Correlation Between Samsung Electronics and HSBC Holdings
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and HSBC Holdings 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 HSBC Holdings 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 HSBC Holdings PLC, you can compare the effects of market volatilities on Samsung Electronics and HSBC Holdings 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 HSBC Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and HSBC Holdings.
Diversification Opportunities for Samsung Electronics and HSBC Holdings
-0.82 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Samsung and HSBC is -0.82. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and HSBC Holdings PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on HSBC Holdings PLC 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 HSBC Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of HSBC Holdings PLC has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and HSBC Holdings go up and down completely randomly.
Pair Corralation between Samsung Electronics and HSBC Holdings
Assuming the 90 days trading horizon Samsung Electronics Co is expected to under-perform the HSBC Holdings. In addition to that, Samsung Electronics is 2.91 times more volatile than HSBC Holdings PLC. It trades about -0.16 of its total potential returns per unit of risk. HSBC Holdings PLC is currently generating about 0.35 per unit of volatility. If you would invest 72,440 in HSBC Holdings PLC on September 23, 2024 and sell it today you would earn a total of 3,640 from holding HSBC Holdings PLC or generate 5.02% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Electronics Co vs. HSBC Holdings PLC
Performance |
Timeline |
Samsung Electronics |
HSBC Holdings PLC |
Samsung Electronics and HSBC Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and HSBC Holdings
The main advantage of trading using opposite Samsung Electronics and HSBC Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, HSBC Holdings 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 HSBC Holdings will offset losses from the drop in HSBC Holdings' long position.Samsung Electronics vs. Addtech | Samsung Electronics vs. Roper Technologies | Samsung Electronics vs. alstria office REIT AG | Samsung Electronics vs. Arrow Electronics |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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