Correlation Between Freshpet and Singapore Airlines
Can any of the company-specific risk be diversified away by investing in both Freshpet and Singapore Airlines 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 Freshpet and Singapore Airlines into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Freshpet and Singapore Airlines Limited, you can compare the effects of market volatilities on Freshpet and Singapore Airlines 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 Freshpet with a short position of Singapore Airlines. Check out your portfolio center. Please also check ongoing floating volatility patterns of Freshpet and Singapore Airlines.
Diversification Opportunities for Freshpet and Singapore Airlines
-0.12 | Correlation Coefficient |
Good diversification
The 3 months correlation between Freshpet and Singapore is -0.12. Overlapping area represents the amount of risk that can be diversified away by holding Freshpet and Singapore Airlines Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Singapore Airlines and Freshpet 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 Freshpet are associated (or correlated) with Singapore Airlines. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Singapore Airlines has no effect on the direction of Freshpet i.e., Freshpet and Singapore Airlines go up and down completely randomly.
Pair Corralation between Freshpet and Singapore Airlines
Assuming the 90 days horizon Freshpet is expected to under-perform the Singapore Airlines. In addition to that, Freshpet is 1.96 times more volatile than Singapore Airlines Limited. It trades about -0.18 of its total potential returns per unit of risk. Singapore Airlines Limited is currently generating about 0.11 per unit of volatility. If you would invest 448.00 in Singapore Airlines Limited on October 10, 2024 and sell it today you would earn a total of 6.00 from holding Singapore Airlines Limited or generate 1.34% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Freshpet vs. Singapore Airlines Limited
Performance |
Timeline |
Freshpet |
Singapore Airlines |
Freshpet and Singapore Airlines Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Freshpet and Singapore Airlines
The main advantage of trading using opposite Freshpet and Singapore Airlines positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Freshpet position performs unexpectedly, Singapore Airlines 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 Singapore Airlines will offset losses from the drop in Singapore Airlines' long position.Freshpet vs. UMC Electronics Co | Freshpet vs. KIMBALL ELECTRONICS | Freshpet vs. Richardson Electronics | Freshpet vs. STMicroelectronics NV |
Singapore Airlines vs. PREMIER FOODS | Singapore Airlines vs. Ebro Foods SA | Singapore Airlines vs. Performance Food Group | Singapore Airlines vs. Astral Foods Limited |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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