Correlation Between Fast Retailing and Clean Energy
Can any of the company-specific risk be diversified away by investing in both Fast Retailing 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 Fast Retailing and Clean Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fast Retailing Co and Clean Energy Fuels, you can compare the effects of market volatilities on Fast Retailing 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 Fast Retailing with a short position of Clean Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fast Retailing and Clean Energy.
Diversification Opportunities for Fast Retailing and Clean Energy
-0.04 | Correlation Coefficient |
Good diversification
The 3 months correlation between Fast and Clean is -0.04. Overlapping area represents the amount of risk that can be diversified away by holding Fast Retailing 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 Fast Retailing 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 Fast Retailing 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 Fast Retailing i.e., Fast Retailing and Clean Energy go up and down completely randomly.
Pair Corralation between Fast Retailing and Clean Energy
Assuming the 90 days trading horizon Fast Retailing Co is expected to generate 0.45 times more return on investment than Clean Energy. However, Fast Retailing Co is 2.24 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 -0.02 per unit of risk. If you would invest 19,000 in Fast Retailing Co on September 23, 2024 and sell it today you would earn a total of 13,140 from holding Fast Retailing Co or generate 69.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Fast Retailing Co vs. Clean Energy Fuels
Performance |
Timeline |
Fast Retailing |
Clean Energy Fuels |
Fast Retailing and Clean Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fast Retailing and Clean Energy
The main advantage of trading using opposite Fast Retailing and Clean Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fast Retailing 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.Fast Retailing vs. VIENNA INSURANCE GR | Fast Retailing vs. Selective Insurance Group | Fast Retailing vs. Insurance Australia Group | Fast Retailing vs. Reinsurance Group of |
Clean Energy vs. Reliance Industries Limited | Clean Energy vs. Marathon Petroleum Corp | Clean Energy vs. Valero Energy | Clean Energy vs. Neste Oyj |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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