Correlation Between Stronghold Digital and Terawulf
Can any of the company-specific risk be diversified away by investing in both Stronghold Digital and Terawulf 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 Stronghold Digital and Terawulf into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Stronghold Digital Mining and Terawulf, you can compare the effects of market volatilities on Stronghold Digital and Terawulf 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 Stronghold Digital with a short position of Terawulf. Check out your portfolio center. Please also check ongoing floating volatility patterns of Stronghold Digital and Terawulf.
Diversification Opportunities for Stronghold Digital and Terawulf
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Stronghold and Terawulf is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Stronghold Digital Mining and Terawulf in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Terawulf and Stronghold Digital 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 Stronghold Digital Mining are associated (or correlated) with Terawulf. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Terawulf has no effect on the direction of Stronghold Digital i.e., Stronghold Digital and Terawulf go up and down completely randomly.
Pair Corralation between Stronghold Digital and Terawulf
Given the investment horizon of 90 days Stronghold Digital is expected to generate 2.19 times less return on investment than Terawulf. In addition to that, Stronghold Digital is 1.08 times more volatile than Terawulf. It trades about 0.04 of its total potential returns per unit of risk. Terawulf is currently generating about 0.09 per unit of volatility. If you would invest 91.00 in Terawulf on August 27, 2024 and sell it today you would earn a total of 654.00 from holding Terawulf or generate 718.68% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Stronghold Digital Mining vs. Terawulf
Performance |
| Timeline |
| Stronghold Digital Mining |
| Terawulf |
Stronghold Digital and Terawulf Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Stronghold Digital and Terawulf
The main advantage of trading using opposite Stronghold Digital and Terawulf positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Stronghold Digital position performs unexpectedly, Terawulf 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 Terawulf will offset losses from the drop in Terawulf's long position.| Stronghold Digital vs. Terawulf | Stronghold Digital vs. Iris Energy | Stronghold Digital vs. Argo Blockchain PLC | Stronghold Digital vs. Bitfarms |
| Terawulf vs. PowerUp Acquisition Corp | Terawulf vs. Aurora Innovation | Terawulf vs. HUMANA INC | Terawulf vs. Aquagold International |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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