Hyperscale Data, Stock Price History

GPUS Stock   3.17  0.17  5.09%   
Below is the normalized historical share price chart for Hyperscale Data, extending back to December 17, 1996. This chart has been adjusted for all splits and dividends and is plotted against all major global economic recessions. As of today, the current price of Hyperscale Data, stands at 3.17, as last reported on the 1st of March, with the highest price reaching 3.40 and the lowest price hitting 3.11 during the day.
200 Day MA
0.5978
50 Day MA
0.243
Beta
3.436
 
Dot-com Bubble
 
Housing Crash
 
Credit Downgrade
 
Yuan Drop
 
Covid
If you're considering investing in Hyperscale Stock, it is important to understand the factors that can impact its price. Hyperscale Data, holds Efficiency (Sharpe) Ratio of -0.057, which attests that the entity had a -0.057 % return per unit of risk over the last 3 months. Hyperscale Data, exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Hyperscale Data,'s Risk Adjusted Performance of (0.04), market risk adjusted performance of (0.36), and Standard Deviation of 8.94 to validate the risk estimate we provide.
  
Common Stock Shares Outstanding is likely to gain to about 5.4 M in 2025, whereas Total Stockholder Equity is likely to drop slightly above 38.2 M in 2025. . Hyperscale Stock price history is provided at the adjusted basis, taking into account all of the recent filings.

Sharpe Ratio = -0.057

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Estimated Market Risk

 9.07
  actual daily
80
80% of assets are less volatile

Expected Return

 -0.52
  actual daily
0
Most of other assets have higher returns

Risk-Adjusted Return

 -0.06
  actual daily
0
Most of other assets perform better
Based on monthly moving average Hyperscale Data, is not performing at its full potential. However, if added to a well diversified portfolio the total return can be enhanced and market risk can be reduced. You can increase risk-adjusted return of Hyperscale Data, by adding Hyperscale Data, to a well-diversified portfolio.
Price Book
0.313
Enterprise Value Ebitda
(3.32)
Price Sales
0.0542
Shares Float
38.8 M
Earnings Share
K

Hyperscale Data, Stock Price History Chart

There are several ways to analyze Hyperscale Stock price data. The simplest method is using a basic Hyperscale candlestick price chart, which shows Hyperscale Data, price history and the buying and selling dynamics of a specified period. Many traders also use subjective judgment to their trading calls, avoiding the need to trade based on technical analysis.
Highest PriceDecember 10, 20247.1
Lowest PriceFebruary 21, 20253.1

Hyperscale Data, March 1, 2025 Stock Price Synopsis

Various analyses of Hyperscale Data,'s daily price changes, such as its Balance Of Power or Price Action, are crucial when deciding whether to buy, hold, or sell Hyperscale Stock. It can be used to describe the percentage change in the price of Hyperscale Data, from one trading day to the next and could be a valuable metric for traders and investors to gauge the volatility and momentum of Hyperscale Stock.
Hyperscale Data, Price Action Indicator(0.17)
Hyperscale Data, Price Rate Of Daily Change 0.95 
Hyperscale Data, Price Daily Balance Of Power(0.59)

Hyperscale Data, March 1, 2025 Stock Price Analysis

When benchmark price declines in a down market, there may be an uptick in Hyperscale Stock price where buyers come in believing the asset is cheap or selling overdone. The opposite is true when the market is bullish. You can use Hyperscale Data, intraday prices and daily technical indicators to check the level of noise trading in Hyperscale Stock and then apply it to test your longer-term investment strategies against Hyperscale.

