Datavault Stock Forward View - Simple Moving Average

DVLT Stock   0.70  0.03  4.26%   
Predicting where Datavault's stock will trade is more achievable when sentiment data complements traditional analysis. This module isolates the sentiment-driven component of price to highlight potential mispricings.
At this point in time, the relative strength indicator for Datavault stands at 42, indicating moderately negative momentum. This range suggests moderated price movement without extreme directional pressure.
Momentum
Sell Extended
 
Oversold
 
Overbought
Predicting where Datavault's stock will trade is more achievable when sentiment data complements traditional analysis. This module isolates the sentiment-driven component of price to highlight potential mispricings. Fundamental inputs for Datavault's price forecast:
 EPS Estimate Current Year
-0.44
 Wall Street Target Price
3
 Quarterly Revenue Growth
1.467
This section provides headline-driven context for Datavault AI alongside peer activity.

Datavault RSI Context

The Simple Moving Average forecasted value of Datavault AI on the next trading day is expected to be 0.68 with a mean absolute deviation of 0.09 and the sum of the absolute errors of 5.05.

Datavault AI Hype-Price Relationship

Sentiment data for Datavault AI synthesizes media coverage, analyst tone, and social engagement into a single signal. When Datavault's sentiment diverges sharply from price, a mean-reversion trade may be developing.
For Datavault, sentiment analysis reveals whether the prevailing narrative matches business reality. A persistent divergence often resolves in the direction of fundamentals once sentiment normalizes.
The Simple Moving Average forecasted value of Datavault AI on the next trading day is expected to be 0.68 with a mean absolute deviation of 0.09 and the sum of the absolute errors of 5.05.
Datavault after-hype prediction price
    
  $ 0.71  
The sentiment panel provides context that can be compared with forecasting models and technical indicators.
Historical Fundamental Analysis of Datavault can be used to cross-verify projections for Datavault. The historical series provides projection context.

Datavault Additional Predictive Modules

Most predictive techniques to examine Datavault price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Datavault using various technical indicators. When you analyze Datavault charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
A two period moving average forecast for Datavault is based on an daily price series in which the stock price on a given day is replaced by the mean of that price and the preceding price. This model is best suited to price patterns experiencing average volatility.

Datavault Simple Moving Average Price Forecast For the 12th of March 2026

Given 90 days horizon, the Simple Moving Average forecasted value of Datavault AI on the next trading day is expected to be 0.68 with a mean absolute deviation of 0.09 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 5.05 .
Please note that although there have been many attempts to predict Datavault Stock prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Datavault's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Datavault Stock Forecast Pattern

Backtest Datavault  Datavault Price Prediction  Research Analysis  

Datavault Forecasted Value

This next-day forecast for Datavault AI uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. Investors should still remember that no empirical framework consistently proves that one family of forecasting models will outperform all other approaches in live markets.
Market Value
0.70
0.68
Expected Value
13.59
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Moving Average forecasting method's relative quality and the estimations of the prediction error of Datavault stock data series using in forecasting. Note that when a statistical model is used to represent Datavault stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.
AICAkaike Information Criteria110.4813
BiasArithmetic mean of the errors 0.0181
MADMean absolute deviation0.0857
MAPEMean absolute percentage error0.0952
SAESum of the absolute errors5.0535
The simple moving average model is conceptually a linear regression of the current value of Datavault AI price series against current and previous (unobserved) value of Datavault. In time series analysis, the simple moving-average model is a very common approach for modeling univariate price series models including forecasting prices into the future
The mean reversion effect in Datavault is stronger when the initial deviation was driven by sentiment rather than fundamental change. Identifying the root cause of Datavault's price dislocation is essential before acting.
Hype
Prediction
LowEstimatedHigh
0.040.7113.62
Details
Intrinsic
Valuation
LowRealHigh
0.030.6713.58
Details
Earnings
Estimates (0)
LowProjected EPSHigh
-0.11-0.11-0.11
Details
Competitive positioning is a critical dimension of Datavault analysis. Understanding where Datavault AI stands relative to its peers on returns, growth, and valuation helps investors assess whether its advantage is sustainable.

