02), and Market Risk Adjusted Performance of (0.10). Hyperscale Data technical analysis makes it possible for you to employ historical prices and volume momentum with the intention to determine a pattern that calculates the direction of the firm's future prices. Please check out Hyperscale Data information ratio and kurtosis to decide if Hyperscale Data is priced fairly, providing market reflects its last-minute price of 0.19 per share. As Hyperscale Data appears to be a penny stock we also urge to confirm its jensen alpha numbers.
Hyperscale Data Total Revenue |
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Gross Profit | Profit Margin | Market Capitalization | Enterprise Value Revenue 1.2212 | Revenue |
| Last Reported | Projected for Next Year | ||
| Net Loss | -55.6 M | -52.8 M | |
| Net Loss | -55.6 M | -58.4 M | |
| Net Loss | (59.69) | (62.67) | |
| Net Income Per E B T | 0.82 | 0.66 |
Hyperscale | Net Income | Build AI portfolio with Hyperscale Stock |
The evolution of Net Income for Hyperscale Data provides essential context for understanding the company's financial health trajectory. By analyzing this metric's behavior over time, investors can assess whether recent trends align with long-term patterns, and how Hyperscale Data compares to historical norms and industry peers.
Latest Hyperscale Data's Net Income Growth Pattern
Below is the plot of the Net Income of Hyperscale Data over the last few years. Net income is one of the most important fundamental items in finance. It plays a large role in Hyperscale Data financial statement analysis. It represents the amount of money remaining after all of Hyperscale Data operating expenses, interest, taxes and preferred stock dividends have been deducted from a company total revenue. It is Hyperscale Data's Net Loss historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in Hyperscale Data's overall financial position and show how it may be relating to other accounts over time.
| View | Last Reported (61.76 M) | 10 Years Trend |
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Net Income |
| Timeline |
Hyperscale Net Income Regression Statistics
| Arithmetic Mean | (41,036,856) | |
| Coefficient Of Variation | (160.58) | |
| Mean Deviation | 42,647,029 | |
| Median | (23,251,000) | |
| Standard Deviation | 65,895,497 | |
| Sample Variance | 4342.2T | |
| Range | 232.2M | |
| R-Value | (0.58) | |
| Mean Square Error | 3048T | |
| R-Squared | 0.34 | |
| Significance | 0.01 | |
| Slope | (7,630,365) | |
| Total Sum of Squares | 69475.5T |
Hyperscale Net Income History
Other Fundumenentals of Hyperscale Data
Hyperscale Data Net Income component correlations
Hyperscale Net Income 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 Net Income. 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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Is there potential for Industrial Conglomerates market expansion? Will Hyperscale introduce new products? Factors like these will boost the valuation of Hyperscale Data. Market participants price Hyperscale higher when confident in its future expansion prospects. Understanding fair value requires weighing current performance against future potential. All the valuation information about Hyperscale Data listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share (28.33) | Revenue Per Share | Quarterly Revenue Growth 0.453 | Return On Assets | Return On Equity |
Hyperscale Data's market price often diverges from its book value, the accounting figure shown on Hyperscale's balance sheet. Smart investors calculate Hyperscale Data's intrinsic value - its true economic worth - which may differ significantly from both market price and book value. Analysts utilize numerous techniques to assess fundamental value, seeking to purchase shares when trading prices fall beneath estimated intrinsic worth. Since Hyperscale Data's trading price responds to investor sentiment, macroeconomic conditions, and market psychology, it can swing far from fundamental value.
Please note, there is a significant difference between Hyperscale Data's value and its price as these two are different measures arrived at by different means. Investors typically determine if Hyperscale Data is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Hyperscale Data's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
Hyperscale Data 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Hyperscale Data's stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Hyperscale Data.
