Correlation Between Auto Trader and BURLINGTON STORES
Can any of the company-specific risk be diversified away by investing in both Auto Trader and BURLINGTON STORES 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 Auto Trader and BURLINGTON STORES into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Auto Trader Group and BURLINGTON STORES, you can compare the effects of market volatilities on Auto Trader and BURLINGTON STORES 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 Auto Trader with a short position of BURLINGTON STORES. Check out your portfolio center. Please also check ongoing floating volatility patterns of Auto Trader and BURLINGTON STORES.
Diversification Opportunities for Auto Trader and BURLINGTON STORES
-0.34 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Auto and BURLINGTON is -0.34. Overlapping area represents the amount of risk that can be diversified away by holding Auto Trader Group and BURLINGTON STORES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BURLINGTON STORES and Auto Trader 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 Auto Trader Group are associated (or correlated) with BURLINGTON STORES. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BURLINGTON STORES has no effect on the direction of Auto Trader i.e., Auto Trader and BURLINGTON STORES go up and down completely randomly.
Pair Corralation between Auto Trader and BURLINGTON STORES
Assuming the 90 days trading horizon Auto Trader is expected to generate 39.26 times less return on investment than BURLINGTON STORES. But when comparing it to its historical volatility, Auto Trader Group is 1.07 times less risky than BURLINGTON STORES. It trades about 0.01 of its potential returns per unit of risk. BURLINGTON STORES is currently generating about 0.34 of returns per unit of risk over similar time horizon. If you would invest 23,600 in BURLINGTON STORES on September 7, 2024 and sell it today you would earn a total of 4,000 from holding BURLINGTON STORES or generate 16.95% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Auto Trader Group vs. BURLINGTON STORES
Performance |
Timeline |
Auto Trader Group |
BURLINGTON STORES |
Auto Trader and BURLINGTON STORES Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Auto Trader and BURLINGTON STORES
The main advantage of trading using opposite Auto Trader and BURLINGTON STORES positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Auto Trader position performs unexpectedly, BURLINGTON STORES 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 BURLINGTON STORES will offset losses from the drop in BURLINGTON STORES's long position.Auto Trader vs. Columbia Sportswear | Auto Trader vs. ANTA SPORTS PRODUCT | Auto Trader vs. CosmoSteel Holdings Limited | Auto Trader vs. CECO ENVIRONMENTAL |
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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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