Consumer Products Fund Overlap Studies Parabolic SAR Extended

RYCAX Fund  USD 38.29  0.08  0.21%   
Consumer Products overlap studies tool provides the execution environment for running the Parabolic SAR Extended study and other technical functions against Consumer Products. Consumer Products 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 overlap studies indicators. As with most other technical indicators, the Parabolic SAR Extended study function is designed to identify and follow existing trends. Consumer Products overlay technical analysis usually involve calculating upper and lower limits of price movements based on various statistical techniques. Please specify the following input to run this model: Start Value, Offset on Reverse, AF Init Long, AF Long, AF Max Long, AF Init Short, AF Short, and AF Max Short.

Study
Start Value
Offset on Reverse
AF Init Long
AF Long
AF Max Long
AF Init Short
AF Short
AF Max Short
Execute Study
The output start index for this execution was one with a total number of output elements of sixty. The Extended Parabolic SAR indicator is used to determine the direction of Consumer Products's momentum and the point in time when it has higher than normal probability of directional change. It has more input parameters than standard Parabolic SAR indicator.

Consumer Products Technical Analysis Modules

Most technical analysis of Consumer Products 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 Products 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 Products Fund. We use our internally-developed statistical techniques to arrive at the intrinsic value of Consumer Products Fund 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 Products's daily price indicators and compare them against related drivers, such as overlap studies 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 Products's intrinsic value. In addition to deriving basic predictive indicators for Consumer Products, we also check how macroeconomic factors affect Consumer Products price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
Hype
Prediction
LowEstimatedHigh
37.2438.2939.34
Details
Intrinsic
Valuation
LowRealHigh
37.9038.9540.00
Details
Naive
Forecast
LowNextHigh
34.6835.7336.78
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
37.1641.5045.83
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Consumer Products. Your research has to be compared to or analyzed against Consumer Products' peers to derive any actionable benefits. When done correctly, Consumer Products' competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Consumer Products.

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As an individual investor, you need to find a reliable way to track all your investment portfolios' performance accurately. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing you full analytical transparency into your positions, our tools can tell you how much better you can do without increasing your risk or reducing expected return.

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Consumer Products 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 Consumer Products 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 Consumer Products will appreciate offsetting losses from the drop in the long position's value.

Consumer Products Pair Trading

Consumer Products Fund Pair Trading Analysis

The ability to find closely correlated positions to Consumer Products could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Consumer Products 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 Consumer Products - 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 Consumer Products Fund to buy it.
The correlation of Consumer Products 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 Consumer Products moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Consumer Products 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 Consumer Products 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.
Pair CorrelationCorrelation Matching

Other Information on Investing in Consumer Mutual Fund

Consumer Products 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 Products security.
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