SF Sustainable (Switzerland) Statistic Functions Time Series Forecast
| SFPF Fund | 124.50 0.50 0.40% |
| Symbol |
The output start index for this execution was nine with a total number of output elements of fifty-two. The Time Series Forecast uses simple linear regression to derive SF Sustainable Property best fit line over a given time period and plot it forward over user-defined time period.
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.| Cycle Indicators | ||
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| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
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.
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SF Sustainable Property pair trading
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if SF Sustainable position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in SF Sustainable will appreciate offsetting losses from the drop in the long position's value.SF Sustainable Pair Trading
SF Sustainable Property Pair Trading Analysis
The ability to find closely correlated positions to SF Sustainable could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace SF Sustainable when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back SF Sustainable - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling SF Sustainable Property to buy it.
The correlation of SF Sustainable is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as SF Sustainable moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if SF Sustainable Property moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for SF Sustainable can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.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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