SFS Group Stock Forecast - Simple Moving Average

SFSN Stock  CHF 127.00  1.60  1.28%   
The Simple Moving Average forecasted value of SFS Group AG on the next trading day is expected to be 126.20 with a mean absolute deviation of 0.99 and the sum of the absolute errors of 58.30. SFS Stock Forecast is based on your current time horizon.
  
A two period moving average forecast for SFS Group 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.

SFS Group Simple Moving Average Price Forecast For the 29th of November

Given 90 days horizon, the Simple Moving Average forecasted value of SFS Group AG on the next trading day is expected to be 126.20 with a mean absolute deviation of 0.99, mean absolute percentage error of 1.52, and the sum of the absolute errors of 58.30.
Please note that although there have been many attempts to predict SFS 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 SFS Group's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

SFS Group Stock Forecast Pattern

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SFS Group Forecasted Value

In the context of forecasting SFS Group'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. SFS Group's downside and upside margins for the forecasting period are 125.20 and 127.20, respectively. We have considered SFS Group'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
127.00
125.20
Downside
126.20
Expected Value
127.20
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 SFS Group stock data series using in forecasting. Note that when a statistical model is used to represent SFS Group 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 Criteria114.8525
BiasArithmetic mean of the errors -0.0424
MADMean absolute deviation0.9881
MAPEMean absolute percentage error0.0078
SAESum of the absolute errors58.3
The simple moving average model is conceptually a linear regression of the current value of SFS Group AG price series against current and previous (unobserved) value of SFS Group. 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 SFS Group

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as SFS Group AG. 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
124.40125.40126.40
Details
Intrinsic
Valuation
LowRealHigh
112.86126.55127.55
Details
Bollinger
Band Projection (param)
LowMiddleHigh
124.04125.24126.44
Details

Other Forecasting Options for SFS Group

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

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

SFS Group AG 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 SFS Group'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 SFS Group's current price.

SFS Group Market Strength Events

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

SFS Group Risk Indicators

The analysis of SFS Group'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 SFS Group's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sfs 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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Additional Tools for SFS Stock Analysis

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