Correlation Between BURLINGTON STORES and Caseys General
Can any of the company-specific risk be diversified away by investing in both BURLINGTON STORES and Caseys General 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 BURLINGTON STORES and Caseys General into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BURLINGTON STORES and Caseys General Stores, you can compare the effects of market volatilities on BURLINGTON STORES and Caseys General 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 BURLINGTON STORES with a short position of Caseys General. Check out your portfolio center. Please also check ongoing floating volatility patterns of BURLINGTON STORES and Caseys General.
Diversification Opportunities for BURLINGTON STORES and Caseys General
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between BURLINGTON and Caseys is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding BURLINGTON STORES and Caseys General Stores in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Caseys General Stores and BURLINGTON STORES 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 BURLINGTON STORES are associated (or correlated) with Caseys General. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Caseys General Stores has no effect on the direction of BURLINGTON STORES i.e., BURLINGTON STORES and Caseys General go up and down completely randomly.
Pair Corralation between BURLINGTON STORES and Caseys General
Assuming the 90 days trading horizon BURLINGTON STORES is expected to generate 1.61 times more return on investment than Caseys General. However, BURLINGTON STORES is 1.61 times more volatile than Caseys General Stores. It trades about 0.38 of its potential returns per unit of risk. Caseys General Stores is currently generating about 0.12 per unit of risk. If you would invest 23,400 in BURLINGTON STORES on September 8, 2024 and sell it today you would earn a total of 4,200 from holding BURLINGTON STORES or generate 17.95% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
BURLINGTON STORES vs. Caseys General Stores
Performance |
Timeline |
BURLINGTON STORES |
Caseys General Stores |
BURLINGTON STORES and Caseys General Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BURLINGTON STORES and Caseys General
The main advantage of trading using opposite BURLINGTON STORES and Caseys General positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BURLINGTON STORES position performs unexpectedly, Caseys General 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 Caseys General will offset losses from the drop in Caseys General's long position.BURLINGTON STORES vs. LG Display Co | BURLINGTON STORES vs. PLAYMATES TOYS | BURLINGTON STORES vs. Sumitomo Rubber Industries | BURLINGTON STORES vs. Vulcan Materials |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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