Correlation Between Blockchain Group and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Blockchain Group and Dow Jones 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 Blockchain Group and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Blockchain Group SA and Dow Jones Industrial, you can compare the effects of market volatilities on Blockchain Group and Dow Jones 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 Blockchain Group with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Blockchain Group and Dow Jones.
Diversification Opportunities for Blockchain Group and Dow Jones
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Blockchain and Dow is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Blockchain Group SA and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and Blockchain Group 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 Blockchain Group SA are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Blockchain Group i.e., Blockchain Group and Dow Jones go up and down completely randomly.
Pair Corralation between Blockchain Group and Dow Jones
Assuming the 90 days trading horizon Blockchain Group SA is expected to generate 8.85 times more return on investment than Dow Jones. However, Blockchain Group is 8.85 times more volatile than Dow Jones Industrial. It trades about 0.06 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.15 per unit of risk. If you would invest 17.00 in Blockchain Group SA on August 29, 2024 and sell it today you would earn a total of 12.00 from holding Blockchain Group SA or generate 70.59% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.64% |
Values | Daily Returns |
Blockchain Group SA vs. Dow Jones Industrial
Performance |
Timeline |
Blockchain Group and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Blockchain Group SA
Pair trading matchups for Blockchain Group
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Blockchain Group and Dow Jones
The main advantage of trading using opposite Blockchain Group and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Blockchain Group position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.Blockchain Group vs. Adocia | Blockchain Group vs. Manitou BF SA | Blockchain Group vs. Ossiam Minimum Variance | Blockchain Group vs. Ekinops SA |
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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 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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