Correlation Between Korea Electric and Cingulate Warrants
Can any of the company-specific risk be diversified away by investing in both Korea Electric and Cingulate Warrants 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 Korea Electric and Cingulate Warrants into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Korea Electric Power and Cingulate Warrants, you can compare the effects of market volatilities on Korea Electric and Cingulate Warrants 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 Korea Electric with a short position of Cingulate Warrants. Check out your portfolio center. Please also check ongoing floating volatility patterns of Korea Electric and Cingulate Warrants.
Diversification Opportunities for Korea Electric and Cingulate Warrants
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Korea and Cingulate is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Korea Electric Power and Cingulate Warrants in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cingulate Warrants and Korea Electric 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 Korea Electric Power are associated (or correlated) with Cingulate Warrants. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cingulate Warrants has no effect on the direction of Korea Electric i.e., Korea Electric and Cingulate Warrants go up and down completely randomly.
Pair Corralation between Korea Electric and Cingulate Warrants
Considering the 90-day investment horizon Korea Electric is expected to generate 223.33 times less return on investment than Cingulate Warrants. But when comparing it to its historical volatility, Korea Electric Power is 57.33 times less risky than Cingulate Warrants. It trades about 0.03 of its potential returns per unit of risk. Cingulate Warrants is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest 15.00 in Cingulate Warrants on August 31, 2024 and sell it today you would lose (11.85) from holding Cingulate Warrants or give up 79.0% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 75.4% |
Values | Daily Returns |
Korea Electric Power vs. Cingulate Warrants
Performance |
Timeline |
Korea Electric Power |
Cingulate Warrants |
Korea Electric and Cingulate Warrants Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Korea Electric and Cingulate Warrants
The main advantage of trading using opposite Korea Electric and Cingulate Warrants positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Korea Electric position performs unexpectedly, Cingulate Warrants 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 Cingulate Warrants will offset losses from the drop in Cingulate Warrants' long position.Korea Electric vs. Enel Chile SA | Korea Electric vs. Centrais Eltricas Brasileiras | Korea Electric vs. Central Puerto SA | Korea Electric vs. CMS Energy |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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