| 11/21/2025 |
| 02/19/2026 |
If you would invest 0.00 in Hyperscale Data on November 21, 2025 and sell it all today you would earn a total of 0.00 from holding Hyperscale Data or generate 0.0% return on investment in Hyperscale Data over 90 days. Hyperscale Data is related to or competes with SIFCO Industries, Ads Tec, Sky Harbour, Sidus Space, Ideal Power, BG Staffing, and Magnitude International. Hyperscale Data is entity of United States More
Hyperscale Data Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Hyperscale Data's stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Hyperscale Data upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.04) | |||
| Maximum Drawdown | 62.5 | |||
| Value At Risk | (11.54) | |||
| Potential Upside | 16.67 |
Hyperscale Data Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Hyperscale Data's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Hyperscale Data's standard deviation. In reality, there are many statistical measures that can use Hyperscale Data historical prices to predict the future Hyperscale Data's volatility.| Risk Adjusted Performance | (0.02) | |||
| Jensen Alpha | (0.53) | |||
| Total Risk Alpha | (0.89) | |||
| Treynor Ratio | (0.11) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Hyperscale Data's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hyperscale Data February 19, 2026 Technical Indicators
| Cycle Indicators | ||
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| Math Transform | ||
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| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
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| Volume Indicators |
| Risk Adjusted Performance | (0.02) | |||
| Market Risk Adjusted Performance | (0.10) | |||
| Mean Deviation | 6.77 | |||
| Coefficient Of Variation | (2,780) | |||
| Standard Deviation | 10.69 | |||
| Variance | 114.37 | |||
| Information Ratio | (0.04) | |||
| Jensen Alpha | (0.53) | |||
| Total Risk Alpha | (0.89) | |||
| Treynor Ratio | (0.11) | |||
| Maximum Drawdown | 62.5 | |||
| Value At Risk | (11.54) | |||
| Potential Upside | 16.67 | |||
| Skewness | 2.48 | |||
| Kurtosis | 8.8 |
Hyperscale Data Backtested Returns
Currently, Hyperscale Data is out of control. Hyperscale Data holds Efficiency (Sharpe) Ratio of close to zero, which attests that the entity had a close to zero % return per unit of risk over the last 3 months. We have found twenty-two technical indicators for Hyperscale Data, which you can use to evaluate the volatility of the firm. Please check out Hyperscale Data's Risk Adjusted Performance of (0.02), market risk adjusted performance of (0.10), and Standard Deviation of 10.69 to validate if the risk estimate we provide is consistent with the expected return of 0.0194%. The company retains a Market Volatility (i.e., Beta) of 3.58, which attests to a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Hyperscale Data will likely underperform. Hyperscale Data right now retains a risk of 10.67%. Please check out Hyperscale Data jensen alpha, kurtosis, as well as the relationship between the Kurtosis and period momentum indicator , to decide if Hyperscale Data will be following its current trending patterns.
Auto-correlation | 0.77 |
Good predictability
Hyperscale Data has good predictability. Overlapping area represents the amount of predictability between Hyperscale Data time series from 21st of November 2025 to 5th of January 2026 and 5th of January 2026 to 19th of February 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Hyperscale Data price movement. The serial correlation of 0.77 indicates that around 77.0% of current Hyperscale Data price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.77 | |
| Spearman Rank Test | 0.73 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Because income is reported on the Income Statement of a company and is measured in dollars some investors prefer to use Profit Margin, which measures income as a percentage of sales.
| Competition |
Hyperscale Accumulated Other Comprehensive Income
Accumulated Other Comprehensive Income |
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Based on the recorded statements, Hyperscale Data reported net income of (61.76 Million). This is 123.8% lower than that of the Industrial Conglomerates sector and 105.58% lower than that of the Industrials industry. The net income for all United States stocks is 110.82% higher than that of the company.
Hyperscale Net Income 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 Net Income 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 net income category among its peers.
Hyperscale Fundamentals
| Return On Equity | -3.33 | ||||
| Return On Asset | -0.0882 | ||||
| Profit Margin | (0.49) % | ||||
| Operating Margin | (0.39) % | ||||
| Current Valuation | 115.58 M | ||||
| Shares Outstanding | 323.83 M | ||||
| Shares Owned By Insiders | 0.01 % | ||||
| Shares Owned By Institutions | 0.19 % | ||||
| Number Of Shares Shorted | 20.08 M | ||||
| Price To Book | 1.24 X | ||||
| Price To Sales | 0.73 X | ||||
| Revenue | 106.66 M | ||||
| Gross Profit | 24.3 M | ||||
| EBITDA | (18.07 M) | ||||
| Net Income | (61.76 M) | ||||
| Total Debt | 120.3 M | ||||
| Book Value Per Share | 0.40 X | ||||
| Cash Flow From Operations | (19.41 M) | ||||
| Short Ratio | 0.16 X | ||||
| Earnings Per Share | (28.33) X | ||||
| Number Of Employees | 374 | ||||
| Beta | 2.53 | ||||
| Market Capitalization | 99.5 M | ||||
| Total Asset | 220.77 M | ||||
| Retained Earnings | (628.95 M) | ||||
| Working Capital | (157.09 M) | ||||
| Net Asset | 220.77 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.