Schneider Electric Sa Stock Probability of Future Pink Sheet Price Finishing Under 46.05

SBGSY Stock  USD 50.40  0.07  0.14%   
Schneider Electric's future price is the expected price of Schneider Electric instrument. It is based on its current growth rate as well as the projected cash flow expected by the investors. This tool provides a mechanism to make assumptions about the upside potential and downside risk of Schneider Electric SA performance during a given time horizon utilizing its historical volatility. Check out Schneider Electric Backtesting, Schneider Electric Valuation, Schneider Electric Correlation, Schneider Electric Hype Analysis, Schneider Electric Volatility, Schneider Electric History as well as Schneider Electric Performance.
  
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Schneider Electric Target Price Odds to finish below 46.05

The tendency of Schneider Pink Sheet price to converge on an average value over time is a known aspect in finance that investors have used since the beginning of the stock market for forecasting. However, many studies suggest that some traded equity instruments are consistently mispriced before traders' demand and supply correct the spread. One possible conclusion to this anomaly is that these stocks have additional risk, for which investors demand compensation in the form of extra returns.
Current PriceHorizonTarget PriceOdds to drop to $ 46.05  or more in 90 days
 50.40 90 days 46.05 
near 1
Based on a normal probability distribution, the odds of Schneider Electric to drop to $ 46.05  or more in 90 days from now is near 1 (This Schneider Electric SA probability density function shows the probability of Schneider Pink Sheet to fall within a particular range of prices over 90 days) . Probability of Schneider Electric price to stay between $ 46.05  and its current price of $50.4 at the end of the 90-day period is about 22.12 .
Assuming the 90 days horizon Schneider Electric has a beta of 0.0112. This usually implies as returns on the market go up, Schneider Electric average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Schneider Electric SA will be expected to be much smaller as well. Additionally Schneider Electric SA has an alpha of 0.0031, implying that it can generate a 0.003086 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta).
   Schneider Electric Price Density   
       Price  

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.
Hype
Prediction
LowEstimatedHigh
48.8850.4051.92
Details
Intrinsic
Valuation
LowRealHigh
45.6947.2155.44
Details
Naive
Forecast
LowNextHigh
47.2148.7350.25
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
49.8150.2550.68
Details

Schneider Electric Risk Indicators

For the most part, the last 10-20 years have been a very volatile time for the stock market. Schneider Electric is not an exception. The market had few large corrections towards the Schneider Electric's value, including both sudden drops in prices as well as massive rallies. These swings have made and broken many portfolios. An investor can limit the violent swings in their portfolio by implementing a hedging strategy designed to limit downside losses. If you hold Schneider Electric SA, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Schneider Electric within the framework of very fundamental risk indicators.
α
Alpha over Dow Jones
0
β
Beta against Dow Jones0.01
σ
Overall volatility
1.42
Ir
Information ratio -0.08

Schneider Electric Price Density Drivers

Market volatility will typically increase when nervous long traders begin to feel the short-sellers pressure to drive the market lower. The future price of Schneider Pink Sheet often depends not only on the future outlook of the current and potential Schneider Electric's investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. Schneider Electric's indicators that are reflective of the short sentiment are summarized in the table below.
Common Stock Shares Outstanding2.8 B
Cash And Short Term Investments2.6 B

Schneider Electric Technical Analysis

Schneider Electric's future price can be derived by breaking down and analyzing its technical indicators over time. Schneider Pink Sheet technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Schneider Electric SA. In general, you should focus on analyzing Schneider Pink Sheet price patterns and their correlations with different microeconomic environments and drivers.

Schneider Electric Predictive Forecast Models

Schneider Electric's time-series forecasting models is one of many Schneider Electric's pink sheet analysis techniques aimed to predict future share value based on previously observed values. Time-series forecasting models are widely used for non-stationary data. Non-stationary data are called the data whose statistical properties, e.g., the mean and standard deviation, are not constant over time, but instead, these metrics vary over time. This non-stationary Schneider Electric's historical data is usually called time series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the pink sheet market movement and maximize returns from investment trading.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Schneider Electric in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Schneider Electric's short interest history, or implied volatility extrapolated from Schneider Electric options trading.

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.