Correlation Between Burlington Stores, and Visa
Can any of the company-specific risk be diversified away by investing in both Burlington Stores, and Visa 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 Visa into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Burlington Stores, and Visa Inc, you can compare the effects of market volatilities on Burlington Stores, and Visa 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 Visa. Check out your portfolio center. Please also check ongoing floating volatility patterns of Burlington Stores, and Visa.
Diversification Opportunities for Burlington Stores, and Visa
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Burlington and Visa is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Burlington Stores, and Visa Inc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Visa Inc 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 Visa. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Visa Inc has no effect on the direction of Burlington Stores, i.e., Burlington Stores, and Visa go up and down completely randomly.
Pair Corralation between Burlington Stores, and Visa
Assuming the 90 days trading horizon Burlington Stores, is expected to generate 0.58 times more return on investment than Visa. However, Burlington Stores, is 1.72 times less risky than Visa. It trades about -0.05 of its potential returns per unit of risk. Visa Inc is currently generating about -0.05 per unit of risk. If you would invest 5,976 in Burlington Stores, on October 12, 2024 and sell it today you would lose (50.00) from holding Burlington Stores, or give up 0.84% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 88.89% |
| Values | Daily Returns |
Burlington Stores, vs. Visa Inc
Performance |
| Timeline |
| Burlington Stores, |
| Visa Inc |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Good
Burlington Stores, and Visa Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Burlington Stores, and Visa
The main advantage of trading using opposite Burlington Stores, and Visa positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Burlington Stores, position performs unexpectedly, Visa 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 Visa will offset losses from the drop in Visa's long position.| Burlington Stores, vs. Zoom Video Communications | Burlington Stores, vs. Chunghwa Telecom Co, | Burlington Stores, vs. T Mobile | Burlington Stores, vs. Telecomunicaes Brasileiras SA |
| Visa vs. Telecomunicaes Brasileiras SA | Visa vs. Microchip Technology Incorporated | Visa vs. Verizon Communications | Visa vs. DXC Technology |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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