Correlation Between Sumitomo Mitsui and Karsten SA
Can any of the company-specific risk be diversified away by investing in both Sumitomo Mitsui and Karsten SA 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 Sumitomo Mitsui and Karsten SA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sumitomo Mitsui Financial and Karsten SA, you can compare the effects of market volatilities on Sumitomo Mitsui and Karsten SA 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 Sumitomo Mitsui with a short position of Karsten SA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sumitomo Mitsui and Karsten SA.
Diversification Opportunities for Sumitomo Mitsui and Karsten SA
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Sumitomo and Karsten is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding Sumitomo Mitsui Financial and Karsten SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Karsten SA and Sumitomo Mitsui 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 Sumitomo Mitsui Financial are associated (or correlated) with Karsten SA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Karsten SA has no effect on the direction of Sumitomo Mitsui i.e., Sumitomo Mitsui and Karsten SA go up and down completely randomly.
Pair Corralation between Sumitomo Mitsui and Karsten SA
Assuming the 90 days trading horizon Sumitomo Mitsui Financial is expected to generate 0.67 times more return on investment than Karsten SA. However, Sumitomo Mitsui Financial is 1.49 times less risky than Karsten SA. It trades about 0.23 of its potential returns per unit of risk. Karsten SA is currently generating about 0.06 per unit of risk. If you would invest 6,881 in Sumitomo Mitsui Financial on September 23, 2024 and sell it today you would earn a total of 2,146 from holding Sumitomo Mitsui Financial or generate 31.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 95.31% |
Values | Daily Returns |
Sumitomo Mitsui Financial vs. Karsten SA
Performance |
Timeline |
Sumitomo Mitsui Financial |
Karsten SA |
Sumitomo Mitsui and Karsten SA Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sumitomo Mitsui and Karsten SA
The main advantage of trading using opposite Sumitomo Mitsui and Karsten SA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sumitomo Mitsui position performs unexpectedly, Karsten SA 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 Karsten SA will offset losses from the drop in Karsten SA's long position.Sumitomo Mitsui vs. Palantir Technologies | Sumitomo Mitsui vs. CVS Health | Sumitomo Mitsui vs. Marvell Technology | Sumitomo Mitsui vs. Take Two Interactive Software |
Karsten SA vs. Companhia de Gs | Karsten SA vs. Springs Global Participaes | Karsten SA vs. Companhia de Tecidos | Karsten SA vs. Marcopolo SA |
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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.
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