Correlation Between REN and Render Network
Can any of the company-specific risk be diversified away by investing in both REN and Render Network 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 REN and Render Network into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between REN and Render Network, you can compare the effects of market volatilities on REN and Render Network 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 REN with a short position of Render Network. Check out your portfolio center. Please also check ongoing floating volatility patterns of REN and Render Network.
Diversification Opportunities for REN and Render Network
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between REN and Render is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding REN and Render Network in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Render Network and REN 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 REN are associated (or correlated) with Render Network. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Render Network has no effect on the direction of REN i.e., REN and Render Network go up and down completely randomly.
Pair Corralation between REN and Render Network
Assuming the 90 days trading horizon REN is expected to under-perform the Render Network. In addition to that, REN is 1.31 times more volatile than Render Network. It trades about -0.16 of its total potential returns per unit of risk. Render Network is currently generating about -0.12 per unit of volatility. If you would invest 678.00 in Render Network on December 30, 2024 and sell it today you would lose (330.00) from holding Render Network or give up 48.67% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
REN vs. Render Network
Performance |
Timeline |
REN |
Render Network |
REN and Render Network Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with REN and Render Network
The main advantage of trading using opposite REN and Render Network positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if REN position performs unexpectedly, Render Network 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 Render Network will offset losses from the drop in Render Network's long position.The idea behind REN and Render Network 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.Render Network vs. Render Token | Render Network vs. Staked Ether | Render Network vs. Phala Network | Render Network vs. EigenLayer |
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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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