Correlation Between Samsung Electronics and STOMO MITSUI
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and STOMO MITSUI 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 STOMO MITSUI 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 STOMO MITSUI FINL, you can compare the effects of market volatilities on Samsung Electronics and STOMO MITSUI 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 STOMO MITSUI. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and STOMO MITSUI.
Diversification Opportunities for Samsung Electronics and STOMO MITSUI
-0.66 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Samsung and STOMO is -0.66. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and STOMO MITSUI FINL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on STOMO MITSUI FINL 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 STOMO MITSUI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of STOMO MITSUI FINL has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and STOMO MITSUI go up and down completely randomly.
Pair Corralation between Samsung Electronics and STOMO MITSUI
Assuming the 90 days trading horizon Samsung Electronics Co is expected to under-perform the STOMO MITSUI. In addition to that, Samsung Electronics is 1.12 times more volatile than STOMO MITSUI FINL. It trades about -0.07 of its total potential returns per unit of risk. STOMO MITSUI FINL is currently generating about 0.18 per unit of volatility. If you would invest 1,965 in STOMO MITSUI FINL on October 15, 2024 and sell it today you would earn a total of 402.00 from holding STOMO MITSUI FINL or generate 20.46% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 96.67% |
Values | Daily Returns |
Samsung Electronics Co vs. STOMO MITSUI FINL
Performance |
Timeline |
Samsung Electronics |
STOMO MITSUI FINL |
Samsung Electronics and STOMO MITSUI Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and STOMO MITSUI
The main advantage of trading using opposite Samsung Electronics and STOMO MITSUI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, STOMO MITSUI 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 STOMO MITSUI will offset losses from the drop in STOMO MITSUI's long position.Samsung Electronics vs. X FAB Silicon Foundries | Samsung Electronics vs. Caseys General Stores | Samsung Electronics vs. Quaker Chemical | Samsung Electronics vs. H2O Retailing |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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