Correlation Between Dongkuk Steel and SeAH Bestee
Can any of the company-specific risk be diversified away by investing in both Dongkuk Steel and SeAH Bestee 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 Dongkuk Steel and SeAH Bestee into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dongkuk Steel Mill and SeAH Bestee, you can compare the effects of market volatilities on Dongkuk Steel and SeAH Bestee 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 Dongkuk Steel with a short position of SeAH Bestee. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dongkuk Steel and SeAH Bestee.
Diversification Opportunities for Dongkuk Steel and SeAH Bestee
-0.53 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Dongkuk and SeAH is -0.53. Overlapping area represents the amount of risk that can be diversified away by holding Dongkuk Steel Mill and SeAH Bestee in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SeAH Bestee and Dongkuk Steel 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 Dongkuk Steel Mill are associated (or correlated) with SeAH Bestee. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SeAH Bestee has no effect on the direction of Dongkuk Steel i.e., Dongkuk Steel and SeAH Bestee go up and down completely randomly.
Pair Corralation between Dongkuk Steel and SeAH Bestee
Assuming the 90 days trading horizon Dongkuk Steel Mill is expected to under-perform the SeAH Bestee. But the stock apears to be less risky and, when comparing its historical volatility, Dongkuk Steel Mill is 5.61 times less risky than SeAH Bestee. The stock trades about -0.31 of its potential returns per unit of risk. The SeAH Bestee is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 1,997,000 in SeAH Bestee on August 28, 2024 and sell it today you would earn a total of 113,000 from holding SeAH Bestee or generate 5.66% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Dongkuk Steel Mill vs. SeAH Bestee
Performance |
| Timeline |
| Dongkuk Steel Mill |
| SeAH Bestee |
Dongkuk Steel and SeAH Bestee Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Dongkuk Steel and SeAH Bestee
The main advantage of trading using opposite Dongkuk Steel and SeAH Bestee positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dongkuk Steel position performs unexpectedly, SeAH Bestee 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 SeAH Bestee will offset losses from the drop in SeAH Bestee's long position.| Dongkuk Steel vs. iNtRON Biotechnology | Dongkuk Steel vs. Korean Drug Co | Dongkuk Steel vs. Vitzro Tech Co | Dongkuk Steel vs. CU Tech Corp |
| SeAH Bestee vs. Sewoon Medical Co | SeAH Bestee vs. Sung Bo Chemicals | SeAH Bestee vs. Namhae Chemical | SeAH Bestee vs. Daehan Synthetic Fiber |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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