Correlation Between Kukil Metal and Hanjin Transportation
Can any of the company-specific risk be diversified away by investing in both Kukil Metal and Hanjin Transportation 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 Kukil Metal and Hanjin Transportation into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kukil Metal Co and Hanjin Transportation Co, you can compare the effects of market volatilities on Kukil Metal and Hanjin Transportation 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 Kukil Metal with a short position of Hanjin Transportation. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kukil Metal and Hanjin Transportation.
Diversification Opportunities for Kukil Metal and Hanjin Transportation
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Kukil and Hanjin is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Kukil Metal Co and Hanjin Transportation Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hanjin Transportation and Kukil Metal 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 Kukil Metal Co are associated (or correlated) with Hanjin Transportation. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hanjin Transportation has no effect on the direction of Kukil Metal i.e., Kukil Metal and Hanjin Transportation go up and down completely randomly.
Pair Corralation between Kukil Metal and Hanjin Transportation
Assuming the 90 days trading horizon Kukil Metal Co is expected to under-perform the Hanjin Transportation. In addition to that, Kukil Metal is 1.68 times more volatile than Hanjin Transportation Co. It trades about 0.0 of its total potential returns per unit of risk. Hanjin Transportation Co is currently generating about 0.1 per unit of volatility. If you would invest 1,881,123 in Hanjin Transportation Co on December 24, 2024 and sell it today you would earn a total of 69,877 from holding Hanjin Transportation Co or generate 3.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Kukil Metal Co vs. Hanjin Transportation Co
Performance |
Timeline |
Kukil Metal |
Hanjin Transportation |
Kukil Metal and Hanjin Transportation Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kukil Metal and Hanjin Transportation
The main advantage of trading using opposite Kukil Metal and Hanjin Transportation positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kukil Metal position performs unexpectedly, Hanjin Transportation 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 Hanjin Transportation will offset losses from the drop in Hanjin Transportation's long position.Kukil Metal vs. Samyung Trading Co | Kukil Metal vs. Stic Investments | Kukil Metal vs. Sangsangin Investment Securities | Kukil Metal vs. Leeno Industrial |
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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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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