Schneider Electric Pink Sheet Forecast - Simple Exponential Smoothing
| SBGSY Stock | USD 50.40 0.46 0.92% |
The Simple Exponential Smoothing forecasted value of Schneider Electric SA on the next trading day is expected to be 50.38 with a mean absolute deviation of 0.63 and the sum of the absolute errors of 37.58. Schneider Pink Sheet Forecast is based on your current time horizon.
Schneider |
Schneider Electric Simple Exponential Smoothing Price Forecast For the 24th of November
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Schneider Electric SA on the next trading day is expected to be 50.38 with a mean absolute deviation of 0.63, mean absolute percentage error of 0.60, and the sum of the absolute errors of 37.58.Please note that although there have been many attempts to predict Schneider 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 Schneider Electric's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Schneider Electric Pink Sheet Forecast Pattern
| Backtest Schneider Electric | Schneider Electric Price Prediction | Buy or Sell Advice |
Schneider Electric Forecasted Value
In the context of forecasting Schneider Electric'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. Schneider Electric's downside and upside margins for the forecasting period are 48.87 and 51.90, respectively. We have considered Schneider Electric'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.
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 Schneider Electric pink sheet data series using in forecasting. Note that when a statistical model is used to represent Schneider Electric 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.| AIC | Akaike Information Criteria | 115.7548 |
| Bias | Arithmetic mean of the errors | 0.0065 |
| MAD | Mean absolute deviation | 0.6264 |
| MAPE | Mean absolute percentage error | 0.0121 |
| SAE | Sum of the absolute errors | 37.5835 |
Predictive Modules for Schneider Electric
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Schneider Electric. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Schneider Electric's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Other Forecasting Options for Schneider Electric
For every potential investor in Schneider, whether a beginner or expert, Schneider Electric's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Schneider Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Schneider. Basic forecasting techniques help filter out the noise by identifying Schneider Electric's price trends.View Schneider Electric Related Equities
| Risk & Return | Correlation |
Schneider Electric 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 Schneider Electric'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 Schneider Electric's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Schneider Electric Market Strength Events
Market strength indicators help investors to evaluate how Schneider Electric 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 Schneider Electric shares will generate the highest return on investment. By undertsting and applying Schneider Electric pink sheet market strength indicators, traders can identify Schneider Electric SA entry and exit signals to maximize returns.
Schneider Electric Risk Indicators
The analysis of Schneider Electric'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 Schneider Electric's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting schneider 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.
| Mean Deviation | 1.2 | |||
| Semi Deviation | 1.53 | |||
| Standard Deviation | 1.52 | |||
| Variance | 2.32 | |||
| Downside Variance | 2.6 | |||
| Semi Variance | 2.33 | |||
| Expected Short fall | (1.18) |
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 Schneider Pink Sheet Analysis
When running Schneider Electric's price analysis, check to measure Schneider Electric'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 Schneider Electric is operating at the current time. Most of Schneider Electric's value examination focuses on studying past and present price action to predict the probability of Schneider Electric's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Schneider Electric's price. Additionally, you may evaluate how the addition of Schneider Electric to your portfolios can decrease your overall portfolio volatility.