Siemens Energy Pink Sheet Forecast - Simple Exponential Smoothing

SMEGF Stock  USD 54.90  3.32  6.44%   
The Simple Exponential Smoothing forecasted value of Siemens Energy AG on the next trading day is expected to be 54.90 with a mean absolute deviation of 0.84 and the sum of the absolute errors of 50.22. Siemens Pink Sheet Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Siemens Energy's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Siemens Energy simple exponential smoothing forecast is a very popular model used to produce a smoothed price series. Whereas in simple Moving Average models the past observations for Siemens Energy AG are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as Siemens Energy AG prices get older.

Siemens Energy Simple Exponential Smoothing Price Forecast For the 2nd of December

Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Siemens Energy AG on the next trading day is expected to be 54.90 with a mean absolute deviation of 0.84, mean absolute percentage error of 1.57, and the sum of the absolute errors of 50.22.
Please note that although there have been many attempts to predict Siemens Pink Sheet 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 Energy's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Siemens Energy Pink Sheet Forecast Pattern

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Siemens Energy Forecasted Value

In the context of forecasting Siemens Energy's Pink Sheet 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 Energy's downside and upside margins for the forecasting period are 51.90 and 57.90, respectively. We have considered Siemens Energy'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
54.90
54.90
Expected Value
57.90
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Siemens Energy pink sheet data series using in forecasting. Note that when a statistical model is used to represent Siemens Energy pink sheet, 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 Criteria116.7206
BiasArithmetic mean of the errors -0.4667
MADMean absolute deviation0.837
MAPEMean absolute percentage error0.0205
SAESum of the absolute errors50.22
This simple exponential smoothing model begins by setting Siemens Energy AG forecast for the second period equal to the observation of the first period. In other words, recent Siemens Energy observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Siemens Energy

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 Energy AG. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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
51.9054.9057.90
Details
Intrinsic
Valuation
LowRealHigh
53.5256.5259.52
Details
Bollinger
Band Projection (param)
LowMiddleHigh
46.3551.1055.85
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Siemens Energy. Your research has to be compared to or analyzed against Siemens Energy's peers to derive any actionable benefits. When done correctly, Siemens Energy'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 Energy AG.

Other Forecasting Options for Siemens Energy

For every potential investor in Siemens, whether a beginner or expert, Siemens Energy's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Siemens Pink Sheet 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 Energy's price trends.

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

Siemens Energy AG Technical and Predictive Analytics

The pink sheet market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Siemens Energy'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 Energy's current price.

Siemens Energy Market Strength Events

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

Siemens Energy Risk Indicators

The analysis of Siemens Energy'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 Energy's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting siemens pink sheet 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 Pink Sheet

Siemens Energy financial ratios help investors to determine whether Siemens Pink Sheet 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 Energy security.