Data Storage Stock Technical Analysis
| DTSTW Stock | USD 0.11 0.03 17.93% |
As of the 17th of February 2026, Data Storage shows the Coefficient Of Variation of 12774.4, downside deviation of 12.4, and Mean Deviation of 6.22. Data Storage technical analysis allows you to utilize historical prices and volume patterns in order to determine a pattern that computes the direction of the firm's future prices. Please confirm Data Storage variance and potential upside to decide if Data Storage is priced favorably, providing market reflects its regular price of 0.1149 per share. As Data Storage appears to be a penny stock we also advise to verify its total risk alpha numbers.
Data Storage Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Data, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to DataData Storage's Momentum analyses are specifically helpful, as they help investors time the market using mark points where the market can reverse. The reversal spots are usually identified through divergence between price movement and momentum.What growth prospects exist in Internet Services & Infrastructure sector? Can Data capture new markets? Factors like these will boost the valuation of Data Storage. Projected growth potential of Data fundamentally drives upward valuation adjustments. Valuation analysis balances hard financial data with qualitative growth assessments. While each Data Storage valuation metric matters, prioritizing which indicators carry greater predictive weight remains essential.
Quarterly Earnings Growth 274.596 | Revenue Per Share | Quarterly Revenue Growth 0.282 | Return On Assets | Return On Equity |
The market value of Data Storage is measured differently than its book value, which is the value of Data that is recorded on the company's balance sheet. Investors also form their own opinion of Data Storage's value that differs from its market value or its book value, called intrinsic value, which is Data Storage's true underlying value. Investment professionals apply varied valuation frameworks to compute inherent worth and acquire positions when market prices trade at discounts to calculated value. Because Data Storage's market value can be influenced by many factors that don't directly affect Data Storage's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
It's important to distinguish between Data Storage's intrinsic value and market price, which are calculated using different methodologies. Investment decisions regarding Data Storage should consider multiple factors including financial performance, growth metrics, competitive position, and professional analysis. Meanwhile, Data Storage's quoted price indicates the marketplace figure where supply meets demand through bilateral consent.
Data Storage '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 Data Storage'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 Data Storage.
| 11/19/2025 |
| 02/17/2026 |
If you would invest 0.00 in Data Storage on November 19, 2025 and sell it all today you would earn a total of 0.00 from holding Data Storage or generate 0.0% return on investment in Data Storage over 90 days. Data Storage is related to or competes with Cemtrex, Alpha Modus, Youxin Technology, Infrared Cameras, LGL, Maris Tech, and Myseum. Data Storage is entity of United States. It is traded as Stock on NASDAQ exchange. More
Data Storage 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 Data Storage'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 Data Storage upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 12.4 | |||
| Information Ratio | 5.0E-4 | |||
| Maximum Drawdown | 55.48 | |||
| Value At Risk | (16.67) | |||
| Potential Upside | 19.05 |
Data Storage Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Data Storage's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Data Storage's standard deviation. In reality, there are many statistical measures that can use Data Storage historical prices to predict the future Data Storage's volatility.| Risk Adjusted Performance | 0.0155 | |||
| Jensen Alpha | 0.0618 | |||
| Total Risk Alpha | (0.64) | |||
| Sortino Ratio | 4.0E-4 | |||
| Treynor Ratio | 1.47 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Data Storage'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.
