Science Applications Stock Forecast - Simple Moving Average

85S Stock   118.00  3.00  2.61%   
The Simple Moving Average forecasted value of Science Applications International on the next trading day is expected to be 118.00 with a mean absolute deviation of 2.31 and the sum of the absolute errors of 136.42. Science Stock Forecast is based on your current time horizon.
  
A two period moving average forecast for Science Applications 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.

Science Applications Simple Moving Average Price Forecast For the 24th of November

Given 90 days horizon, the Simple Moving Average forecasted value of Science Applications International on the next trading day is expected to be 118.00 with a mean absolute deviation of 2.31, mean absolute percentage error of 18.64, and the sum of the absolute errors of 136.42.
Please note that although there have been many attempts to predict Science 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 Science Applications' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Science Applications Stock Forecast Pattern

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Science Applications Forecasted Value

In the context of forecasting Science Applications' 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. Science Applications' downside and upside margins for the forecasting period are 115.50 and 120.50, respectively. We have considered Science Applications' 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
118.00
115.50
Downside
118.00
Expected Value
120.50
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 Science Applications stock data series using in forecasting. Note that when a statistical model is used to represent Science Applications 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 Criteria117.3602
BiasArithmetic mean of the errors -0.0592
MADMean absolute deviation2.3121
MAPEMean absolute percentage error0.0188
SAESum of the absolute errors136.415
The simple moving average model is conceptually a linear regression of the current value of Science Applications International price series against current and previous (unobserved) value of Science Applications. 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

Predictive Modules for Science Applications

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Science Applications. 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 Science Applications' 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
115.48118.00120.52
Details
Intrinsic
Valuation
LowRealHigh
93.0695.58129.80
Details
Bollinger
Band Projection (param)
LowMiddleHigh
118.00118.00118.00
Details

Other Forecasting Options for Science Applications

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

Science Applications 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 Science Applications stock to make a market-neutral strategy. Peer analysis of Science Applications could also be used in its relative valuation, which is a method of valuing Science Applications by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Science Applications 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 Science Applications' 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 Science Applications' current price.

Science Applications Market Strength Events

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

Science Applications Risk Indicators

The analysis of Science Applications' 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 Science Applications' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting science 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.
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Additional Tools for Science Stock Analysis

When running Science Applications' price analysis, check to measure Science Applications' 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 Science Applications is operating at the current time. Most of Science Applications' value examination focuses on studying past and present price action to predict the probability of Science Applications' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Science Applications' price. Additionally, you may evaluate how the addition of Science Applications to your portfolios can decrease your overall portfolio volatility.