Correlation Between UMC Electronics and STMicroelectronics
Can any of the company-specific risk be diversified away by investing in both UMC Electronics and STMicroelectronics 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 UMC Electronics and STMicroelectronics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between UMC Electronics Co and STMicroelectronics NV, you can compare the effects of market volatilities on UMC Electronics and STMicroelectronics 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 UMC Electronics with a short position of STMicroelectronics. Check out your portfolio center. Please also check ongoing floating volatility patterns of UMC Electronics and STMicroelectronics.
Diversification Opportunities for UMC Electronics and STMicroelectronics
0.27 | Correlation Coefficient |
Modest diversification
The 3 months correlation between UMC and STMicroelectronics is 0.27. Overlapping area represents the amount of risk that can be diversified away by holding UMC Electronics Co and STMicroelectronics NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on STMicroelectronics and UMC 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 UMC Electronics Co are associated (or correlated) with STMicroelectronics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of STMicroelectronics has no effect on the direction of UMC Electronics i.e., UMC Electronics and STMicroelectronics go up and down completely randomly.
Pair Corralation between UMC Electronics and STMicroelectronics
Assuming the 90 days horizon UMC Electronics Co is expected to generate 1.23 times more return on investment than STMicroelectronics. However, UMC Electronics is 1.23 times more volatile than STMicroelectronics NV. It trades about -0.03 of its potential returns per unit of risk. STMicroelectronics NV is currently generating about -0.07 per unit of risk. If you would invest 208.00 in UMC Electronics Co on November 7, 2024 and sell it today you would lose (28.00) from holding UMC Electronics Co or give up 13.46% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
UMC Electronics Co vs. STMicroelectronics NV
Performance |
Timeline |
UMC Electronics |
STMicroelectronics |
UMC Electronics and STMicroelectronics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with UMC Electronics and STMicroelectronics
The main advantage of trading using opposite UMC Electronics and STMicroelectronics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if UMC Electronics position performs unexpectedly, STMicroelectronics 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 STMicroelectronics will offset losses from the drop in STMicroelectronics' long position.UMC Electronics vs. ARDAGH METAL PACDL 0001 | UMC Electronics vs. BlueScope Steel Limited | UMC Electronics vs. MAANSHAN IRON H | UMC Electronics vs. ANGANG STEEL H |
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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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