Data Storage February 17, 2026 Technical Indicators
| Cycle Indicators | ||
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| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0155 | |||
| Market Risk Adjusted Performance | 1.48 | |||
| Mean Deviation | 6.22 | |||
| Semi Deviation | 8.14 | |||
| Downside Deviation | 12.4 | |||
| Coefficient Of Variation | 12774.4 | |||
| Standard Deviation | 9.51 | |||
| Variance | 90.44 | |||
| Information Ratio | 5.0E-4 | |||
| Jensen Alpha | 0.0618 | |||
| Total Risk Alpha | (0.64) | |||
| Sortino Ratio | 4.0E-4 | |||
| Treynor Ratio | 1.47 | |||
| Maximum Drawdown | 55.48 | |||
| Value At Risk | (16.67) | |||
| Potential Upside | 19.05 | |||
| Downside Variance | 153.78 | |||
| Semi Variance | 66.33 | |||
| Expected Short fall | (9.85) | |||
| Skewness | (0.03) | |||
| Kurtosis | 1.84 |
Data Storage Backtested Returns
Data Storage secures Sharpe Ratio (or Efficiency) of -0.13, which denotes the company had a -0.13 % return per unit of risk over the last 3 months. Data Storage exposes twenty-nine different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Data Storage's Coefficient Of Variation of 12774.4, downside deviation of 12.4, and Mean Deviation of 6.22 to check the risk estimate we provide. The firm shows a Beta (market volatility) of 0.0439, which means not very significant fluctuations relative to the market. As returns on the market increase, Data Storage's returns are expected to increase less than the market. However, during the bear market, the loss of holding Data Storage is expected to be smaller as well. At this point, Data Storage has a negative expected return of -1.08%. Please make sure to confirm Data Storage's potential upside, as well as the relationship between the accumulation distribution and price action indicator , to decide if Data Storage performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.38 |
Poor reverse predictability
Data Storage has poor reverse predictability. Overlapping area represents the amount of predictability between Data Storage time series from 19th of November 2025 to 3rd of January 2026 and 3rd of January 2026 to 17th 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 Data Storage price movement. The serial correlation of -0.38 indicates that just about 38.0% of current Data Storage price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.38 | |
| Spearman Rank Test | -0.47 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Data Storage 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.
Data Storage Technical Analysis
The output start index for this execution was one with a total number of output elements of sixty. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Data Storage volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Data Storage Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Data Storage on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Data Storage based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Data Storage price pattern first instead of the macroeconomic environment surrounding Data Storage. By analyzing Data Storage's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Data Storage's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Data Storage specific price patterns or momentum indicators. Please read more on our technical analysis page.
| 2025 | 2026 (projected) | Payables Turnover | 4.03 | 3.34 | Days Of Inventory On Hand | 14.45 | 20.24 |
Data Storage February 17, 2026 Technical Indicators
Most technical analysis of Data help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Data from various momentum indicators to cycle indicators. When you analyze Data charts, please remember that the event formation may indicate an entry point for a short seller, and look at different other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0155 | |||
| Market Risk Adjusted Performance | 1.48 | |||
| Mean Deviation | 6.22 | |||
| Semi Deviation | 8.14 | |||
| Downside Deviation | 12.4 | |||
| Coefficient Of Variation | 12774.4 | |||
| Standard Deviation | 9.51 | |||
| Variance | 90.44 | |||
| Information Ratio | 5.0E-4 | |||
| Jensen Alpha | 0.0618 | |||
| Total Risk Alpha | (0.64) | |||
| Sortino Ratio | 4.0E-4 | |||
| Treynor Ratio | 1.47 | |||
| Maximum Drawdown | 55.48 | |||
| Value At Risk | (16.67) | |||
| Potential Upside | 19.05 | |||
| Downside Variance | 153.78 | |||
| Semi Variance | 66.33 | |||
| Expected Short fall | (9.85) | |||
| Skewness | (0.03) | |||
| Kurtosis | 1.84 |
Data Storage February 17, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Data stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 0.31 | ||
| Daily Balance Of Power | (0.57) | ||
| Rate Of Daily Change | 0.82 | ||
| Day Median Price | 0.12 | ||
| Day Typical Price | 0.12 | ||
| Price Action Indicator | (0.02) | ||
| Market Facilitation Index | 0.04 |
Additional Tools for Data Stock Analysis
When running Data Storage's price analysis, check to measure Data Storage'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 Data Storage is operating at the current time. Most of Data Storage's value examination focuses on studying past and present price action to predict the probability of Data Storage's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Data Storage's price. Additionally, you may evaluate how the addition of Data Storage to your portfolios can decrease your overall portfolio volatility.