Correlation Between Algorand and Ethereum Classic
Can any of the company-specific risk be diversified away by investing in both Algorand and Ethereum Classic 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 Algorand and Ethereum Classic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Algorand and Ethereum Classic, you can compare the effects of market volatilities on Algorand and Ethereum Classic 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 Algorand with a short position of Ethereum Classic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Algorand and Ethereum Classic.
Diversification Opportunities for Algorand and Ethereum Classic
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Algorand and Ethereum is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Algorand and Ethereum Classic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ethereum Classic and Algorand 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 Algorand are associated (or correlated) with Ethereum Classic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ethereum Classic has no effect on the direction of Algorand i.e., Algorand and Ethereum Classic go up and down completely randomly.
Pair Corralation between Algorand and Ethereum Classic
Assuming the 90 days trading horizon Algorand is expected to generate 1.16 times more return on investment than Ethereum Classic. However, Algorand is 1.16 times more volatile than Ethereum Classic. It trades about 0.11 of its potential returns per unit of risk. Ethereum Classic is currently generating about 0.1 per unit of risk. If you would invest 10.00 in Algorand on January 20, 2024 and sell it today you would earn a total of 8.00 from holding Algorand or generate 80.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Algorand vs. Ethereum Classic
Performance |
| Timeline |
| Algorand |
| Ethereum Classic |
Algorand and Ethereum Classic Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Algorand and Ethereum Classic
The main advantage of trading using opposite Algorand and Ethereum Classic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Algorand position performs unexpectedly, Ethereum Classic 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 Ethereum Classic will offset losses from the drop in Ethereum Classic's long position.The idea behind Algorand and Ethereum Classic 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.| Ethereum Classic vs. Bitcoin | Ethereum Classic vs. Dogecoin | Ethereum Classic vs. Bitcoin Cash | Ethereum Classic vs. Litecoin |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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