Correlation Between Fast Retailing and Check Point
Can any of the company-specific risk be diversified away by investing in both Fast Retailing and Check Point 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 Check Point 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 Check Point Software, you can compare the effects of market volatilities on Fast Retailing and Check Point 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 Check Point. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fast Retailing and Check Point.
Diversification Opportunities for Fast Retailing and Check Point
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Fast and Check is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Fast Retailing Co and Check Point Software in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Check Point Software 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 Check Point. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Check Point Software has no effect on the direction of Fast Retailing i.e., Fast Retailing and Check Point go up and down completely randomly.
Pair Corralation between Fast Retailing and Check Point
Assuming the 90 days trading horizon Fast Retailing is expected to generate 1.79 times less return on investment than Check Point. In addition to that, Fast Retailing is 1.24 times more volatile than Check Point Software. It trades about 0.16 of its total potential returns per unit of risk. Check Point Software is currently generating about 0.35 per unit of volatility. If you would invest 15,655 in Check Point Software on September 4, 2024 and sell it today you would earn a total of 1,775 from holding Check Point Software or generate 11.34% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fast Retailing Co vs. Check Point Software
Performance |
| Timeline |
| Fast Retailing |
| Check Point Software |
Fast Retailing and Check Point Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fast Retailing and Check Point
The main advantage of trading using opposite Fast Retailing and Check Point positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fast Retailing position performs unexpectedly, Check Point 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 Check Point will offset losses from the drop in Check Point's long position.| Fast Retailing vs. TOTAL GABON | Fast Retailing vs. Walgreens Boots Alliance | Fast Retailing vs. Peak Resources Limited |
| Check Point vs. TOTAL GABON | Check Point vs. Walgreens Boots Alliance | Check Point vs. Peak Resources 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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