SF Sustainable (Switzerland) Statistic Functions Linear Regression Slope

SFPF Fund   124.50  0.50  0.40%   
SF Sustainable statistic functions tool provides the execution environment for running the Linear Regression Slope function and other technical functions against SF Sustainable. SF Sustainable 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 Slope function function is designed to identify and follow existing trends. SF Sustainable 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 Slope is the rate of change in SF Sustainable Property price series over its benchmark or peer price series.

SF Sustainable Technical Analysis Modules

Most technical analysis of SF Sustainable 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 SFPF from various momentum indicators to cycle indicators. When you analyze SFPF 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 SF Sustainable 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 SF Sustainable Property. We use our internally-developed statistical techniques to arrive at the intrinsic value of SF Sustainable Property based on widely used predictive technical indicators. In general, we focus on analyzing SFPF Fund price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build SF Sustainable'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 SF Sustainable's intrinsic value. In addition to deriving basic predictive indicators for SF Sustainable, we also check how macroeconomic factors affect SF Sustainable price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
Hype
Prediction
LowEstimatedHigh
123.68124.50125.32
Details
Intrinsic
Valuation
LowRealHigh
117.68118.50136.95
Details
Naive
Forecast
LowNextHigh
124.03124.85125.67
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
124.12125.75127.38
Details

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Other Information on Investing in SFPF Fund

SF Sustainable financial ratios help investors to determine whether SFPF 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 SFPF with respect to the benefits of owning SF Sustainable security.
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