Correlation Between XRP and ITC

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Can any of the company-specific risk be diversified away by investing in both XRP and ITC at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining XRP and ITC into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between XRP and ITC, you can compare the effects of market volatilities on XRP and ITC and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in XRP with a short position of ITC. Check out your portfolio center. Please also check ongoing floating volatility patterns of XRP and ITC.

Diversification Opportunities for XRP and ITC

0.47
  Correlation Coefficient
 XRP
 ITC

Very weak diversification

The 3 months correlation between XRP and ITC is 0.47. Overlapping area represents the amount of risk that can be diversified away by holding XRP and ITC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ITC and XRP is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on XRP are associated (or correlated) with ITC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ITC has no effect on the direction of XRP i.e., XRP and ITC go up and down completely randomly.

Pair Corralation between XRP and ITC

If you would invest  56.00  in XRP on September 1, 2024 and sell it today you would earn a total of  124.00  from holding XRP or generate 221.43% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy1.54%
ValuesDaily Returns

XRP  vs.  ITC

 Performance 
       Timeline  
XRP 

Risk-Adjusted Performance

24 of 100

 
Weak
 
Strong
Solid
Compared to the overall equity markets, risk-adjusted returns on investments in XRP are ranked lower than 24 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, XRP exhibited solid returns over the last few months and may actually be approaching a breakup point.
ITC 

Risk-Adjusted Performance

0 of 100

 
Weak
 
Strong
Very Weak
Over the last 90 days ITC has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound fundamental indicators, ITC is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.

XRP and ITC Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with XRP and ITC

The main advantage of trading using opposite XRP and ITC positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if XRP position performs unexpectedly, ITC 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 ITC will offset losses from the drop in ITC's long position.
The idea behind XRP and ITC pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.

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