Digital Turbine Stock Forecast - Naive Prediction
| 4MD Stock | EUR 1.97 0.04 2.07% |
The Naive Prediction forecasted value of Digital Turbine on the next trading day is expected to be 1.91 with a mean absolute deviation of 0.22 and the sum of the absolute errors of 13.59. Digital Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Digital Turbine's historical fundamentals, such as revenue growth or operating cash flow patterns.
Digital |
Digital Turbine Naive Prediction Price Forecast For the 9th of January
Given 90 days horizon, the Naive Prediction forecasted value of Digital Turbine on the next trading day is expected to be 1.91 with a mean absolute deviation of 0.22, mean absolute percentage error of 0.08, and the sum of the absolute errors of 13.59.Please note that although there have been many attempts to predict Digital 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 Digital Turbine's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Digital Turbine Stock Forecast Pattern
| Backtest Digital Turbine | Digital Turbine Price Prediction | Buy or Sell Advice |
Digital Turbine Forecasted Value
In the context of forecasting Digital Turbine'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. Digital Turbine's downside and upside margins for the forecasting period are 0.02 and 10.78, respectively. We have considered Digital Turbine'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.
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 Digital Turbine stock data series using in forecasting. Note that when a statistical model is used to represent Digital Turbine 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.| AIC | Akaike Information Criteria | 115.5917 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.2228 |
| MAPE | Mean absolute percentage error | 0.117 |
| SAE | Sum of the absolute errors | 13.5899 |
Predictive Modules for Digital Turbine
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Digital Turbine. 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.Other Forecasting Options for Digital Turbine
For every potential investor in Digital, whether a beginner or expert, Digital Turbine's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Digital Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Digital. Basic forecasting techniques help filter out the noise by identifying Digital Turbine's price trends.Digital Turbine 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 Digital Turbine stock to make a market-neutral strategy. Peer analysis of Digital Turbine could also be used in its relative valuation, which is a method of valuing Digital Turbine by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Digital Turbine 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 Digital Turbine'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 Digital Turbine's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Digital Turbine Market Strength Events
Market strength indicators help investors to evaluate how Digital Turbine stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Digital Turbine shares will generate the highest return on investment. By undertsting and applying Digital Turbine stock market strength indicators, traders can identify Digital Turbine entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.02 | |||
| Day Median Price | 1.97 | |||
| Day Typical Price | 1.97 | |||
| Price Action Indicator | 0.02 | |||
| Period Momentum Indicator | 0.04 |
Digital Turbine Risk Indicators
The analysis of Digital Turbine'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 Digital Turbine's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting digital 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.
| Mean Deviation | 5.3 | |||
| Standard Deviation | 8.64 | |||
| Variance | 74.62 |
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.
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Additional Information and Resources on Investing in Digital Stock
When determining whether Digital Turbine is a strong investment it is important to analyze Digital Turbine's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Digital Turbine's future performance. For an informed investment choice regarding Digital Stock, refer to the following important reports:Check out Historical Fundamental Analysis of Digital Turbine to cross-verify your projections. For more detail on how to invest in Digital Stock please use our How to Invest in Digital Turbine guide.You can also try the Bollinger Bands module to use Bollinger Bands indicator to analyze target price for a given investing horizon.