Correlation Between Ethereum and Compound Governance
Can any of the company-specific risk be diversified away by investing in both Ethereum and Compound Governance 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 Ethereum and Compound Governance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ethereum and Compound Governance Token, you can compare the effects of market volatilities on Ethereum and Compound Governance 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 Ethereum with a short position of Compound Governance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ethereum and Compound Governance.
Diversification Opportunities for Ethereum and Compound Governance
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Ethereum and Compound is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Ethereum and Compound Governance Token in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Compound Governance Token and Ethereum 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 Ethereum are associated (or correlated) with Compound Governance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Compound Governance Token has no effect on the direction of Ethereum i.e., Ethereum and Compound Governance go up and down completely randomly.
Pair Corralation between Ethereum and Compound Governance
Assuming the 90 days trading horizon Ethereum is expected to generate 1.31 times less return on investment than Compound Governance. But when comparing it to its historical volatility, Ethereum is 1.24 times less risky than Compound Governance. It trades about 0.18 of its potential returns per unit of risk. Compound Governance Token is currently generating about 0.19 of returns per unit of risk over similar time horizon. If you would invest 4,518 in Compound Governance Token on August 30, 2024 and sell it today you would earn a total of 2,793 from holding Compound Governance Token or generate 61.82% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Ethereum vs. Compound Governance Token
Performance |
Timeline |
Ethereum |
Compound Governance Token |
Ethereum and Compound Governance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ethereum and Compound Governance
The main advantage of trading using opposite Ethereum and Compound Governance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ethereum position performs unexpectedly, Compound Governance 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 Compound Governance will offset losses from the drop in Compound Governance's long position.Ethereum vs. Ethereum Classic | Ethereum vs. Ethereum PoW | Ethereum vs. Ethereum Name Service | Ethereum vs. Staked Ether |
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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 Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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