Correlation Between Grayscale Bitcoin and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Grayscale Bitcoin 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 Grayscale Bitcoin and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Grayscale Bitcoin Cash and Dow Jones Industrial, you can compare the effects of market volatilities on Grayscale Bitcoin 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 Grayscale Bitcoin with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Grayscale Bitcoin and Dow Jones.
Diversification Opportunities for Grayscale Bitcoin and Dow Jones
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Grayscale and Dow is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding Grayscale Bitcoin Cash 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 Grayscale 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 Grayscale Bitcoin Cash 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 Grayscale Bitcoin i.e., Grayscale Bitcoin and Dow Jones go up and down completely randomly.
Pair Corralation between Grayscale Bitcoin and Dow Jones
Given the investment horizon of 90 days Grayscale Bitcoin Cash is expected to generate 9.72 times more return on investment than Dow Jones. However, Grayscale Bitcoin is 9.72 times more volatile than Dow Jones Industrial. It trades about 0.02 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.13 per unit of risk. If you would invest 884.00 in Grayscale Bitcoin Cash on September 15, 2024 and sell it today you would lose (114.00) from holding Grayscale Bitcoin Cash or give up 12.9% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Grayscale Bitcoin Cash vs. Dow Jones Industrial
Performance |
Timeline |
Grayscale Bitcoin and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Grayscale Bitcoin Cash
Pair trading matchups for Grayscale Bitcoin
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Grayscale Bitcoin and Dow Jones
The main advantage of trading using opposite Grayscale Bitcoin and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Grayscale Bitcoin 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.Grayscale Bitcoin vs. SPENN Technology AS | Grayscale Bitcoin vs. OFX Group Ltd | Grayscale Bitcoin vs. HUMANA INC | Grayscale Bitcoin vs. Barloworld Ltd ADR |
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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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