Schneider Electric Se Stock Market Value
| SBGSF Stock | USD 220.41 4.19 1.87% |
| Symbol | Schneider |
Schneider Electric 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Schneider Electric's pink sheet what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Schneider Electric.
| 07/28/2023 |
| 04/23/2024 |
If you would invest 0.00 in Schneider Electric on July 28, 2023 and sell it all today you would earn a total of 0.00 from holding Schneider Electric SE or generate 0.0% return on investment in Schneider Electric over 270 days. Schneider Electric is related to or competes with GE Aerospace, Eaton PLC, Illinois Tool, Parker Hannifin, and Emerson Electric. Schneider Electric S.E. provides energy and automation digital solutions worldwide More
Schneider Electric Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Schneider Electric's pink sheet current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Schneider Electric SE upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.59 | |||
| Information Ratio | 0.1212 | |||
| Maximum Drawdown | 6.6 | |||
| Value At Risk | (2.35) | |||
| Potential Upside | 2.76 |
Schneider Electric Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Schneider Electric's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Schneider Electric's standard deviation. In reality, there are many statistical measures that can use Schneider Electric historical prices to predict the future Schneider Electric's volatility.| Risk Adjusted Performance | 0.1146 | |||
| Jensen Alpha | 0.18 | |||
| Total Risk Alpha | 0.0724 | |||
| Sortino Ratio | 0.1159 | |||
| Treynor Ratio | 0.2469 |
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.
Schneider Electric Backtested Returns
We consider Schneider Electric very steady. Schneider Electric owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.12, which indicates the firm had a 0.12% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Schneider Electric SE, which you can use to evaluate the volatility of the company. Please validate Schneider Electric's Semi Deviation of 1.38, coefficient of variation of 563.43, and Risk Adjusted Performance of 0.1146 to confirm if the risk estimate we provide is consistent with the expected return of 0.18%. Schneider Electric has a performance score of 9 on a scale of 0 to 100. The entity has a beta of 1.05, which indicates a somewhat significant risk relative to the market. Schneider Electric returns are very sensitive to returns on the market. As the market goes up or down, Schneider Electric is expected to follow. Schneider Electric right now has a risk of 1.52%. Please validate Schneider Electric total risk alpha, expected short fall, market facilitation index, as well as the relationship between the value at risk and daily balance of power , to decide if Schneider Electric will be following its existing price patterns.
Auto-correlation | -0.38 |
Poor reverse predictability
Schneider Electric SE has poor reverse predictability. Overlapping area represents the amount of predictability between Schneider Electric time series from 28th of July 2023 to 10th of December 2023 and 10th of December 2023 to 23rd of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Schneider Electric price movement. The serial correlation of -0.38 indicates that just about 38.0% of current Schneider Electric price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.38 | |
| Spearman Rank Test | -0.23 | |
| Residual Average | 0.0 | |
| Price Variance | 238.38 |
Schneider Electric lagged returns against current returns
Autocorrelation, which is Schneider Electric pink sheet's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Schneider Electric's pink sheet expected returns. We can calculate the autocorrelation of Schneider Electric returns to help us make a trade decision. For example, suppose you find that Schneider Electric has exhibited high autocorrelation historically, and you observe that the pink sheet is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Schneider Electric regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Schneider Electric pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Schneider Electric pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Schneider Electric pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Schneider Electric Lagged Returns
When evaluating Schneider Electric's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Schneider Electric pink sheet have on its future price. Schneider Electric autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Schneider Electric autocorrelation shows the relationship between Schneider Electric pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Schneider Electric SE.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Check out Schneider Electric Correlation, Schneider Electric Volatility and Schneider Electric Alpha and Beta module to complement your research on Schneider Electric. You can also try the Portfolio Holdings module to check your current holdings and cash postion to detemine if your portfolio needs rebalancing.
Complementary 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.
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Schneider Electric technical pink sheet analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, pink sheet market cycles, or different charting patterns.