Hyperscale Stock Price History Data

The price series of Hyperscale Data, for the period between Sun, Dec 1, 2024 and Sat, Mar 1, 2025 has a statistical range of 4.0 with a coefficient of variation of 24.59. Under current investment horizon, the daily prices are spread out with arithmetic mean of 4.84. The median price for the last 90 days is 4.98. The company completed 1024:1000 stock split on 12th of April 2024. Hyperscale Data, completed dividends distribution on 2019-08-06.
OpenHighLowCloseVolume
03/01/2025
 3.40  3.40  3.11  3.17 
02/27/2025 3.40  3.40  3.11  3.17  23,118 
02/26/2025 3.25  3.45  3.25  3.34  24,574 
02/25/2025 3.68  3.68  3.12  3.28  33,200 
02/24/2025 3.08  3.71  2.96  3.57  89,307 
02/21/2025 3.13  3.26  3.01  3.10  34,982 
02/20/2025 3.12  3.21  2.89  3.15  62,676 
02/19/2025 3.60  3.67  2.62  3.13  1,115,671 
02/18/2025 3.48  3.54  3.26  3.26  18,300 
02/14/2025 3.53  3.62  3.31  3.40  28,800 
02/13/2025 3.70  3.70  3.51  3.51  14,797 
02/12/2025 3.62  3.80  3.60  3.62  13,579 
02/11/2025 3.97  3.97  3.62  3.62  21,999 
02/10/2025 3.69  4.00  3.69  3.80  36,483 
02/07/2025 4.41  4.41  3.61  3.66  28,535 
02/06/2025 4.03  4.13  3.80  3.80  16,336 
02/05/2025 4.23  4.23  3.95  3.95  12,302 
02/04/2025 3.80  4.16  3.80  3.93  38,745 
02/03/2025 3.98  4.08  3.82  3.84  53,538 
01/31/2025 4.25  4.41  4.10  4.15  17,238 
01/30/2025 4.28  4.49  3.94  4.35  92,600 
01/29/2025 4.23  4.57  4.23  4.23  12,800 
01/28/2025 4.49  4.49  4.14  4.19  21,000 
01/27/2025 4.76  4.86  4.26  4.40  46,900 
01/24/2025 4.78  5.12  4.75  5.06  25,000 
01/23/2025 5.20  5.55  4.78  4.86  57,300 
01/22/2025 4.75  5.24  4.56  5.24  66,600 
01/21/2025 4.78  4.99  4.43  4.54  84,400 
01/17/2025 3.74  4.80  3.60  4.70  215,800 
01/16/2025 3.60  3.92  3.45  3.74  44,500 
01/15/2025 3.27  3.60  3.14  3.60  77,500 
01/14/2025 3.36  3.50  3.09  3.17  78,700 
01/13/2025 4.18  4.28  3.12  3.16  177,300 
01/10/2025 4.56  4.56  4.10  4.18  43,300 
01/08/2025 5.63  5.69  4.07  4.25  138,600 
01/07/2025 5.77  6.48  5.41  5.46  288,316 
01/06/2025 5.85  6.08  5.51  5.74  166,977 
01/03/2025 5.19  5.47  5.01  5.46  50,200 
01/02/2025 4.95  5.04  4.79  5.02  63,100 
12/31/2024 5.19  5.27  4.84  4.86  47,700 
12/30/2024 5.22  5.45  4.78  5.14  49,100 
12/27/2024 5.49  5.50  5.11  5.38  51,800 
12/26/2024 5.58  5.73  5.31  5.43  90,300 
12/24/2024 5.44  5.55  5.00  5.30  16,200 
12/23/2024 5.35  5.64  5.20  5.36  40,300 
12/20/2024 5.36  5.78  5.28  5.38  43,000 
12/19/2024 5.76  6.25  5.35  5.35  83,600 
12/18/2024 5.79  6.24  5.79  5.81  28,700 
12/17/2024 6.35  6.69  5.71  5.92  77,900 
12/16/2024 7.00  7.10  6.30  6.48  80,300 
12/13/2024 6.72  6.97  6.57  6.87  28,400 
12/12/2024 6.83  7.00  6.56  6.68  28,900 
12/11/2024 7.00  7.07  6.80  6.85  23,300 
12/10/2024 6.64  7.81  6.43  7.10  94,500 
12/09/2024 6.77  6.80  6.36  6.63  79,500 
12/06/2024 6.16  7.14  5.55  6.77  649,800 
12/05/2024 5.46  5.62  4.98  4.98  39,600 
12/04/2024 5.89  5.89  5.25  5.34  66,000 
12/03/2024 5.49  5.95  5.40  5.76  53,100 
12/02/2024 5.99  5.99  5.28  5.47  86,700 
11/29/2024 6.76  6.88  5.77  5.96  61,200 

About Hyperscale Data, Stock history

Hyperscale Data, investors dedicate a lot of time and effort to gaining insight into how a market's past behavior relates to its future. Access to timely market data for Hyperscale is vital when making an investment decision, and regardless of whether you use fundamental or technical analysis, your return on investment in Hyperscale Data, will depend on recognizing future opportunities and eliminating past mistakes. Historical data analysis is the study of market behavior over a given time. Recorded market-related data such as price, volatility, and volume can be quantified and studied over a defined period. Through a detailed examination of a market's past behavior, traders and investors can gain perspective on the inner workings of that market. The information obtained throughout analyzing Hyperscale Data, stock prices may prove useful in developing a viable investing in Hyperscale Data,
Last ReportedProjected for Next Year
Common Stock Shares Outstanding5.2 M5.4 M

Hyperscale Data, Stock Technical Analysis

Hyperscale Data, technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.
A focus of Hyperscale Data, technical analysis is to determine if market prices reflect all relevant information impacting that market. A technical analyst looks at the history of Hyperscale Data, trading pattern rather than external drivers such as economic, fundamental, or social events. It is believed that price action tends to repeat itself due to investors' collective, patterned behavior. Hence technical analysis focuses on identifiable price trends and conditions. More Info...

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Hyperscale Data, Technical and Predictive Indicators

Predictive indicators are helping investors to find signals for Hyperscale Data,'s price direction in advance. Along with the technical and fundamental analysis of Hyperscale Stock historical price patterns, it is also worthwhile for investors to track various predictive indicators of Hyperscale to make sure they correctly time the market and exploit it's hidden potentials. Even though most predictive indicators are useful for the short-term horizon, it's virtually impossible to predict the unforeseen market. For traders with a short-term horizon, predictive indicators add value when properly applied. Long-term investors, however, may find many predictive indicators less useful.

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.