Correlation Between Fusion Fuel and SolarWindow Technologies
Can any of the company-specific risk be diversified away by investing in both Fusion Fuel and SolarWindow Technologies 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 Fusion Fuel and SolarWindow Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fusion Fuel Green and SolarWindow Technologies, you can compare the effects of market volatilities on Fusion Fuel and SolarWindow Technologies 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 Fusion Fuel with a short position of SolarWindow Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fusion Fuel and SolarWindow Technologies.
Diversification Opportunities for Fusion Fuel and SolarWindow Technologies
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Fusion and SolarWindow is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding Fusion Fuel Green and SolarWindow Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SolarWindow Technologies and Fusion Fuel 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 Fusion Fuel Green are associated (or correlated) with SolarWindow Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SolarWindow Technologies has no effect on the direction of Fusion Fuel i.e., Fusion Fuel and SolarWindow Technologies go up and down completely randomly.
Pair Corralation between Fusion Fuel and SolarWindow Technologies
Assuming the 90 days horizon Fusion Fuel Green is expected to generate 3.06 times more return on investment than SolarWindow Technologies. However, Fusion Fuel is 3.06 times more volatile than SolarWindow Technologies. It trades about -0.04 of its potential returns per unit of risk. SolarWindow Technologies is currently generating about -0.14 per unit of risk. If you would invest 4.50 in Fusion Fuel Green on August 31, 2024 and sell it today you would lose (3.00) from holding Fusion Fuel Green or give up 66.67% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Fusion Fuel Green vs. SolarWindow Technologies
Performance |
Timeline |
Fusion Fuel Green |
SolarWindow Technologies |
Fusion Fuel and SolarWindow Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fusion Fuel and SolarWindow Technologies
The main advantage of trading using opposite Fusion Fuel and SolarWindow Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fusion Fuel position performs unexpectedly, SolarWindow Technologies 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 SolarWindow Technologies will offset losses from the drop in SolarWindow Technologies' long position.Fusion Fuel vs. Fluence Energy | Fusion Fuel vs. Altus Power | Fusion Fuel vs. Energy Vault Holdings | Fusion Fuel vs. Enlight Renewable Energy |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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