Correlation Between Target and Samsung Electronics
Can any of the company-specific risk be diversified away by investing in both Target and Samsung Electronics 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 Target and Samsung Electronics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Target and Samsung Electronics Co, you can compare the effects of market volatilities on Target and Samsung Electronics 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 Target with a short position of Samsung Electronics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Target and Samsung Electronics.
Diversification Opportunities for Target and Samsung Electronics
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Target and Samsung is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Target and Samsung Electronics Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Samsung Electronics and Target 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 Target are associated (or correlated) with Samsung Electronics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Samsung Electronics has no effect on the direction of Target i.e., Target and Samsung Electronics go up and down completely randomly.
Pair Corralation between Target and Samsung Electronics
Assuming the 90 days trading horizon Target is expected to generate 1.22 times more return on investment than Samsung Electronics. However, Target is 1.22 times more volatile than Samsung Electronics Co. It trades about 0.03 of its potential returns per unit of risk. Samsung Electronics Co is currently generating about -0.09 per unit of risk. If you would invest 254,777 in Target on September 12, 2024 and sell it today you would earn a total of 18,223 from holding Target or generate 7.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Target vs. Samsung Electronics Co
Performance |
Timeline |
Target |
Samsung Electronics |
Target and Samsung Electronics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Target and Samsung Electronics
The main advantage of trading using opposite Target and Samsung Electronics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Target position performs unexpectedly, Samsung Electronics 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 Samsung Electronics will offset losses from the drop in Samsung Electronics' long position.Target vs. Burlington Stores | Target vs. The Select Sector | Target vs. Promotora y Operadora | Target vs. iShares Global Timber |
Samsung Electronics vs. Hoteles City Express | Samsung Electronics vs. United States Steel | Samsung Electronics vs. Grupo Sports World | Samsung Electronics vs. Monster Beverage Corp |
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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