Correlation Between Gyeongnam Steel and Kukil Metal
Can any of the company-specific risk be diversified away by investing in both Gyeongnam Steel and Kukil Metal 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 Gyeongnam Steel and Kukil Metal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gyeongnam Steel Co and Kukil Metal Co, you can compare the effects of market volatilities on Gyeongnam Steel and Kukil Metal 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 Gyeongnam Steel with a short position of Kukil Metal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gyeongnam Steel and Kukil Metal.
Diversification Opportunities for Gyeongnam Steel and Kukil Metal
-0.28 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Gyeongnam and Kukil is -0.28. Overlapping area represents the amount of risk that can be diversified away by holding Gyeongnam Steel Co and Kukil Metal Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kukil Metal and Gyeongnam 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 Gyeongnam Steel Co are associated (or correlated) with Kukil Metal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kukil Metal has no effect on the direction of Gyeongnam Steel i.e., Gyeongnam Steel and Kukil Metal go up and down completely randomly.
Pair Corralation between Gyeongnam Steel and Kukil Metal
Assuming the 90 days trading horizon Gyeongnam Steel Co is expected to generate 1.04 times more return on investment than Kukil Metal. However, Gyeongnam Steel is 1.04 times more volatile than Kukil Metal Co. It trades about 0.12 of its potential returns per unit of risk. Kukil Metal Co is currently generating about -0.33 per unit of risk. If you would invest 278,000 in Gyeongnam Steel Co on September 2, 2024 and sell it today you would earn a total of 11,500 from holding Gyeongnam Steel Co or generate 4.14% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Gyeongnam Steel Co vs. Kukil Metal Co
Performance |
| Timeline |
| Gyeongnam Steel |
| Kukil Metal |
Gyeongnam Steel and Kukil Metal Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Gyeongnam Steel and Kukil Metal
The main advantage of trading using opposite Gyeongnam Steel and Kukil Metal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gyeongnam Steel position performs unexpectedly, Kukil Metal 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 Kukil Metal will offset losses from the drop in Kukil Metal's long position.| Gyeongnam Steel vs. Keum Kang Steel | Gyeongnam Steel vs. Tplex Co | Gyeongnam Steel vs. Jeil Steel Mfg | Gyeongnam Steel vs. Daedong Steel Co |
| Kukil Metal vs. Keum Kang Steel | Kukil Metal vs. Tplex Co | Kukil Metal vs. Jeil Steel Mfg | Kukil Metal vs. Daedong Steel Co |
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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