Correlation Between Samsung Electronics and Starbucks
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and Starbucks 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 Samsung Electronics and Starbucks into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung Electronics Co and Starbucks, you can compare the effects of market volatilities on Samsung Electronics and Starbucks 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 Samsung Electronics with a short position of Starbucks. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and Starbucks.
Diversification Opportunities for Samsung Electronics and Starbucks
-0.7 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Samsung and Starbucks is -0.7. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and Starbucks in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Starbucks and Samsung Electronics 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 Samsung Electronics Co are associated (or correlated) with Starbucks. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Starbucks has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and Starbucks go up and down completely randomly.
Pair Corralation between Samsung Electronics and Starbucks
Assuming the 90 days trading horizon Samsung Electronics Co is expected to under-perform the Starbucks. In addition to that, Samsung Electronics is 1.99 times more volatile than Starbucks. It trades about -0.09 of its total potential returns per unit of risk. Starbucks is currently generating about 0.07 per unit of volatility. If you would invest 8,833 in Starbucks on September 13, 2024 and sell it today you would earn a total of 512.00 from holding Starbucks or generate 5.8% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Electronics Co vs. Starbucks
Performance |
Timeline |
Samsung Electronics |
Starbucks |
Samsung Electronics and Starbucks Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and Starbucks
The main advantage of trading using opposite Samsung Electronics and Starbucks positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, Starbucks 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 Starbucks will offset losses from the drop in Starbucks' long position.Samsung Electronics vs. Samsung Electronics Co | Samsung Electronics vs. Sony Group | Samsung Electronics vs. Superior Plus Corp | Samsung Electronics vs. SIVERS SEMICONDUCTORS AB |
Starbucks vs. Superior Plus Corp | Starbucks vs. SIVERS SEMICONDUCTORS AB | Starbucks vs. NorAm Drilling AS | Starbucks vs. Norsk Hydro ASA |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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