CyberVein price prediction
Our price prediction is based on hi-resolution deal analysis from cryptocurrency exchanges. We are collecting and gather statistics to obtain price support levels that show most important zones witch traders want to buy or sell stocks. These buy/sell histograms showed in report combined with current trend analysis can be used to build high probability forecasting of future price trends. It also can be useful to set a price on calculated levels to be sure maximum profit was received.Disclaimer
Cryptocurrency trading involves substantial risk of loss and is not suitable for every investor. All trading strategies are used at your own risk. This page performs statistical analysis of past data and can be used for assumptions about the future only taking into account the statistical probability
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Insufficient data
Unfortunately, at the moment the amount of data on deals with CyberVein is not enough to build a model.Perhaps with an increase in the volume of transactions for this currency, we will be able to show this report later.
Highly correlated currencies
| Coin | Correlation | Links |
|---|---|---|
| Third tier | ||
OPEN Platform
OPEN
|
0.43951058 | details, prediction |
This report should be leaned to get most info about heading trends. It means that CyberVein price can be leaded by other, more mighty cryptocurrency, or maybe some market trend have affect on it.
It can be confidently asserted that any crypto currency has a significant dependence on the market as a whole and, in particular, the top 3 currencies - Bitcoin, Ethereum and Ripple, so the prediction of their prices will affect the price of CyberVein
Low correlated currencies
| Coin | Correlation | Links |
|---|---|---|
| Third tier | ||
|
OPEN Platform
OPEN
|
0.43951058 | details, prediction |
This report should be leaned to build highly diversified portfolio.
It makes sense to mention that a low correlation in this case includes not only coins whose movements are not statistically related but, on the contrary, move in opposite directions (in the case of a negative value of the parameter)