Correlation Between UMC Electronics and Alfa Financial
Can any of the company-specific risk be diversified away by investing in both UMC Electronics and Alfa Financial 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 Alfa Financial 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 Alfa Financial Software, you can compare the effects of market volatilities on UMC Electronics and Alfa Financial 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 Alfa Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of UMC Electronics and Alfa Financial.
Diversification Opportunities for UMC Electronics and Alfa Financial
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between UMC and Alfa is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding UMC Electronics Co and Alfa Financial Software in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alfa Financial Software 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 Alfa Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Alfa Financial Software has no effect on the direction of UMC Electronics i.e., UMC Electronics and Alfa Financial go up and down completely randomly.
Pair Corralation between UMC Electronics and Alfa Financial
Assuming the 90 days horizon UMC Electronics Co is expected to generate 1.85 times more return on investment than Alfa Financial. However, UMC Electronics is 1.85 times more volatile than Alfa Financial Software. It trades about 0.08 of its potential returns per unit of risk. Alfa Financial Software is currently generating about 0.05 per unit of risk. If you would invest 168.00 in UMC Electronics Co on December 21, 2024 and sell it today you would earn a total of 21.00 from holding UMC Electronics Co or generate 12.5% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
UMC Electronics Co vs. Alfa Financial Software
Performance |
Timeline |
UMC Electronics |
Alfa Financial Software |
UMC Electronics and Alfa Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with UMC Electronics and Alfa Financial
The main advantage of trading using opposite UMC Electronics and Alfa Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if UMC Electronics position performs unexpectedly, Alfa Financial 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 Alfa Financial will offset losses from the drop in Alfa Financial's long position.UMC Electronics vs. Jupiter Fund Management | UMC Electronics vs. MONEYSUPERMARKET | UMC Electronics vs. Maple Leaf Foods | UMC Electronics vs. AGF Management Limited |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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