Schweiter Technologies Stock Forward View - 4 Period Moving Average

SWTQ Stock  CHF 273.00  3.00  1.11%   
This page provides 4 Period Moving Average reference data for Schweiter Technologies AG, calculated from historical daily prices. The model output shown here is derived from Schweiter Technologies's historical price series and is provided for informational purposes. Projected values and accuracy measures are included for reference.
The 4 Period Moving Average forecasted value of Schweiter Technologies AG on the next trading day is expected to be 268.38 with a mean absolute deviation of 5.54 and the sum of the absolute errors of 321.38.The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Schweiter Technologies. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Schweiter Technologies AG and therefore, it cannot be a useful forecasting tool for medium or long range price predictions The 4 Period Moving Average reference information for Schweiter Technologies is based on available price data and is intended for informational purposes.
A four-period moving average forecast model for Schweiter Technologies AG is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.

4 Period Moving Average Price Forecast For the 25th of March

Given 90 days horizon, the 4 Period Moving Average forecasted value of Schweiter Technologies AG on the next trading day is expected to be 268.38 with a mean absolute deviation of 5.54 , mean absolute percentage error of 43.87 , and the sum of the absolute errors of 321.38 .
Please note that although there have been many attempts to predict Schweiter Stock prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Schweiter Technologies' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

Backtest Schweiter Technologies  Schweiter Technologies Price Prediction  Research Analysis  

Forecasted Value

The next-day forecast for Schweiter Technologies AG focuses on identifying predictive downside and upside bands that can frame a realistic trading range. The projected forecast band currently runs from roughly 266.22 on the downside to about 270.53 on the upside.
Market Value
273.00
266.22
Downside
268.38
Expected Value
270.53
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Schweiter Technologies stock data series using in forecasting. Note that when a statistical model is used to represent Schweiter Technologies 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 Criteria116.3782
BiasArithmetic mean of the errors -0.9203
MADMean absolute deviation5.5409
MAPEMean absolute percentage error0.0214
SAESum of the absolute errors321.375
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Schweiter Technologies. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Schweiter Technologies AG and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Other Forecasting Options for Schweiter Technologies

The autocorrelation structure of Schweiter Technologies' daily returns reveals whether Schweiter exhibits momentum, mean-reversion, or random-walk behavior. Separating these elements helps distinguish persistent directional moves from temporary noise in Schweiter Stock price data. Stochastic oscillator analysis compares Schweiter Technologies' closing price to its range over a given period.

Schweiter Technologies Related Equities

The stocks listed below are peers of Schweiter Technologies within the Industrials space and offer context for ranking and strength. Growth rate gaps between Schweiter Technologies and its peers often explain pricing differences in the market. When Schweiter Technologies breaks from its peer group on a key metric, it often signals a firm-level change worth exploring. Combining quantitative ratios with qualitative context such as management quality and market position sharpens peer comparisons.
 Risk & Return  Correlation

Schweiter Technologies Market Strength Events

Market strength indicators applied to Schweiter Technologies stock help assess momentum and resilience across environments. These indicators support informed market timing decisions when analyzing Schweiter Technologies. For Schweiter Technologies AG, market strength indicators complement fundamental analysis with timing context.

Schweiter Technologies Risk Indicators

Risk indicator analysis for Schweiter Technologies is essential for accurately projecting its future price trajectory. The process involves identifying the amount of risk involved in Schweiter Technologies' investment and either accepting or mitigating it. Understanding the risk profile of Schweiter Technologies' allows investors to make more informed decisions about position sizing.
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.

Story Coverage note for Schweiter Technologies

Coverage intensity for Schweiter Technologies AG matters because narrative visibility can influence sentiment, participation, and volatility around the name. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

Other Macroaxis Stories

Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.

Schweiter Technologies Short Properties

Reviewing short-oriented indicators for Schweiter Technologies AG is useful because long and short participants often create very different signals for timing and volatility. This is most valuable when investors want to know whether bearish pressure is starting to shape the market's reaction function.
Common Stock Shares Outstanding1.4 M
Cash And Short Term Investments111.1 M

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