Correlation Between EV Advanced and Daechang Steel
Can any of the company-specific risk be diversified away by investing in both EV Advanced and Daechang Steel 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 EV Advanced and Daechang Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EV Advanced Material and Daechang Steel Co, you can compare the effects of market volatilities on EV Advanced and Daechang Steel 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 EV Advanced with a short position of Daechang Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of EV Advanced and Daechang Steel.
Diversification Opportunities for EV Advanced and Daechang Steel
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between 131400 and Daechang is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding EV Advanced Material and Daechang Steel Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daechang Steel and EV Advanced 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 EV Advanced Material are associated (or correlated) with Daechang Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daechang Steel has no effect on the direction of EV Advanced i.e., EV Advanced and Daechang Steel go up and down completely randomly.
Pair Corralation between EV Advanced and Daechang Steel
Assuming the 90 days trading horizon EV Advanced Material is expected to under-perform the Daechang Steel. In addition to that, EV Advanced is 2.55 times more volatile than Daechang Steel Co. It trades about -0.06 of its total potential returns per unit of risk. Daechang Steel Co is currently generating about -0.03 per unit of volatility. If you would invest 263,551 in Daechang Steel Co on October 4, 2024 and sell it today you would lose (54,051) from holding Daechang Steel Co or give up 20.51% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
EV Advanced Material vs. Daechang Steel Co
Performance |
Timeline |
EV Advanced Material |
Daechang Steel |
EV Advanced and Daechang Steel Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with EV Advanced and Daechang Steel
The main advantage of trading using opposite EV Advanced and Daechang Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EV Advanced position performs unexpectedly, Daechang Steel 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 Daechang Steel will offset losses from the drop in Daechang Steel's long position.EV Advanced vs. AptaBio Therapeutics | EV Advanced vs. Daewoo SBI SPAC | EV Advanced vs. Dream Security co | EV Advanced vs. Microfriend |
Daechang Steel vs. Soulbrain Holdings Co | Daechang Steel vs. Wonik Ips Co | Daechang Steel vs. Dongjin Semichem Co | Daechang Steel vs. Solution Advanced Technology |
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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