Correlation Between Hanil Chemical and Dongnam Chemical
Can any of the company-specific risk be diversified away by investing in both Hanil Chemical and Dongnam Chemical 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 Hanil Chemical and Dongnam Chemical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hanil Chemical Ind and Dongnam Chemical Co, you can compare the effects of market volatilities on Hanil Chemical and Dongnam Chemical 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 Hanil Chemical with a short position of Dongnam Chemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hanil Chemical and Dongnam Chemical.
Diversification Opportunities for Hanil Chemical and Dongnam Chemical
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hanil and Dongnam is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Hanil Chemical Ind and Dongnam Chemical Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dongnam Chemical and Hanil Chemical 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 Hanil Chemical Ind are associated (or correlated) with Dongnam Chemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dongnam Chemical has no effect on the direction of Hanil Chemical i.e., Hanil Chemical and Dongnam Chemical go up and down completely randomly.
Pair Corralation between Hanil Chemical and Dongnam Chemical
Assuming the 90 days trading horizon Hanil Chemical is expected to generate 1.43 times less return on investment than Dongnam Chemical. In addition to that, Hanil Chemical is 1.59 times more volatile than Dongnam Chemical Co. It trades about 0.08 of its total potential returns per unit of risk. Dongnam Chemical Co is currently generating about 0.19 per unit of volatility. If you would invest 2,908,756 in Dongnam Chemical Co on December 4, 2024 and sell it today you would earn a total of 516,244 from holding Dongnam Chemical Co or generate 17.75% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.28% |
Values | Daily Returns |
Hanil Chemical Ind vs. Dongnam Chemical Co
Performance |
Timeline |
Hanil Chemical Ind |
Dongnam Chemical |
Hanil Chemical and Dongnam Chemical Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hanil Chemical and Dongnam Chemical
The main advantage of trading using opposite Hanil Chemical and Dongnam Chemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hanil Chemical position performs unexpectedly, Dongnam Chemical 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 Dongnam Chemical will offset losses from the drop in Dongnam Chemical's long position.Hanil Chemical vs. PJ Metal Co | Hanil Chemical vs. Nice Information Telecommunication | Hanil Chemical vs. Aprogen Healthcare Games | Hanil Chemical vs. Digital Power Communications |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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