Correlation Between BURLINGTON STORES and Xinhua Winshare
Can any of the company-specific risk be diversified away by investing in both BURLINGTON STORES and Xinhua Winshare 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 Xinhua Winshare into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BURLINGTON STORES and Xinhua Winshare Publishing, you can compare the effects of market volatilities on BURLINGTON STORES and Xinhua Winshare 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 Xinhua Winshare. Check out your portfolio center. Please also check ongoing floating volatility patterns of BURLINGTON STORES and Xinhua Winshare.
Diversification Opportunities for BURLINGTON STORES and Xinhua Winshare
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between BURLINGTON and Xinhua is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding BURLINGTON STORES and Xinhua Winshare Publishing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Xinhua Winshare Publ 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 Xinhua Winshare. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Xinhua Winshare Publ has no effect on the direction of BURLINGTON STORES i.e., BURLINGTON STORES and Xinhua Winshare go up and down completely randomly.
Pair Corralation between BURLINGTON STORES and Xinhua Winshare
Assuming the 90 days trading horizon BURLINGTON STORES is expected to generate 8.3 times less return on investment than Xinhua Winshare. But when comparing it to its historical volatility, BURLINGTON STORES is 1.54 times less risky than Xinhua Winshare. It trades about 0.07 of its potential returns per unit of risk. Xinhua Winshare Publishing is currently generating about 0.36 of returns per unit of risk over similar time horizon. If you would invest 123.00 in Xinhua Winshare Publishing on October 10, 2024 and sell it today you would earn a total of 17.00 from holding Xinhua Winshare Publishing or generate 13.82% 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. Xinhua Winshare Publishing
Performance |
Timeline |
BURLINGTON STORES |
Xinhua Winshare Publ |
BURLINGTON STORES and Xinhua Winshare Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BURLINGTON STORES and Xinhua Winshare
The main advantage of trading using opposite BURLINGTON STORES and Xinhua Winshare positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BURLINGTON STORES position performs unexpectedly, Xinhua Winshare 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 Xinhua Winshare will offset losses from the drop in Xinhua Winshare's long position.BURLINGTON STORES vs. Apple Inc | BURLINGTON STORES vs. Apple Inc | BURLINGTON STORES vs. Apple Inc | BURLINGTON STORES vs. Apple Inc |
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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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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