Correlation Between First Trust and Grayscale Bitcoin
Can any of the company-specific risk be diversified away by investing in both First Trust and Grayscale Bitcoin 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 First Trust and Grayscale Bitcoin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust SkyBridge and Grayscale Bitcoin Trust, you can compare the effects of market volatilities on First Trust and Grayscale Bitcoin 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 First Trust with a short position of Grayscale Bitcoin. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and Grayscale Bitcoin.
Diversification Opportunities for First Trust and Grayscale Bitcoin
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between First and Grayscale is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding First Trust SkyBridge and Grayscale Bitcoin Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Grayscale Bitcoin Trust and First Trust 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 First Trust SkyBridge are associated (or correlated) with Grayscale Bitcoin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Grayscale Bitcoin Trust has no effect on the direction of First Trust i.e., First Trust and Grayscale Bitcoin go up and down completely randomly.
Pair Corralation between First Trust and Grayscale Bitcoin
Given the investment horizon of 90 days First Trust is expected to generate 1.16 times less return on investment than Grayscale Bitcoin. In addition to that, First Trust is 1.23 times more volatile than Grayscale Bitcoin Trust. It trades about 0.1 of its total potential returns per unit of risk. Grayscale Bitcoin Trust is currently generating about 0.14 per unit of volatility. If you would invest 803.00 in Grayscale Bitcoin Trust on August 30, 2024 and sell it today you would earn a total of 6,879 from holding Grayscale Bitcoin Trust or generate 856.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
First Trust SkyBridge vs. Grayscale Bitcoin Trust
Performance |
Timeline |
First Trust SkyBridge |
Grayscale Bitcoin Trust |
First Trust and Grayscale Bitcoin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Trust and Grayscale Bitcoin
The main advantage of trading using opposite First Trust and Grayscale Bitcoin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, Grayscale Bitcoin 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 Grayscale Bitcoin will offset losses from the drop in Grayscale Bitcoin's long position.First Trust vs. VanEck Digital Transformation | First Trust vs. Bitwise Crypto Industry | First Trust vs. Global X Blockchain | First Trust vs. First Trust Indxx |
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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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