Correlation Between Osang Healthcare and Hannong Chemicals
Can any of the company-specific risk be diversified away by investing in both Osang Healthcare and Hannong Chemicals 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 Osang Healthcare and Hannong Chemicals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Osang Healthcare Co,Ltd and Hannong Chemicals, you can compare the effects of market volatilities on Osang Healthcare and Hannong Chemicals 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 Osang Healthcare with a short position of Hannong Chemicals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Osang Healthcare and Hannong Chemicals.
Diversification Opportunities for Osang Healthcare and Hannong Chemicals
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Osang and Hannong is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Osang Healthcare Co,Ltd and Hannong Chemicals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hannong Chemicals and Osang Healthcare 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 Osang Healthcare Co,Ltd are associated (or correlated) with Hannong Chemicals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hannong Chemicals has no effect on the direction of Osang Healthcare i.e., Osang Healthcare and Hannong Chemicals go up and down completely randomly.
Pair Corralation between Osang Healthcare and Hannong Chemicals
Assuming the 90 days trading horizon Osang Healthcare Co,Ltd is expected to generate 0.92 times more return on investment than Hannong Chemicals. However, Osang Healthcare Co,Ltd is 1.09 times less risky than Hannong Chemicals. It trades about -0.05 of its potential returns per unit of risk. Hannong Chemicals is currently generating about -0.18 per unit of risk. If you would invest 1,290,000 in Osang Healthcare Co,Ltd on October 6, 2024 and sell it today you would lose (141,000) from holding Osang Healthcare Co,Ltd or give up 10.93% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Osang Healthcare Co,Ltd vs. Hannong Chemicals
Performance |
Timeline |
Osang Healthcare Co,Ltd |
Hannong Chemicals |
Osang Healthcare and Hannong Chemicals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Osang Healthcare and Hannong Chemicals
The main advantage of trading using opposite Osang Healthcare and Hannong Chemicals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Osang Healthcare position performs unexpectedly, Hannong Chemicals 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 Hannong Chemicals will offset losses from the drop in Hannong Chemicals' long position.Osang Healthcare vs. Samsung Electronics Co | Osang Healthcare vs. Samsung Electronics Co | Osang Healthcare vs. LG Energy Solution | Osang Healthcare vs. SK Hynix |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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