SCIENCE IN Stock Forecast - Simple Regression

8D9 Stock  EUR 0.29  0.01  3.33%   
The Simple Regression forecasted value of SCIENCE IN SPORT on the next trading day is expected to be 0.30 with a mean absolute deviation of 0 and the sum of the absolute errors of 0.30. SCIENCE Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of SCIENCE IN's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through SCIENCE IN price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

SCIENCE IN Simple Regression Price Forecast For the 24th of November

Given 90 days horizon, the Simple Regression forecasted value of SCIENCE IN SPORT on the next trading day is expected to be 0.30 with a mean absolute deviation of 0, mean absolute percentage error of 0.00004, and the sum of the absolute errors of 0.30.
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 IN's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

SCIENCE IN Stock Forecast Pattern

Backtest SCIENCE INSCIENCE IN Price PredictionBuy or Sell Advice 

SCIENCE IN Forecasted Value

In the context of forecasting SCIENCE IN'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. SCIENCE IN's downside and upside margins for the forecasting period are 0 and 2.27, respectively. We have considered SCIENCE IN'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
0.29
0.30
Expected Value
2.27
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of SCIENCE IN stock data series using in forecasting. Note that when a statistical model is used to represent SCIENCE IN 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 Criteria107.9792
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0049
MAPEMean absolute percentage error0.0174
SAESum of the absolute errors0.296
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as SCIENCE IN SPORT historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for SCIENCE IN

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 IN SPORT. 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.
Hype
Prediction
LowEstimatedHigh
0.010.292.28
Details
Intrinsic
Valuation
LowRealHigh
0.010.242.23
Details

Other Forecasting Options for SCIENCE IN

For every potential investor in SCIENCE, whether a beginner or expert, SCIENCE IN's 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 IN's price trends.

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

SCIENCE IN SPORT 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 IN'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 SCIENCE IN's current price.

SCIENCE IN Market Strength Events

Market strength indicators help investors to evaluate how SCIENCE IN 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 IN shares will generate the highest return on investment. By undertsting and applying SCIENCE IN stock market strength indicators, traders can identify SCIENCE IN SPORT entry and exit signals to maximize returns.

SCIENCE IN Risk Indicators

The analysis of SCIENCE IN'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 SCIENCE IN's 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.

Currently Active Assets on Macroaxis

Other Information on Investing in SCIENCE Stock

SCIENCE IN financial ratios help investors to determine whether SCIENCE Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in SCIENCE with respect to the benefits of owning SCIENCE IN security.