Correlation Between Samsung Electronics and Clean Energy
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics 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 Samsung Electronics and Clean Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung Electronics Co and Clean Energy Fuels, you can compare the effects of market volatilities on Samsung Electronics 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 Samsung Electronics with a short position of Clean Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and Clean Energy.
Diversification Opportunities for Samsung Electronics and Clean Energy
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Samsung and Clean is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co 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 Samsung Electronics 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 Samsung Electronics Co 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 Samsung Electronics i.e., Samsung Electronics and Clean Energy go up and down completely randomly.
Pair Corralation between Samsung Electronics and Clean Energy
Assuming the 90 days trading horizon Samsung Electronics is expected to generate 2.17 times less return on investment than Clean Energy. But when comparing it to its historical volatility, Samsung Electronics Co is 2.24 times less risky than Clean Energy. It trades about 0.16 of its potential returns per unit of risk. Clean Energy Fuels is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 123.00 in Clean Energy Fuels on April 22, 2025 and sell it today you would earn a total of 53.00 from holding Clean Energy Fuels or generate 43.09% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Electronics Co vs. Clean Energy Fuels
Performance |
Timeline |
Samsung Electronics |
Clean Energy Fuels |
Samsung Electronics and Clean Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and Clean Energy
The main advantage of trading using opposite Samsung Electronics and Clean Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics 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.Samsung Electronics vs. Samsung Electronics Co | Samsung Electronics vs. Microsoft | Samsung Electronics vs. Tencent Holdings |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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