Correlation Between Hannong Chemicals and DB Insurance
Can any of the company-specific risk be diversified away by investing in both Hannong Chemicals and DB Insurance 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 Hannong Chemicals and DB Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hannong Chemicals and DB Insurance Co, you can compare the effects of market volatilities on Hannong Chemicals and DB Insurance 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 Hannong Chemicals with a short position of DB Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hannong Chemicals and DB Insurance.
Diversification Opportunities for Hannong Chemicals and DB Insurance
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hannong and 005830 is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Hannong Chemicals and DB Insurance Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DB Insurance and Hannong Chemicals 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 Hannong Chemicals are associated (or correlated) with DB Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DB Insurance has no effect on the direction of Hannong Chemicals i.e., Hannong Chemicals and DB Insurance go up and down completely randomly.
Pair Corralation between Hannong Chemicals and DB Insurance
Assuming the 90 days trading horizon Hannong Chemicals is expected to generate 1.74 times more return on investment than DB Insurance. However, Hannong Chemicals is 1.74 times more volatile than DB Insurance Co. It trades about 0.03 of its potential returns per unit of risk. DB Insurance Co is currently generating about 0.04 per unit of risk. If you would invest 1,409,000 in Hannong Chemicals on August 29, 2024 and sell it today you would earn a total of 112,000 from holding Hannong Chemicals or generate 7.95% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Hannong Chemicals vs. DB Insurance Co
Performance |
Timeline |
Hannong Chemicals |
DB Insurance |
Hannong Chemicals and DB Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hannong Chemicals and DB Insurance
The main advantage of trading using opposite Hannong Chemicals and DB Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hannong Chemicals position performs unexpectedly, DB Insurance 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 DB Insurance will offset losses from the drop in DB Insurance's long position.Hannong Chemicals vs. AptaBio Therapeutics | Hannong Chemicals vs. Daewoo SBI SPAC | Hannong Chemicals vs. Dream Security co | Hannong Chemicals vs. Microfriend |
DB Insurance vs. Cube Entertainment | DB Insurance vs. Dreamus Company | DB Insurance vs. LG Energy Solution | DB Insurance vs. Dongwon System |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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