Correlation Between EigenLayer and Arweave
Can any of the company-specific risk be diversified away by investing in both EigenLayer and Arweave 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 Arweave into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EigenLayer and Arweave, you can compare the effects of market volatilities on EigenLayer and Arweave 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 Arweave. Check out your portfolio center. Please also check ongoing floating volatility patterns of EigenLayer and Arweave.
Diversification Opportunities for EigenLayer and Arweave
-0.6 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between EigenLayer and Arweave is -0.6. Overlapping area represents the amount of risk that can be diversified away by holding EigenLayer and Arweave in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Arweave 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 Arweave. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Arweave has no effect on the direction of EigenLayer i.e., EigenLayer and Arweave go up and down completely randomly.
Pair Corralation between EigenLayer and Arweave
Assuming the 90 days trading horizon EigenLayer is expected to generate 5.59 times less return on investment than Arweave. In addition to that, EigenLayer is 1.25 times more volatile than Arweave. It trades about 0.03 of its total potential returns per unit of risk. Arweave is currently generating about 0.2 per unit of volatility. If you would invest 1,692 in Arweave on August 27, 2024 and sell it today you would earn a total of 482.00 from holding Arweave or generate 28.49% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
EigenLayer vs. Arweave
Performance |
| Timeline |
| EigenLayer |
| Arweave |
EigenLayer and Arweave Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with EigenLayer and Arweave
The main advantage of trading using opposite EigenLayer and Arweave positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EigenLayer position performs unexpectedly, Arweave 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 Arweave will offset losses from the drop in Arweave's long position.The idea behind EigenLayer and Arweave 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 Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.
Other Complementary Tools
| Funds Screener Find actively-traded funds from around the world traded on over 30 global exchanges | |
| Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm | |
| Risk-Return Analysis View associations between returns expected from investment and the risk you assume | |
| My Watchlist Analysis Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like | |
| Correlation Analysis Reduce portfolio risk simply by holding instruments which are not perfectly correlated |