Correlation Between 3iQ Bitcoin and BetaPro SP
Can any of the company-specific risk be diversified away by investing in both 3iQ Bitcoin and BetaPro SP 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 3iQ Bitcoin and BetaPro SP into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between 3iQ Bitcoin ETF and BetaPro SP 500, you can compare the effects of market volatilities on 3iQ Bitcoin and BetaPro SP 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 3iQ Bitcoin with a short position of BetaPro SP. Check out your portfolio center. Please also check ongoing floating volatility patterns of 3iQ Bitcoin and BetaPro SP.
Diversification Opportunities for 3iQ Bitcoin and BetaPro SP
-0.68 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between 3iQ and BetaPro is -0.68. Overlapping area represents the amount of risk that can be diversified away by holding 3iQ Bitcoin ETF and BetaPro SP 500 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BetaPro SP 500 and 3iQ Bitcoin 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 3iQ Bitcoin ETF are associated (or correlated) with BetaPro SP. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BetaPro SP 500 has no effect on the direction of 3iQ Bitcoin i.e., 3iQ Bitcoin and BetaPro SP go up and down completely randomly.
Pair Corralation between 3iQ Bitcoin and BetaPro SP
Assuming the 90 days trading horizon 3iQ Bitcoin ETF is expected to under-perform the BetaPro SP. But the etf apears to be less risky and, when comparing its historical volatility, 3iQ Bitcoin ETF is 1.38 times less risky than BetaPro SP. The etf trades about -0.04 of its potential returns per unit of risk. The BetaPro SP 500 is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 783.00 in BetaPro SP 500 on December 27, 2024 and sell it today you would earn a total of 20.00 from holding BetaPro SP 500 or generate 2.55% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
3iQ Bitcoin ETF vs. BetaPro SP 500
Performance |
Timeline |
3iQ Bitcoin ETF |
BetaPro SP 500 |
3iQ Bitcoin and BetaPro SP Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with 3iQ Bitcoin and BetaPro SP
The main advantage of trading using opposite 3iQ Bitcoin and BetaPro SP positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if 3iQ Bitcoin position performs unexpectedly, BetaPro SP 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 BetaPro SP will offset losses from the drop in BetaPro SP's long position.3iQ Bitcoin vs. 3iQ CoinShares Ether | 3iQ Bitcoin vs. NBI High Yield | 3iQ Bitcoin vs. NBI Unconstrained Fixed | 3iQ Bitcoin vs. Mackenzie Developed ex North |
BetaPro SP vs. BetaPro NASDAQ 100 2x | BetaPro SP vs. BetaPro SP 500 | BetaPro SP vs. BetaPro SP 500 | BetaPro SP 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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