Data Storage Stock Forecast - Naive Prediction

DTST Stock  USD 5.11  0.01  0.20%   
The Naive Prediction forecasted value of Data Storage Corp on the next trading day is expected to be 4.97 with a mean absolute deviation of 0.08 and the sum of the absolute errors of 4.90. Data Stock Forecast is based on your current time horizon.
At this time the relative strength indicator of Data Storage's share price is below 20 suggesting that the stock is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards.

Momentum 0

 Sell Peaked

 
Oversold
 
Overbought
The successful prediction of Data Storage's future price could yield a significant profit. We analyze noise-free headlines and recent hype associated with Data Storage Corp, which may create opportunities for some arbitrage if properly timed. Below are the key fundamental drivers impacting Data Storage's stock price prediction:
Quarterly Earnings Growth
274.596
EPS Estimate Next Quarter
(0.11)
EPS Estimate Current Year
2.06
EPS Estimate Next Year
(0.39)
Wall Street Target Price
9
Using Data Storage hype-based prediction, you can estimate the value of Data Storage Corp from the perspective of Data Storage response to recently generated media hype and the effects of current headlines on its competitors.
The Naive Prediction forecasted value of Data Storage Corp on the next trading day is expected to be 4.97 with a mean absolute deviation of 0.08 and the sum of the absolute errors of 4.90.

Data Storage after-hype prediction price

    
  USD 5.16  
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Check out Historical Fundamental Analysis of Data Storage to cross-verify your projections.
For more information on how to buy Data Stock please use our How to Invest in Data Storage guide.Receivables Turnover is likely to gain to 16.84 in 2026, whereas Inventory Turnover is likely to drop 17.65 in 2026. . Common Stock Shares Outstanding is likely to gain to about 8.9 M in 2026. Net Income Applicable To Common Shares is likely to gain to about 246.5 K in 2026.

Data Storage Additional Predictive Modules

Most predictive techniques to examine Data price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Data using various technical indicators. When you analyze Data 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.
Forecasting cash, or other financial indicators, requires analysts to apply different statistical methods, techniques, and algorithms to find hidden patterns within the Data Storage's financial statements to predict how it will affect future prices.
 
Cash  
First Reported
2007-12-31
Previous Quarter
611.3 K
Current Value
284.7 K
Quarterly Volatility
3.1 M
 
Housing Crash
 
Credit Downgrade
 
Yuan Drop
 
Covid
A naive forecasting model for Data Storage is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Data Storage Corp value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Data Storage Naive Prediction Price Forecast For the 3rd of January

Given 90 days horizon, the Naive Prediction forecasted value of Data Storage Corp on the next trading day is expected to be 4.97 with a mean absolute deviation of 0.08, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.90.
Please note that although there have been many attempts to predict Data Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Data Storage's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Data Storage Stock Forecast Pattern

Backtest Data StorageData Storage Price PredictionBuy or Sell Advice 

Data Storage Forecasted Value

In the context of forecasting Data Storage's Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Data Storage's downside and upside margins for the forecasting period are 2.62 and 7.31, respectively. We have considered Data Storage's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Market Value
5.11
4.97
Expected Value
7.31
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Data Storage stock data series using in forecasting. Note that when a statistical model is used to represent Data Storage 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 Criteria113.5969
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0804
MAPEMean absolute percentage error0.018
SAESum of the absolute errors4.9019
This model is not at all useful as a medium-long range forecasting tool of Data Storage Corp. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Data Storage. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Data Storage

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Data Storage Corp. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.
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.
Hype
Prediction
LowEstimatedHigh
2.825.167.50
Details
Intrinsic
Valuation
LowRealHigh
3.906.248.58
Details
1 Analysts
Consensus
LowTargetHigh
8.199.009.99
Details

Other Forecasting Options for Data Storage

For every potential investor in Data, whether a beginner or expert, Data Storage's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Data Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Data. Basic forecasting techniques help filter out the noise by identifying Data Storage's price trends.

Data Storage Related Equities

One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Data Storage stock to make a market-neutral strategy. Peer analysis of Data Storage could also be used in its relative valuation, which is a method of valuing Data Storage by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Data Storage Corp Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Data Storage's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Data Storage's current price.

Data Storage Market Strength Events

Market strength indicators help investors to evaluate how Data Storage stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Data Storage shares will generate the highest return on investment. By undertsting and applying Data Storage stock market strength indicators, traders can identify Data Storage Corp entry and exit signals to maximize returns.

Data Storage Risk Indicators

The analysis of Data Storage's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Data Storage's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting data stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
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.

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 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.