Correlation Between GM and Ethereum Name
Can any of the company-specific risk be diversified away by investing in both GM and Ethereum Name 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 GM and Ethereum Name into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Ethereum Name Service, you can compare the effects of market volatilities on GM and Ethereum Name 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 GM with a short position of Ethereum Name. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Ethereum Name.
Diversification Opportunities for GM and Ethereum Name
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between GM and Ethereum is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Ethereum Name Service in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ethereum Name Service and GM 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 General Motors are associated (or correlated) with Ethereum Name. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ethereum Name Service has no effect on the direction of GM i.e., GM and Ethereum Name go up and down completely randomly.
Pair Corralation between GM and Ethereum Name
Allowing for the 90-day total investment horizon GM is expected to generate 11.29 times less return on investment than Ethereum Name. But when comparing it to its historical volatility, General Motors is 4.32 times less risky than Ethereum Name. It trades about 0.12 of its potential returns per unit of risk. Ethereum Name Service is currently generating about 0.31 of returns per unit of risk over similar time horizon. If you would invest 1,680 in Ethereum Name Service on August 31, 2024 and sell it today you would earn a total of 1,714 from holding Ethereum Name Service or generate 102.02% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
General Motors vs. Ethereum Name Service
Performance |
| Timeline |
| General Motors |
| Ethereum Name Service |
GM and Ethereum Name Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and Ethereum Name
The main advantage of trading using opposite GM and Ethereum Name positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Ethereum Name 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 Ethereum Name will offset losses from the drop in Ethereum Name's long position.The idea behind General Motors and Ethereum Name Service pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Ethereum Name vs. Ethereum Classic | Ethereum Name vs. Ethereum PoW | Ethereum Name vs. Staked Ether | Ethereum Name vs. EigenLayer |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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