Correlation Between URBAN OUTFITTERS and SBM OFFSHORE
Can any of the company-specific risk be diversified away by investing in both URBAN OUTFITTERS and SBM OFFSHORE 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 URBAN OUTFITTERS and SBM OFFSHORE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between URBAN OUTFITTERS and SBM OFFSHORE, you can compare the effects of market volatilities on URBAN OUTFITTERS and SBM OFFSHORE 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 URBAN OUTFITTERS with a short position of SBM OFFSHORE. Check out your portfolio center. Please also check ongoing floating volatility patterns of URBAN OUTFITTERS and SBM OFFSHORE.
Diversification Opportunities for URBAN OUTFITTERS and SBM OFFSHORE
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between URBAN and SBM is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding URBAN OUTFITTERS and SBM OFFSHORE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SBM OFFSHORE and URBAN OUTFITTERS 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 URBAN OUTFITTERS are associated (or correlated) with SBM OFFSHORE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SBM OFFSHORE has no effect on the direction of URBAN OUTFITTERS i.e., URBAN OUTFITTERS and SBM OFFSHORE go up and down completely randomly.
Pair Corralation between URBAN OUTFITTERS and SBM OFFSHORE
Assuming the 90 days trading horizon URBAN OUTFITTERS is expected to generate 3.36 times more return on investment than SBM OFFSHORE. However, URBAN OUTFITTERS is 3.36 times more volatile than SBM OFFSHORE. It trades about 0.4 of its potential returns per unit of risk. SBM OFFSHORE is currently generating about -0.28 per unit of risk. If you would invest 3,600 in URBAN OUTFITTERS on September 20, 2024 and sell it today you would earn a total of 1,650 from holding URBAN OUTFITTERS or generate 45.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
URBAN OUTFITTERS vs. SBM OFFSHORE
Performance |
Timeline |
URBAN OUTFITTERS |
SBM OFFSHORE |
URBAN OUTFITTERS and SBM OFFSHORE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with URBAN OUTFITTERS and SBM OFFSHORE
The main advantage of trading using opposite URBAN OUTFITTERS and SBM OFFSHORE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if URBAN OUTFITTERS position performs unexpectedly, SBM OFFSHORE 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 SBM OFFSHORE will offset losses from the drop in SBM OFFSHORE's long position.URBAN OUTFITTERS vs. Apple Inc | URBAN OUTFITTERS vs. Apple Inc | URBAN OUTFITTERS vs. Apple Inc | URBAN OUTFITTERS vs. Microsoft |
SBM OFFSHORE vs. URBAN OUTFITTERS | SBM OFFSHORE vs. DELTA AIR LINES | SBM OFFSHORE vs. Westinghouse Air Brake | SBM OFFSHORE vs. Pentair plc |
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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