CyberAgent (Germany) Volatility Indicators Average True Range
| CL2 Stock | EUR 6.70 0.05 0.74% |
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Incorrect Input. Please change your parameters or increase the time horizon required for running this function. The output start index for this execution was zero with a total number of output elements of zero. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of CyberAgent volatility. High ATR values indicate high volatility, and low values indicate low volatility.
CyberAgent Technical Analysis Modules
Most technical analysis of CyberAgent 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 CyberAgent from various momentum indicators to cycle indicators. When you analyze CyberAgent 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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About CyberAgent 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 CyberAgent. We use our internally-developed statistical techniques to arrive at the intrinsic value of CyberAgent based on widely used predictive technical indicators. In general, we focus on analyzing CyberAgent Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build CyberAgent's daily price indicators and compare them against related drivers, such as volatility indicators 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 CyberAgent's intrinsic value. In addition to deriving basic predictive indicators for CyberAgent, we also check how macroeconomic factors affect CyberAgent price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
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CyberAgent 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 CyberAgent 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 CyberAgent will appreciate offsetting losses from the drop in the long position's value.CyberAgent Pair Trading
CyberAgent Pair Trading Analysis
The ability to find closely correlated positions to CyberAgent could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace CyberAgent 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 CyberAgent - 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 CyberAgent to buy it.
The correlation of CyberAgent 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 CyberAgent moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if CyberAgent 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 CyberAgent 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 CyberAgent Stock
CyberAgent financial ratios help investors to determine whether CyberAgent Stock 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 CyberAgent with respect to the benefits of owning CyberAgent security.