Quantitative U S Fund Statistic Functions Beta
| GQSCX Fund | USD 16.33 0.30 1.80% |
| Symbol |
The output start index for this execution was three with a total number of output elements of fifty-eight. The Beta measures systematic risk based on how returns on Quantitative U S correlated with the market. If Beta is less than 0 Quantitative generally moves in the opposite direction as compared to the market. If Quantitative Beta is about zero movement of price series is uncorrelated with the movement of the benchmark. if Beta is between zero and one Quantitative U S is generally moves in the same direction as, but less than the movement of the market. For Beta = 1 movement of Quantitative is generally in the same direction as the market. If Beta > 1 Quantitative moves generally in the same direction as, but more than the movement of the benchmark.
Quantitative Technical Analysis Modules
Most technical analysis of Quantitative 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 Quantitative from various momentum indicators to cycle indicators. When you analyze Quantitative 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 | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About Quantitative 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 Quantitative U S. We use our internally-developed statistical techniques to arrive at the intrinsic value of Quantitative U S based on widely used predictive technical indicators. In general, we focus on analyzing Quantitative Mutual Fund price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Quantitative'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 Quantitative's intrinsic value. In addition to deriving basic predictive indicators for Quantitative, we also check how macroeconomic factors affect Quantitative 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 Quantitative'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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Other Information on Investing in Quantitative Mutual Fund
Quantitative financial ratios help investors to determine whether Quantitative Mutual Fund 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 Quantitative with respect to the benefits of owning Quantitative security.
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