Correlation Between DB Insurance and Cots Technology
Can any of the company-specific risk be diversified away by investing in both DB Insurance and Cots Technology 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 DB Insurance and Cots Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DB Insurance Co and Cots Technology Co, you can compare the effects of market volatilities on DB Insurance and Cots Technology 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 DB Insurance with a short position of Cots Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of DB Insurance and Cots Technology.
Diversification Opportunities for DB Insurance and Cots Technology
0.35 | Correlation Coefficient |
Weak diversification
The 3 months correlation between 005830 and Cots is 0.35. Overlapping area represents the amount of risk that can be diversified away by holding DB Insurance Co and Cots Technology Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cots Technology and DB Insurance 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 DB Insurance Co are associated (or correlated) with Cots Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cots Technology has no effect on the direction of DB Insurance i.e., DB Insurance and Cots Technology go up and down completely randomly.
Pair Corralation between DB Insurance and Cots Technology
Assuming the 90 days trading horizon DB Insurance Co is expected to generate 0.73 times more return on investment than Cots Technology. However, DB Insurance Co is 1.37 times less risky than Cots Technology. It trades about -0.03 of its potential returns per unit of risk. Cots Technology Co is currently generating about -0.08 per unit of risk. If you would invest 11,260,000 in DB Insurance Co on September 13, 2024 and sell it today you would lose (720,000) from holding DB Insurance Co or give up 6.39% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
DB Insurance Co vs. Cots Technology Co
Performance |
| Timeline |
| DB Insurance |
| Cots Technology |
DB Insurance and Cots Technology Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DB Insurance and Cots Technology
The main advantage of trading using opposite DB Insurance and Cots Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DB Insurance position performs unexpectedly, Cots Technology 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 Cots Technology will offset losses from the drop in Cots Technology's long position.| DB Insurance vs. KB Financial Group | DB Insurance vs. Shinhan Financial Group | DB Insurance vs. Hana Financial | DB Insurance vs. Woori Financial Group |
| Cots Technology vs. Cloud Air CoLtd | Cots Technology vs. Jeju Air Co | Cots Technology vs. Dongbu Insurance Co | Cots Technology vs. DB Insurance 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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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