Correlation Between Grayscale Ethereum and T REX
Can any of the company-specific risk be diversified away by investing in both Grayscale Ethereum and T REX 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 Grayscale Ethereum and T REX into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Grayscale Ethereum Mini and T REX 2X Long, you can compare the effects of market volatilities on Grayscale Ethereum and T REX 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 Grayscale Ethereum with a short position of T REX. Check out your portfolio center. Please also check ongoing floating volatility patterns of Grayscale Ethereum and T REX.
Diversification Opportunities for Grayscale Ethereum and T REX
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Grayscale and TSLT is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Grayscale Ethereum Mini and T REX 2X Long in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on T REX 2X and Grayscale 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 Grayscale Ethereum Mini are associated (or correlated) with T REX. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of T REX 2X has no effect on the direction of Grayscale Ethereum i.e., Grayscale Ethereum and T REX go up and down completely randomly.
Pair Corralation between Grayscale Ethereum and T REX
Considering the 90-day investment horizon Grayscale Ethereum is expected to generate 1.75 times less return on investment than T REX. But when comparing it to its historical volatility, Grayscale Ethereum Mini is 1.77 times less risky than T REX. It trades about 0.33 of its potential returns per unit of risk. T REX 2X Long is currently generating about 0.33 of returns per unit of risk over similar time horizon. If you would invest 1,614 in T REX 2X Long on September 1, 2024 and sell it today you would earn a total of 1,294 from holding T REX 2X Long or generate 80.17% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Grayscale Ethereum Mini vs. T REX 2X Long
Performance |
| Timeline |
| Grayscale Ethereum Mini |
| T REX 2X |
Grayscale Ethereum and T REX Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Grayscale Ethereum and T REX
The main advantage of trading using opposite Grayscale Ethereum and T REX positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Grayscale Ethereum position performs unexpectedly, T REX 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 T REX will offset losses from the drop in T REX's long position.| Grayscale Ethereum vs. ProShares Trust | Grayscale Ethereum vs. iShares Ethereum Trust | Grayscale Ethereum vs. ProShares Trust | Grayscale Ethereum vs. Grayscale Ethereum Trust |
| T REX vs. Tidal Trust II | T REX vs. Tidal Trust II | T REX vs. Direxion Daily META | T REX vs. Direxion Daily META |
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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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