Datavault After-Hype Price Density Analysis

The probability distribution for Datavault's predicted price encodes the full spectrum of outcomes, weighted by their estimated likelihood. Investors should compare this range against their personal risk tolerance before committing to Datavault positions.
   Next price density   
       Expected price to next headline  

Datavault Estimiated After-Hype Price Volatility

The news prediction model for Datavault analyzes the correlation between Datavault's historical headline events and same-day or next-day price movements. Datavault's after-hype downside and upside margins for the prediction period are 0.04 and 13.62, respectively. Predictive accuracy varies significantly across different news categories and market regimes for Datavault.
Current Value
0.70
0.71
After-hype Price
13.62
Upside
The after-hype framework applied to Datavault AI assumes a 3 months review window and focuses on post-sentiment normalization rather than raw momentum. This view is most useful when investors want to compare sentiment-driven price extension with a more measured post-news scenario.

Datavault Stock Price Outlook Analysis

Have you ever been surprised when a price of a Company such as Datavault is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Datavault backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Datavault, there might be something going there, and it might present an excellent short sale opportunity.
Expected ReturnPeriod VolatilityHype ElasticityRelated ElasticityNews DensityRelated DensityExpected Hype
  0.56 
12.91
  0.01 
  0.08 
11 Events
6 Events
In 11 days
Latest traded priceExpected after-news pricePotential return on next major newsAverage after-hype volatility
0.70
0.71
1.64 
129,100  
Notes

Datavault Hype Timeline

Datavault AI is currently traded for 0.70. The company has historical hype elasticity of 0.01, and average elasticity to hype of competition of -0.08. Datavault is expected to increase in value after the next headline, with the price projected to jump to 0.71 or above. The average volatility of media hype impact on the company the price is over 100%. The price appreciation on the next news is projected to be 1.64%, whereas the daily expected return is currently at -0.56%. The volatility of related hype on Datavault is about 9492.65%, with the expected price after the next announcement by competition of 0.62. The company reported previous year's revenue of 2.67 M. Net Loss for the year was -51.41 M with profit before overhead, payroll, taxes, and interest of 528 K. Given the investment horizon of 90 days the next expected press release will be in 11 days.
Historical Fundamental Analysis of Datavault can be used to cross-verify projections for Datavault. The historical series provides projection context.

Datavault Related Hype Analysis

Sector-wide news events often affect Datavault before the fundamental impact on Datavault's own business becomes clear. Peer hype analysis helps investors distinguish between sector-level sentiment shifts and Datavault-specific developments.
Hype
Elasticity
News
Density
Semi
Deviation
Information
Ratio
Potential
Upside
Value
At Risk
Maximum
Drawdown
DMRCDigimarc-0.05 7 per month 0.00 -0.13 6.05 -8.01 20.69
TTECTTEC Holdings 0.04 7 per month 0.00 -0.03 8.68 -8.77 22.32
ARAIArrive AI-0.56 10 per month 0.00 -0.32 6.40 -11.85 29.79
LTRXLantronix-0.20 7 per month 4.65 0.06 6.50 -7.48 26.34
TCXTucows Inc-1.12 7 per month 0.00 -0.12 4.22 -5.93 16.74
ZEPPZepp Health Corp-0.67 5 per month 0.00 -0.05 8.73 -12.76 39.55
UISUnisys-0.07 7 per month 0.00 -0.06 8.08 -5.47 18.79
PERFPerfect Corp 0.16 11 per month 0.00 -0.1 4.29 -4.42 26.03
AXTIAXT Inc 1.45 10 per month 6.48 0.25 21.00 -12.32 41.23
SQNSSequans Communications SA-0.34 10 per month 0.00 -0.15 7.35 -8.29 30.18

Other Forecasting Options for Datavault

For both new and experienced investors in Datavault, the ability to analyze Datavault's price movement is a fundamental investment skill. Price chart noise in Datavault Stock can create false signals and mislead investment decisions.

Datavault Related Equities

The following equities are related to Datavault within the Information Technology space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Datavault against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
 Risk & Return  Correlation

Datavault Market Strength Events

Tracking market strength indicators for Datavault helps investors understand the momentum dynamics of the stock in real time. These signals support informed decisions about when to enter or exit positions in Datavault AI for maximum return potential.

Datavault Risk Indicators

Properly assessing Datavault's risk indicators is a prerequisite for building reliable price forecasts. Identifying and quantifying the risks associated with Datavault's allows investors to make better-informed decisions about accepting or hedging their exposure.
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Story Coverage note for Datavault

Coverage intensity for Datavault AI matters because narrative visibility can influence sentiment, participation, and volatility around the name. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.

Datavault Short Properties

Short sentiment tied to Datavault AI matters because heavier bearish pressure can change how quickly future price expectations become unstable. Used correctly, these measures can help investors decide when hedging or timing discipline may matter more than conviction alone.
Common Stock Shares Outstanding4.2 M
Cash And Short Term Investments3.3 M

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