Consumer Goods Ultrasector Fund Statistic Functions Linear Regression

CNPSX Fund  USD 70.10  0.48  0.69%   
Consumer Goods statistic functions tool provides the execution environment for running the Linear Regression function and other technical functions against Consumer Goods. Consumer Goods value trend is the prevailing direction of the price over some defined period of time. The concept of trend is an important idea in technical analysis, including the analysis of statistic functions indicators. As with most other technical indicators, the Linear Regression function function is designed to identify and follow existing trends. Consumer Goods statistical functions help analysts to determine different price movement patterns based on how price series statistical indicators change over time. Please specify Time Period to run this model.

Execute Function
The output start index for this execution was nine with a total number of output elements of fifty-two. The Linear Regression model generates relationship between price series of Consumer Goods Ultra and its peer or benchmark and helps predict Consumer Goods future price from its past values.

Consumer Goods Technical Analysis Modules

Most technical analysis of Consumer Goods 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 Consumer from various momentum indicators to cycle indicators. When you analyze Consumer 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.

About Consumer Goods 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 Consumer Goods Ultrasector. We use our internally-developed statistical techniques to arrive at the intrinsic value of Consumer Goods Ultrasector based on widely used predictive technical indicators. In general, we focus on analyzing Consumer Mutual Fund price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Consumer Goods'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 Consumer Goods's intrinsic value. In addition to deriving basic predictive indicators for Consumer Goods, we also check how macroeconomic factors affect Consumer Goods 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 Consumer Goods' 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
69.2370.1070.97
Details
Intrinsic
Valuation
LowRealHigh
68.9169.7870.65
Details
Naive
Forecast
LowNextHigh
71.0871.9672.83
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
65.8468.4771.10
Details

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Other Information on Investing in Consumer Mutual Fund

Consumer Goods financial ratios help investors to determine whether Consumer 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 Consumer with respect to the benefits of owning Consumer Goods security.
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