Correlation Between Burlington Stores and Franklin Street
Can any of the company-specific risk be diversified away by investing in both Burlington Stores and Franklin Street 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 Franklin Street into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Burlington Stores and Franklin Street Properties, you can compare the effects of market volatilities on Burlington Stores and Franklin Street 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 Franklin Street. Check out your portfolio center. Please also check ongoing floating volatility patterns of Burlington Stores and Franklin Street.
Diversification Opportunities for Burlington Stores and Franklin Street
0.28 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Burlington and Franklin is 0.28. Overlapping area represents the amount of risk that can be diversified away by holding Burlington Stores and Franklin Street Properties in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Franklin Street Prop 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 Franklin Street. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Franklin Street Prop has no effect on the direction of Burlington Stores i.e., Burlington Stores and Franklin Street go up and down completely randomly.
Pair Corralation between Burlington Stores and Franklin Street
Given the investment horizon of 90 days Burlington Stores is expected to generate 0.77 times more return on investment than Franklin Street. However, Burlington Stores is 1.29 times less risky than Franklin Street. It trades about 0.04 of its potential returns per unit of risk. Franklin Street Properties is currently generating about -0.01 per unit of risk. If you would invest 19,667 in Burlington Stores on September 3, 2024 and sell it today you would earn a total of 9,367 from holding Burlington Stores or generate 47.63% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Burlington Stores vs. Franklin Street Properties
Performance |
Timeline |
Burlington Stores |
Franklin Street Prop |
Burlington Stores and Franklin Street Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Burlington Stores and Franklin Street
The main advantage of trading using opposite Burlington Stores and Franklin Street positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Burlington Stores position performs unexpectedly, Franklin Street 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 Franklin Street will offset losses from the drop in Franklin Street's long position.Burlington Stores vs. The TJX Companies | Burlington Stores vs. Guess Inc | Burlington Stores vs. Urban Outfitters | Burlington Stores vs. Childrens Place |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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