DATA Overlap Studies Bollinger Bands
| DATA Crypto | USD 0.04 0.0002 0.49% |
| Symbol |
The output start index for this execution was thirteen with a total number of output elements of fourty-eight. The Bollinger Bands is very popular indicator that was developed by John Bollinger. It consist of three lines. DATA middle band is a simple moving average of its typical price. The upper and lower bands are (N) standard deviations above and below the middle band. The bands widen and narrow when the volatility of the price is higher or lower, respectively. The upper and lower bands can also be interpreted as price targets for DATA. When the price bounces off of the lower band and crosses the middle band, then the upper band becomes the price target.
DATA Technical Analysis Modules
Most technical analysis of DATA 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 DATA from various momentum indicators to cycle indicators. When you analyze DATA 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 | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About DATA 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 DATA. We use our internally-developed statistical techniques to arrive at the intrinsic value of DATA based on widely used predictive technical indicators. In general, we focus on analyzing DATA Crypto Coin price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build DATA'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 DATA's intrinsic value. In addition to deriving basic predictive indicators for DATA, we also check how macroeconomic factors affect DATA price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
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