Correlation Between Parkson Retail and Clean Energy
Can any of the company-specific risk be diversified away by investing in both Parkson Retail 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 Parkson Retail and Clean Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Parkson Retail Group and Clean Energy Fuels, you can compare the effects of market volatilities on Parkson Retail 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 Parkson Retail with a short position of Clean Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Parkson Retail and Clean Energy.
Diversification Opportunities for Parkson Retail and Clean Energy
-0.31 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Parkson and Clean is -0.31. Overlapping area represents the amount of risk that can be diversified away by holding Parkson Retail Group 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 Parkson Retail 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 Parkson Retail Group 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 Parkson Retail i.e., Parkson Retail and Clean Energy go up and down completely randomly.
Pair Corralation between Parkson Retail and Clean Energy
Assuming the 90 days trading horizon Parkson Retail is expected to generate 2.69 times less return on investment than Clean Energy. In addition to that, Parkson Retail is 1.07 times more volatile than Clean Energy Fuels. It trades about 0.05 of its total potential returns per unit of risk. Clean Energy Fuels is currently generating about 0.15 per unit of volatility. 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 Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Parkson Retail Group vs. Clean Energy Fuels
Performance |
Timeline |
Parkson Retail Group |
Clean Energy Fuels |
Parkson Retail and Clean Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Parkson Retail and Clean Energy
The main advantage of trading using opposite Parkson Retail and Clean Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Parkson Retail 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.Parkson Retail vs. SHOPRITE HDGS ADR | Parkson Retail vs. Macys Inc | Parkson Retail vs. PEPKOR LTD | Parkson Retail vs. AUREA SA INH |
Clean Energy vs. Eagle Materials | Clean Energy vs. Mitsui Chemicals | Clean Energy vs. SANOK RUBBER ZY | Clean Energy vs. EAGLE MATERIALS |
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 Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.
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