Rupee 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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Rupee price levels prediction for next 24 hours
Next 24 hours brief prediction
Price of RUP has broken last trend and will FALL from the support level $0.0103360005Historic price levels for next 24 hours
These levels are based on local historic minimums and maximums. Weight shows the power of broken trends.
| Price | Weight(level power) | Date of formation |
|---|
Volume profile price channel in 24 hours range
Edge levels of the price channel based on volume profile report.
| Price | Description |
|---|---|
| 0.0103360005 | Maximum price support level based on 24 hours movements |
Rupee price levels prediction for next 7 days
Next 7 days brief prediction
Price of RUP has broken last trend and will FALL from the support level $0.010840002Historic price levels for next 7 days
These levels are based on local historic minimums and maximums. Weight shows the power of broken trends.
| Price | Weight(level power) | Date of formation |
|---|---|---|
| $0.07855283468961716 | Weight: 13.007 | 27 Apr 2018 |
| $0.07184852659702301 | Weight: 11.76 | 23 Oct 2017 |
| $0.069727323949337 | Weight: 8.223 | 08 Mar 2018 |
| $0.06495265662670135 | Weight: 13.992 | 26 Apr 2018 |
| $0.06489253789186478 | Weight: 12.477 | 22 Oct 2017 |
| $0.06487169861793518 | Weight: 20.617 | 09 Mar 2018 |
| $0.05033526197075844 | Weight: 8.349 | 17 May 2018 |
| $0.04967476800084114 | Weight: 15.329 | 22 Apr 2018 |
| $0.041667770594358444 | Weight: 10.24 | 19 Oct 2017 |
| $0.015842419117689133 | Weight: 12.053 | 26 May 2018 |
Volume profile price channel in 7 days range
Edge levels of the price channel based on volume profile report.
| Price | Description |
|---|---|
| 0.010840002 | Maximum price support level based on 7 days movements |
Rupee price levels prediction for next 30 days
Next 30 days brief prediction
Price of RUP has broken last trend and will FALL from the support level $0.041399997Historic price levels for next 30 days
These levels are based on local historic minimums and maximums. Weight shows the power of broken trends.
| Price | Weight(level power) | Date of formation |
|---|---|---|
| $0.18119508028030396 | Weight: 40.593 | 05 Nov 2017 |
| $0.17314478754997253 | Weight: 14.587 | 06 Feb 2018 |
| $0.16392701864242554 | Weight: 28.426 | 29 Dec 2017 |
| $0.14274603128433228 | Weight: 28.264 | 31 Oct 2017 |
| $0.13815222680568695 | Weight: 36.218 | 25 Dec 2017 |
| $0.1326572448015213 | Weight: 15.649 | 10 Dec 2017 |
| $0.13027290999889374 | Weight: 15.225 | 19 Feb 2018 |
| $0.11919382959604263 | Weight: 43.082 | 30 Oct 2017 |
| $0.06487169861793518 | Weight: 20.617 | 09 Mar 2018 |
| $0.04967476800084114 | Weight: 15.329 | 22 Apr 2018 |
Volume profile price channel in 30 days range
Edge levels of the price channel based on volume profile report.
| Price | Description |
|---|---|
| 0.041399997 | Maximum price support level based on 30 days movements |
Highly correlated currencies
| Coin | Correlation | Links |
|---|---|---|
| First tier | ||
Bitcoin
BTC
|
0.8209798 | details, prediction |
ChainLink
LINK
|
0.7785476 | details, prediction |
Monero
XMR
|
0.7783567 | details, prediction |
Litecoin
LTC
|
0.7766026 | details, prediction |
Ethereum Classic
ETC
|
0.7428114 | details, prediction |
| Second tier | ||
Bitcoin Gold
BTG
|
0.81708735 | details, prediction |
MonaCoin
MONA
|
0.8111142 | details, prediction |
DASH
DASH
|
0.80831784 | details, prediction |
NEO
NEO
|
0.80214083 | details, prediction |
QTUM
QTUM
|
0.79693645 | details, prediction |
| Third tier | ||
Phantasma
SOUL
|
0.964623 | details, prediction |
FedoraCoin
TIPS
|
0.9221229 | details, prediction |
MOAC
MOAC
|
0.9139108 | details, prediction |
Loyalcoin
LYL
|
0.90160364 | details, prediction |
Bitcoin Green
BITG
|
0.8944746 | details, prediction |
This report should be leaned to get most info about heading trends. It means that Rupee 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 Rupee
Low correlated currencies
| Coin | Correlation | Links |
|---|---|---|
| First tier | ||
Binance Coin
BNB
|
-0.18118517 | details, prediction |
SONM
SNM
|
0.4064998 | details, prediction |
TRON
TRX
|
0.44755578 | details, prediction |
Ethereum
ETH
|
0.5532812 | details, prediction |
ZCash
ZEC
|
0.5547453 | details, prediction |
| Second tier | ||
Huobi Token
HT
|
-0.3444239 | details, prediction |
True USD
TUSD
|
-0.07220862 | details, prediction |
Decred
DCR
|
-0.041496426 | details, prediction |
Theta
THETA
|
-0.0015107287 | details, prediction |
Dai
DAI
|
0.14656624 | details, prediction |
| Third tier | ||
Docademic
MTC
|
-0.7095058 | details, prediction |
WeAreSatoshi
WSX
|
-0.49285927 | details, prediction |
Bibox Token
BIX
|
-0.41506606 | details, prediction |
StakeNet
XSN
|
-0.35642287 | details, prediction |
Zilbercoin
ZBC
|
-0.3450738 | 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)