Correlation Between Argo Blockchain and Bitfarms
Can any of the company-specific risk be diversified away by investing in both Argo Blockchain and Bitfarms 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 Argo Blockchain and Bitfarms into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Argo Blockchain PLC and Bitfarms, you can compare the effects of market volatilities on Argo Blockchain and Bitfarms 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 Argo Blockchain with a short position of Bitfarms. Check out your portfolio center. Please also check ongoing floating volatility patterns of Argo Blockchain and Bitfarms.
Diversification Opportunities for Argo Blockchain and Bitfarms
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Argo and Bitfarms is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Argo Blockchain PLC and Bitfarms in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bitfarms and Argo Blockchain 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 Argo Blockchain PLC are associated (or correlated) with Bitfarms. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bitfarms has no effect on the direction of Argo Blockchain i.e., Argo Blockchain and Bitfarms go up and down completely randomly.
Pair Corralation between Argo Blockchain and Bitfarms
Given the investment horizon of 90 days Argo Blockchain PLC is expected to under-perform the Bitfarms. But the stock apears to be less risky and, when comparing its historical volatility, Argo Blockchain PLC is 1.09 times less risky than Bitfarms. The stock trades about -0.04 of its potential returns per unit of risk. The Bitfarms is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest 225.00 in Bitfarms on August 28, 2024 and sell it today you would lose (20.00) from holding Bitfarms or give up 8.89% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Argo Blockchain PLC vs. Bitfarms
Performance |
| Timeline |
| Argo Blockchain PLC |
| Bitfarms |
Argo Blockchain and Bitfarms Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Argo Blockchain and Bitfarms
The main advantage of trading using opposite Argo Blockchain and Bitfarms positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Argo Blockchain position performs unexpectedly, Bitfarms 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 Bitfarms will offset losses from the drop in Bitfarms' long position.| Argo Blockchain vs. PowerUp Acquisition Corp | Argo Blockchain vs. Aurora Innovation | Argo Blockchain vs. HUMANA INC | Argo Blockchain vs. Aquagold International |
| Bitfarms vs. PowerUp Acquisition Corp | Bitfarms vs. Aurora Innovation | Bitfarms vs. HUMANA INC | Bitfarms 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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