Correlation Between PAY and EigenLayer

Can any of the company-specific risk be diversified away by investing in both PAY and EigenLayer 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 PAY and EigenLayer into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between PAY and EigenLayer, you can compare the effects of market volatilities on PAY and EigenLayer 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 PAY with a short position of EigenLayer. Check out your portfolio center. Please also check ongoing floating volatility patterns of PAY and EigenLayer.

Diversification Opportunities for PAY and EigenLayer

-0.15

Correlation Coefficient

PAY  EigenLayer

Good diversification

The 3 months correlation between PAY and EigenLayer is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding PAY and EigenLayer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on EigenLayer and PAY 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 PAY are associated (or correlated) with EigenLayer. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of EigenLayer has no effect on the direction of PAY i.e., PAY and EigenLayer go up and down completely randomly.

Pair Corralation between PAY and EigenLayer

Assuming the 90 days trading horizon PAY is expected to generate 54.63 times less return on investment than EigenLayer. But when comparing it to its historical volatility, PAY is 15.05 times less risky than EigenLayer. It trades about 0.03 of its potential returns per unit of risk. EigenLayer is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest  0.00  in EigenLayer on August 23, 2024 and sell it today you would earn a total of  222.00  from holding EigenLayer or generate 9.223372036854776E16% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Insignificant
Accuracy	98.46%
Values	Daily Returns

PAY  vs.  EigenLayer

PAY

Risk-Adjusted Performance

2 of 100

Weak

Compared to the overall equity markets, risk-adjusted returns on investments in PAY are ranked lower than 2 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, PAY exhibited solid returns over the last few months and may actually be approaching a breakup point.

EigenLayer

Risk-Adjusted Performance

9 of 100

OK

Compared to the overall equity markets, risk-adjusted returns on investments in EigenLayer are ranked lower than 9 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, EigenLayer exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with PAY and EigenLayer

The main advantage of trading using opposite PAY and EigenLayer positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PAY position performs unexpectedly, EigenLayer 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 EigenLayer will offset losses from the drop in EigenLayer's long position.

The idea behind PAY and EigenLayer 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.