SIEMENS AG Stock Forecast - 20 Period Moving Average

SIEB Stock  EUR 89.50  1.00  1.13%   
The 20 Period Moving Average forecasted value of SIEMENS AG SP on the next trading day is expected to be 89.58 with a mean absolute deviation of 2.18 and the sum of the absolute errors of 89.45. SIEMENS Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of SIEMENS AG's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
A commonly used 20-period moving average forecast model for SIEMENS AG SP is based on a synthetically constructed SIEMENS AGdaily price series in which the value for a trading day is replaced by the mean of that value and the values for 20 of preceding and succeeding time periods. This model is best suited for price series data that changes over time.

SIEMENS AG 20 Period Moving Average Price Forecast For the 1st of December

Given 90 days horizon, the 20 Period Moving Average forecasted value of SIEMENS AG SP on the next trading day is expected to be 89.58 with a mean absolute deviation of 2.18, mean absolute percentage error of 7.37, and the sum of the absolute errors of 89.45.
Please note that although there have been many attempts to predict SIEMENS 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 SIEMENS AG's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

SIEMENS AG Stock Forecast Pattern

Backtest SIEMENS AGSIEMENS AG Price PredictionBuy or Sell Advice 

SIEMENS AG Forecasted Value

In the context of forecasting SIEMENS AG'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. SIEMENS AG's downside and upside margins for the forecasting period are 87.81 and 91.34, respectively. We have considered SIEMENS AG'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
89.50
89.58
Expected Value
91.34
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 20 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of SIEMENS AG stock data series using in forecasting. Note that when a statistical model is used to represent SIEMENS AG 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 Criteria83.3504
BiasArithmetic mean of the errors -0.8037
MADMean absolute deviation2.1817
MAPEMean absolute percentage error0.0242
SAESum of the absolute errors89.45
The eieght-period moving average method has an advantage over other forecasting models in that it does smooth out peaks and valleys in a set of daily observations. SIEMENS AG SP 20-period moving average forecast can only be used reliably to predict one or two periods into the future.

Predictive Modules for SIEMENS AG

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as SIEMENS AG SP. 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
86.7388.5090.27
Details
Intrinsic
Valuation
LowRealHigh
86.3688.1289.90
Details
Bollinger
Band Projection (param)
LowMiddleHigh
86.0088.1590.30
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as SIEMENS AG. Your research has to be compared to or analyzed against SIEMENS AG's peers to derive any actionable benefits. When done correctly, SIEMENS AG's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in SIEMENS AG SP.

Other Forecasting Options for SIEMENS AG

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

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

SIEMENS AG SP 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 SIEMENS AG'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 SIEMENS AG's current price.

SIEMENS AG Market Strength Events

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

SIEMENS AG Risk Indicators

The analysis of SIEMENS AG'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 SIEMENS AG's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting siemens 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 SIEMENS Stock

SIEMENS AG financial ratios help investors to determine whether SIEMENS 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 SIEMENS with respect to the benefits of owning SIEMENS AG security.