Digital Turbine Stock Forecast - Naive Prediction
| APPS Stock | USD 3.32 0.14 4.40% |
The Naive Prediction forecasted value of Digital Turbine on the next trading day is expected to be 3.79 with a mean absolute deviation of 0.43 and the sum of the absolute errors of 26.41. Digital Stock Forecast is based on your current time horizon.
Digital |
Open Interest Against 2025-06-20 Digital Option Contracts
Although open interest is a measure utilized in the options markets, it could be used to forecast Digital Turbine's spot prices because the number of available contracts in the market changes daily, and new contracts can be created or liquidated at will. Since open interest in Digital Turbine's options reflects these daily shifts, investors could use the patterns of these changes to develop long and short-term trading strategies for Digital Turbine stock based on available contracts left at the end of a trading day.
Please note that to derive more accurate forecasting about market movement from the current Digital Turbine's open interest, investors have to compare it to Digital Turbine's spot prices. As Ford's stock price increases, high open interest indicates that money is entering the market, and the market is strongly bullish. Conversely, if the price of Digital Turbine is decreasing and there is high open interest, that is a sign that the bearish trend will continue, and investors may react by taking short positions in Digital. So, decreasing or low open interest during a bull market indicates that investors are becoming uncertain of the depth of the bullish trend, and a reversal in sentiment will likely follow.
Forecasting cash, or other financial indicators, requires analysts to apply different statistical methods, techniques, and algorithms to find hidden patterns within the Digital Turbine's financial statements to predict how it will affect future prices.
Cash | First Reported 2000-12-31 | Previous Quarter 32.8 M | Current Value 35.3 M | Quarterly Volatility 27.3 M |
Digital Turbine Naive Prediction Price Forecast For the 15th of March 2025
Given 90 days horizon, the Naive Prediction forecasted value of Digital Turbine on the next trading day is expected to be 3.79 with a mean absolute deviation of 0.43, mean absolute percentage error of 0.35, and the sum of the absolute errors of 26.41.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 0.03 and 18.11, 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 | 117.0533 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.433 |
| MAPE | Mean absolute percentage error | 0.1539 |
| SAE | Sum of the absolute errors | 26.4143 |
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.
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 | 6.83 | |||
| Semi Deviation | 5.26 | |||
| Standard Deviation | 13.59 | |||
| Variance | 184.76 | |||
| Downside Variance | 38.7 | |||
| Semi Variance | 27.64 | |||
| Expected Short fall | (8.87) |
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 Tools for Digital Stock Analysis
When running Digital Turbine's price analysis, check to measure Digital Turbine'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 Digital Turbine is operating at the current time. Most of Digital Turbine's value examination focuses on studying past and present price action to predict the probability of Digital Turbine's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Digital Turbine's price. Additionally, you may evaluate how the addition of Digital Turbine to your portfolios can decrease your overall portfolio volatility.