Datavault Ai Stock Technical Analysis
| DVLT Stock | 0.82 0.08 8.89% |
As of the 24th of January, Datavault shows the Mean Deviation of 10.58, variance of 251.8, and Standard Deviation of 15.87. Datavault AI 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.
Datavault Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Datavault, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to DatavaultDatavault | Build AI portfolio with Datavault Stock |
Is IT Consulting & Other Services space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Datavault. If investors know Datavault will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Datavault listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share (10.97) | Revenue Per Share | Quarterly Revenue Growth 1.467 | Return On Assets | Return On Equity |
The market value of Datavault AI is measured differently than its book value, which is the value of Datavault that is recorded on the company's balance sheet. Investors also form their own opinion of Datavault's value that differs from its market value or its book value, called intrinsic value, which is Datavault's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Datavault's market value can be influenced by many factors that don't directly affect Datavault's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Datavault's value and its price as these two are different measures arrived at by different means. Investors typically determine if Datavault is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Datavault'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.
Datavault '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 Datavault'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 Datavault.
| 10/26/2025 |
| 01/24/2026 |
If you would invest 0.00 in Datavault on October 26, 2025 and sell it all today you would earn a total of 0.00 from holding Datavault AI or generate 0.0% return on investment in Datavault over 90 days. Datavault is related to or competes with Digimarc, TTEC Holdings, Arrive AI, Lantronix, Tucows, Zepp Health, and Unisys. Datavault is entity of United States. It is traded as Stock on NASDAQ exchange. More
Datavault 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 Datavault'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 Datavault AI upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.04) | |||
| Maximum Drawdown | 72.53 | |||
| Value At Risk | (17.34) | |||
| Potential Upside | 42.57 |
Datavault Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Datavault's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Datavault's standard deviation. In reality, there are many statistical measures that can use Datavault historical prices to predict the future Datavault's volatility.| Risk Adjusted Performance | (0.02) | |||
| Jensen Alpha | (1.00) | |||
| Total Risk Alpha | (2.06) | |||
| Treynor Ratio | (0.09) |
Datavault January 24, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | (0.02) | |||
| Market Risk Adjusted Performance | (0.08) | |||
| Mean Deviation | 10.58 | |||
| Coefficient Of Variation | (2,803) | |||
| Standard Deviation | 15.87 | |||
| Variance | 251.8 | |||
| Information Ratio | (0.04) | |||
| Jensen Alpha | (1.00) | |||
| Total Risk Alpha | (2.06) | |||
| Treynor Ratio | (0.09) | |||
| Maximum Drawdown | 72.53 | |||
| Value At Risk | (17.34) | |||
| Potential Upside | 42.57 | |||
| Skewness | 2.01 | |||
| Kurtosis | 4.25 |
Datavault AI Backtested Returns
Datavault AI secures Sharpe Ratio (or Efficiency) of -0.0876, which denotes the company had a -0.0876 % return per unit of risk over the last 3 months. Datavault AI exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Datavault's Standard Deviation of 15.87, variance of 251.8, and Mean Deviation of 10.58 to check the risk estimate we provide. The firm shows a Beta (market volatility) of 6.18, which means 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, Datavault will likely underperform. At this point, Datavault AI has a negative expected return of -1.3%. Please make sure to confirm Datavault's total risk alpha, accumulation distribution, as well as the relationship between the Accumulation Distribution and period momentum indicator , to decide if Datavault AI performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.52 |
Modest predictability
Datavault AI has modest predictability. Overlapping area represents the amount of predictability between Datavault time series from 26th of October 2025 to 10th of December 2025 and 10th of December 2025 to 24th of January 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 Datavault AI price movement. The serial correlation of 0.52 indicates that about 52.0% of current Datavault price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.52 | |
| Spearman Rank Test | 0.15 | |
| Residual Average | 0.0 | |
| Price Variance | 0.08 |
Datavault 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.
Datavault AI Technical Analysis
The output start index for this execution was thirty-six with a total number of output elements of twenty-five. 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 Datavault AI volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Datavault 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 Datavault AI 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 Datavault AI based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Datavault AI price pattern first instead of the macroeconomic environment surrounding Datavault AI. By analyzing Datavault'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 Datavault'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 Datavault specific price patterns or momentum indicators. Please read more on our technical analysis page.
| 2023 | 2024 | 2025 | 2026 (projected) | Payables Turnover | 2.39 | 0.83 | 0.95 | 0.9 | Days Of Inventory On Hand | 180.33 | 256.99 | 295.54 | 479.42 |
Datavault January 24, 2026 Technical Indicators
Most technical analysis of Datavault 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 Datavault from various momentum indicators to cycle indicators. When you analyze Datavault 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 | (0.02) | |||
| Market Risk Adjusted Performance | (0.08) | |||
| Mean Deviation | 10.58 | |||
| Coefficient Of Variation | (2,803) | |||
| Standard Deviation | 15.87 | |||
| Variance | 251.8 | |||
| Information Ratio | (0.04) | |||
| Jensen Alpha | (1.00) | |||
| Total Risk Alpha | (2.06) | |||
| Treynor Ratio | (0.09) | |||
| Maximum Drawdown | 72.53 | |||
| Value At Risk | (17.34) | |||
| Potential Upside | 42.57 | |||
| Skewness | 2.01 | |||
| Kurtosis | 4.25 |
Datavault January 24, 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 Datavault 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 | 13,397,646 | ||
| Daily Balance Of Power | (0.57) | ||
| Rate Of Daily Change | 0.91 | ||
| Day Median Price | 0.87 | ||
| Day Typical Price | 0.85 | ||
| Price Action Indicator | (0.09) |
Additional Tools for Datavault Stock Analysis
When running Datavault's price analysis, check to measure Datavault'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 Datavault is operating at the current time. Most of Datavault's value examination focuses on studying past and present price action to predict the probability of Datavault's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Datavault's price. Additionally, you may evaluate how the addition of Datavault to your portfolios can decrease your overall portfolio volatility.