Correlation Between EigenLayer and CHESS

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

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

Diversification Opportunities for EigenLayer and CHESS

0.2

Correlation Coefficient

EigenLayer  CHESS

Modest diversification

The 3 months correlation between EigenLayer and CHESS is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding EigenLayer and CHESS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CHESS 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 CHESS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CHESS has no effect on the direction of EigenLayer i.e., EigenLayer and CHESS go up and down completely randomly.

Pair Corralation between EigenLayer and CHESS

Assuming the 90 days trading horizon EigenLayer is expected to generate 1.09 times more return on investment than CHESS. However, EigenLayer is 1.09 times more volatile than CHESS. It trades about 0.09 of its potential returns per unit of risk. CHESS is currently generating about 0.06 per unit of risk. If you would invest  102.00  in EigenLayer on April 25, 2025 and sell it today you would earn a total of  32.00  from holding EigenLayer or generate 31.37% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Very Weak
Accuracy	100.0%
Values	Daily Returns

EigenLayer  vs.  CHESS

EigenLayer

Risk-Adjusted Performance

OK

Compared to the overall equity markets, risk-adjusted returns on investments in EigenLayer are ranked lower than 6 (%) 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.

CHESS

Risk-Adjusted Performance

Insignificant

Compared to the overall equity markets, risk-adjusted returns on investments in CHESS are ranked lower than 4 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, CHESS exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with EigenLayer and CHESS

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

The idea behind EigenLayer and CHESS 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.

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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.