Correlation Between Merit Medical and Clean Energy
Can any of the company-specific risk be diversified away by investing in both Merit Medical and Clean Energy 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 Merit Medical and Clean Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Merit Medical Systems and Clean Energy Fuels, you can compare the effects of market volatilities on Merit Medical and Clean Energy 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 Merit Medical with a short position of Clean Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Merit Medical and Clean Energy.
Diversification Opportunities for Merit Medical and Clean Energy
0.19 | Correlation Coefficient |
Average diversification
The 3 months correlation between Merit and Clean is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding Merit Medical Systems and Clean Energy Fuels in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Clean Energy Fuels and Merit Medical 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 Merit Medical Systems are associated (or correlated) with Clean Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Clean Energy Fuels has no effect on the direction of Merit Medical i.e., Merit Medical and Clean Energy go up and down completely randomly.
Pair Corralation between Merit Medical and Clean Energy
Assuming the 90 days trading horizon Merit Medical Systems is expected to generate 0.42 times more return on investment than Clean Energy. However, Merit Medical Systems is 2.41 times less risky than Clean Energy. It trades about 0.07 of its potential returns per unit of risk. Clean Energy Fuels is currently generating about -0.03 per unit of risk. If you would invest 8,650 in Merit Medical Systems on September 27, 2024 and sell it today you would earn a total of 600.00 from holding Merit Medical Systems or generate 6.94% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Merit Medical Systems vs. Clean Energy Fuels
Performance |
Timeline |
Merit Medical Systems |
Clean Energy Fuels |
Merit Medical and Clean Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Merit Medical and Clean Energy
The main advantage of trading using opposite Merit Medical and Clean Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Merit Medical position performs unexpectedly, Clean Energy 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 Clean Energy will offset losses from the drop in Clean Energy's long position.Merit Medical vs. Apple Inc | Merit Medical vs. Apple Inc | Merit Medical vs. Apple Inc | Merit Medical vs. Apple Inc |
Clean Energy vs. Reliance Industries Limited | Clean Energy vs. Marathon Petroleum Corp | Clean Energy vs. Valero Energy | Clean Energy vs. NESTE OYJ UNSPADR |
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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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