Correlation Between Ether ETF and Purpose Bitcoin
Can any of the company-specific risk be diversified away by investing in both Ether ETF and Purpose Bitcoin 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 Ether ETF and Purpose Bitcoin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ether ETF CAD and Purpose Bitcoin CAD, you can compare the effects of market volatilities on Ether ETF and Purpose Bitcoin 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 Ether ETF with a short position of Purpose Bitcoin. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ether ETF and Purpose Bitcoin.
Diversification Opportunities for Ether ETF and Purpose Bitcoin
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Ether and Purpose is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding Ether ETF CAD and Purpose Bitcoin CAD in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Purpose Bitcoin CAD and Ether ETF 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 Ether ETF CAD are associated (or correlated) with Purpose Bitcoin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Purpose Bitcoin CAD has no effect on the direction of Ether ETF i.e., Ether ETF and Purpose Bitcoin go up and down completely randomly.
Pair Corralation between Ether ETF and Purpose Bitcoin
Assuming the 90 days trading horizon Ether ETF is expected to generate 3.13 times less return on investment than Purpose Bitcoin. In addition to that, Ether ETF is 1.23 times more volatile than Purpose Bitcoin CAD. It trades about 0.03 of its total potential returns per unit of risk. Purpose Bitcoin CAD is currently generating about 0.12 per unit of volatility. If you would invest 1,163 in Purpose Bitcoin CAD on September 23, 2024 and sell it today you would earn a total of 629.00 from holding Purpose Bitcoin CAD or generate 54.08% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Ether ETF CAD vs. Purpose Bitcoin CAD
Performance |
Timeline |
Ether ETF CAD |
Purpose Bitcoin CAD |
Ether ETF and Purpose Bitcoin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ether ETF and Purpose Bitcoin
The main advantage of trading using opposite Ether ETF and Purpose Bitcoin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ether ETF position performs unexpectedly, Purpose Bitcoin 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 Purpose Bitcoin will offset losses from the drop in Purpose Bitcoin's long position.Ether ETF vs. 3iQ Bitcoin ETF | Ether ETF vs. Purpose Bitcoin CAD | Ether ETF vs. 3iQ CoinShares Ether | Ether ETF vs. BetaPro Inverse Bitcoin |
Purpose Bitcoin vs. 3iQ Bitcoin ETF | Purpose Bitcoin vs. 3iQ CoinShares Ether | Purpose Bitcoin vs. BetaPro Inverse Bitcoin | Purpose Bitcoin vs. BetaPro SP 500 |
Check out your portfolio center.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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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