Shelton Green Alpha Fund Statistic Functions Beta
| NEXTX Fund | USD 30.87 0.43 1.41% |
| Symbol |
The output start index for this execution was nine with a total number of output elements of fifty-two. The Beta measures systematic risk based on how returns on Shelton Green Alpha correlated with the market. If Beta is less than 0 Shelton Green generally moves in the opposite direction as compared to the market. If Shelton Green Beta is about zero movement of price series is uncorrelated with the movement of the benchmark. if Beta is between zero and one Shelton Green Alpha is generally moves in the same direction as, but less than the movement of the market. For Beta = 1 movement of Shelton Green is generally in the same direction as the market. If Beta > 1 Shelton Green moves generally in the same direction as, but more than the movement of the benchmark.
Shelton Green Technical Analysis Modules
Most technical analysis of Shelton Green help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Shelton from various momentum indicators to cycle indicators. When you analyze Shelton charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
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| Math Transform | ||
| Momentum Indicators | ||
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| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About Shelton Green Predictive Technical Analysis
Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Shelton Green Alpha. We use our internally-developed statistical techniques to arrive at the intrinsic value of Shelton Green Alpha based on widely used predictive technical indicators. In general, we focus on analyzing Shelton Mutual Fund price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Shelton Green's daily price indicators and compare them against related drivers, such as statistic functions and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Shelton Green's intrinsic value. In addition to deriving basic predictive indicators for Shelton Green, we also check how macroeconomic factors affect Shelton Green price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Shelton Green'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.
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