Correlation Between EigenLayer and PAY
Can any of the company-specific risk be diversified away by investing in both EigenLayer and PAY 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 EigenLayer and PAY into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EigenLayer and PAY, you can compare the effects of market volatilities on EigenLayer and PAY 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 EigenLayer with a short position of PAY. Check out your portfolio center. Please also check ongoing floating volatility patterns of EigenLayer and PAY.
Diversification Opportunities for EigenLayer and PAY
0.63 | Correlation Coefficient |
Poor diversification
The 3 months correlation between EigenLayer and PAY is 0.63. Overlapping area represents the amount of risk that can be diversified away by holding EigenLayer and PAY in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PAY and EigenLayer 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 EigenLayer are associated (or correlated) with PAY. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PAY has no effect on the direction of EigenLayer i.e., EigenLayer and PAY go up and down completely randomly.
Pair Corralation between EigenLayer and PAY
Assuming the 90 days trading horizon EigenLayer is expected to generate 5.96 times more return on investment than PAY. However, EigenLayer is 5.96 times more volatile than PAY. It trades about 0.05 of its potential returns per unit of risk. PAY is currently generating about 0.02 per unit of risk. If you would invest 284.00 in EigenLayer on November 8, 2024 and sell it today you would lose (113.00) from holding EigenLayer or give up 39.79% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
EigenLayer vs. PAY
Performance |
| Timeline |
| EigenLayer |
| PAY |
EigenLayer and PAY Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with EigenLayer and PAY
The main advantage of trading using opposite EigenLayer and PAY positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EigenLayer position performs unexpectedly, PAY 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 PAY will offset losses from the drop in PAY's long position.The idea behind EigenLayer and PAY 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.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 Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
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