Correlation Between Ethereum and AXA World
Can any of the company-specific risk be diversified away by investing in both Ethereum and AXA World 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 Ethereum and AXA World into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ethereum and AXA World Funds, you can compare the effects of market volatilities on Ethereum and AXA World 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 Ethereum with a short position of AXA World. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ethereum and AXA World.
Diversification Opportunities for Ethereum and AXA World
Excellent diversification
The 3 months correlation between Ethereum and AXA is -0.69. Overlapping area represents the amount of risk that can be diversified away by holding Ethereum and AXA World Funds in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AXA World Funds and Ethereum 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 Ethereum are associated (or correlated) with AXA World. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AXA World Funds has no effect on the direction of Ethereum i.e., Ethereum and AXA World go up and down completely randomly.
Pair Corralation between Ethereum and AXA World
Assuming the 90 days trading horizon Ethereum is expected to generate 6.55 times more return on investment than AXA World. However, Ethereum is 6.55 times more volatile than AXA World Funds. It trades about 0.15 of its potential returns per unit of risk. AXA World Funds is currently generating about -0.07 per unit of risk. If you would invest 243,903 in Ethereum on October 10, 2024 and sell it today you would earn a total of 97,337 from holding Ethereum or generate 39.91% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 89.06% |
Values | Daily Returns |
Ethereum vs. AXA World Funds
Performance |
Timeline |
Ethereum |
AXA World Funds |
Ethereum and AXA World Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ethereum and AXA World
The main advantage of trading using opposite Ethereum and AXA World positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ethereum position performs unexpectedly, AXA World 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 AXA World will offset losses from the drop in AXA World's long position.The idea behind Ethereum and AXA World Funds 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.AXA World vs. AXA World Funds | AXA World vs. Esfera Robotics R | AXA World vs. R co Valor F | AXA World vs. CM AM Monplus NE |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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