Correlation Between Ninepoint Bitcoin and BMO MSCI
Can any of the company-specific risk be diversified away by investing in both Ninepoint Bitcoin and BMO MSCI 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 Ninepoint Bitcoin and BMO MSCI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ninepoint Bitcoin ETF and BMO MSCI USA, you can compare the effects of market volatilities on Ninepoint Bitcoin and BMO MSCI 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 Ninepoint Bitcoin with a short position of BMO MSCI. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ninepoint Bitcoin and BMO MSCI.
Diversification Opportunities for Ninepoint Bitcoin and BMO MSCI
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Ninepoint and BMO is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding Ninepoint Bitcoin ETF and BMO MSCI USA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BMO MSCI USA and Ninepoint 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 Ninepoint Bitcoin ETF are associated (or correlated) with BMO MSCI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BMO MSCI USA has no effect on the direction of Ninepoint Bitcoin i.e., Ninepoint Bitcoin and BMO MSCI go up and down completely randomly.
Pair Corralation between Ninepoint Bitcoin and BMO MSCI
Assuming the 90 days trading horizon Ninepoint Bitcoin ETF is expected to generate 4.01 times more return on investment than BMO MSCI. However, Ninepoint Bitcoin is 4.01 times more volatile than BMO MSCI USA. It trades about 0.25 of its potential returns per unit of risk. BMO MSCI USA is currently generating about 0.24 per unit of risk. If you would invest 1,714 in Ninepoint Bitcoin ETF on September 17, 2024 and sell it today you would earn a total of 941.00 from holding Ninepoint Bitcoin ETF or generate 54.9% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 98.44% |
Values | Daily Returns |
Ninepoint Bitcoin ETF vs. BMO MSCI USA
Performance |
Timeline |
Ninepoint Bitcoin ETF |
BMO MSCI USA |
Ninepoint Bitcoin and BMO MSCI Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ninepoint Bitcoin and BMO MSCI
The main advantage of trading using opposite Ninepoint Bitcoin and BMO MSCI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ninepoint Bitcoin position performs unexpectedly, BMO MSCI 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 BMO MSCI will offset losses from the drop in BMO MSCI's long position.Ninepoint Bitcoin vs. 3iQ Bitcoin ETF | Ninepoint Bitcoin vs. Purpose Bitcoin CAD | Ninepoint Bitcoin vs. BMO Aggregate Bond | Ninepoint Bitcoin vs. iShares Canadian HYBrid |
BMO MSCI vs. iShares SPTSX 60 | BMO MSCI vs. iShares Core SP | BMO MSCI vs. iShares Core SPTSX | BMO MSCI vs. BMO Aggregate Bond |
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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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