Hyperscale Ebit from 2010 to 2026

GPUS Stock   0.24  0.06  30.69%   
Hyperscale Data EBIT yearly trend continues to be comparatively stable with very little volatility. EBIT is likely to outpace its year average in 2026. From the period from 2010 to 2026, Hyperscale Data EBIT quarterly data regression had mean square error of 2363 T and mean deviation of  36,483,252. View All Fundamentals
 
EBIT  
First Reported
1997-06-30
Previous Quarter
-10.2 M
Current Value
-10.3 M
Quarterly Volatility
17.7 M
 
Dot-com Bubble
 
Housing Crash
 
Credit Downgrade
 
Yuan Drop
 
Covid
Check Hyperscale Data financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Hyperscale Data's main balance sheet or income statement drivers, such as Depreciation And Amortization of 31.6 M, Interest Expense of 23.8 M or Total Revenue of 128.8 M, as well as many indicators such as Price To Sales Ratio of 0.0539, Dividend Yield of 0.95 or PTB Ratio of 0.67. Hyperscale financial statements analysis is a perfect complement when working with Hyperscale Data Valuation or Volatility modules.
  
Build AI portfolio with Hyperscale Stock
Check out the analysis of Hyperscale Data Correlation against competitors.
For more information on how to buy Hyperscale Stock please use our How to Invest in Hyperscale Data guide.

Latest Hyperscale Data's Ebit Growth Pattern

Below is the plot of the Ebit of Hyperscale Data over the last few years. It is Hyperscale Data's EBIT 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.
Ebit10 Years Trend
Slightly volatile
   Ebit   
       Timeline  

Hyperscale Ebit Regression Statistics

Arithmetic Mean(33,167,817)
Coefficient Of Variation(171.94)
Mean Deviation36,483,252
Median(16,868,524)
Standard Deviation57,029,708
Sample Variance3252.4T
Range205M
R-Value(0.56)
Mean Square Error2363T
R-Squared0.32
Significance0.02
Slope(6,377,321)
Total Sum of Squares52038.2T

Hyperscale Ebit History

2026-37.8 M
2025-39.8 M
2024-44.2 M
2023-203 M
2022-151.1 M
2021-21 M
2020-20.5 M

Other Fundumenentals of Hyperscale Data

About Hyperscale Data Financial Statements

Hyperscale Data shareholders use historical fundamental indicators, such as Ebit, to determine how well the company is positioned to perform in the future. Although Hyperscale Data investors may analyze each financial statement separately, they are all interrelated. The changes in Hyperscale Data's assets and liabilities, for example, are also reflected in the revenues and expenses on on Hyperscale Data's income statement. Understanding these patterns can help investors time the market effectively. Please read more on our fundamental analysis page.
Last ReportedProjected for Next Year
EBIT-39.8 M-37.8 M
EBITDA-16.3 M-17.1 M
Ebt Per Ebit 0.97  1.10 
Ebit Per Revenue(0.61)(0.58)

Thematic Opportunities

Explore Investment Opportunities

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
Explore Investing Ideas  

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.