Correlation Between Samsung Electronics and Power Assets
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and Power Assets 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 Power Assets 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 Power Assets Holdings, you can compare the effects of market volatilities on Samsung Electronics and Power Assets 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 Power Assets. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and Power Assets.
Diversification Opportunities for Samsung Electronics and Power Assets
-0.7 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Samsung and Power is -0.7. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and Power Assets Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Power Assets Holdings 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 Power Assets. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Power Assets Holdings has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and Power Assets go up and down completely randomly.
Pair Corralation between Samsung Electronics and Power Assets
Assuming the 90 days trading horizon Samsung Electronics Co is expected to under-perform the Power Assets. In addition to that, Samsung Electronics is 1.8 times more volatile than Power Assets Holdings. It trades about -0.22 of its total potential returns per unit of risk. Power Assets Holdings is currently generating about 0.37 per unit of volatility. If you would invest 615.00 in Power Assets Holdings on October 1, 2024 and sell it today you would earn a total of 45.00 from holding Power Assets Holdings or generate 7.32% 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. Power Assets Holdings
Performance |
Timeline |
Samsung Electronics |
Power Assets Holdings |
Samsung Electronics and Power Assets Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and Power Assets
The main advantage of trading using opposite Samsung Electronics and Power Assets positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, Power Assets 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 Power Assets will offset losses from the drop in Power Assets' long position.Samsung Electronics vs. Apple Inc | Samsung Electronics vs. Apple Inc | Samsung Electronics vs. Apple Inc | Samsung Electronics vs. Apple Inc |
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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 Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
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