Correlation Between Cronos and Metis Token
Can any of the company-specific risk be diversified away by investing in both Cronos and Metis Token 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 Cronos and Metis Token into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cronos and Metis Token, you can compare the effects of market volatilities on Cronos and Metis Token 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 Cronos with a short position of Metis Token. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cronos and Metis Token.
Diversification Opportunities for Cronos and Metis Token
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Cronos and Metis is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding Cronos and Metis Token in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Metis Token and Cronos 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 Cronos are associated (or correlated) with Metis Token. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Metis Token has no effect on the direction of Cronos i.e., Cronos and Metis Token go up and down completely randomly.
Pair Corralation between Cronos and Metis Token
Assuming the 90 days trading horizon Cronos is expected to generate 1.06 times more return on investment than Metis Token. However, Cronos is 1.06 times more volatile than Metis Token. It trades about -0.05 of its potential returns per unit of risk. Metis Token is currently generating about -0.21 per unit of risk. If you would invest 14.00 in Cronos on December 30, 2024 and sell it today you would lose (4.00) from holding Cronos or give up 28.57% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Cronos vs. Metis Token
Performance |
Timeline |
Cronos |
Metis Token |
Cronos and Metis Token Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cronos and Metis Token
The main advantage of trading using opposite Cronos and Metis Token positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cronos position performs unexpectedly, Metis Token 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 Metis Token will offset losses from the drop in Metis Token's long position.The idea behind Cronos and Metis Token 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.Metis Token vs. Staked Ether | Metis Token vs. Phala Network | Metis Token vs. EigenLayer | Metis Token vs. EOSDAC |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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