Correlation Between DB Insurance and Dow Jones
Can any of the company-specific risk be diversified away by investing in both DB Insurance and Dow Jones 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 Dow Jones 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 Dow Jones Industrial, you can compare the effects of market volatilities on DB Insurance and Dow Jones 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 Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of DB Insurance and Dow Jones.
Diversification Opportunities for DB Insurance and Dow Jones
-0.59 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between 005830 and Dow is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding DB Insurance Co and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial 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 Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of DB Insurance i.e., DB Insurance and Dow Jones go up and down completely randomly.
Pair Corralation between DB Insurance and Dow Jones
Assuming the 90 days trading horizon DB Insurance Co is expected to generate 3.69 times more return on investment than Dow Jones. However, DB Insurance is 3.69 times more volatile than Dow Jones Industrial. It trades about 0.06 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.1 per unit of risk. If you would invest 8,717,228 in DB Insurance Co on August 25, 2024 and sell it today you would earn a total of 2,132,772 from holding DB Insurance Co or generate 24.47% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 95.79% |
| Values | Daily Returns |
DB Insurance Co vs. Dow Jones Industrial
Performance |
| Timeline |
DB Insurance and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
DB Insurance Co
Pair trading matchups for DB Insurance
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with DB Insurance and Dow Jones
The main advantage of trading using opposite DB Insurance and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DB Insurance position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.| DB Insurance vs. LG Household Healthcare | DB Insurance vs. Aprogen Healthcare Games | DB Insurance vs. Youl Chon Chemical | DB Insurance vs. Hannong Chemicals |
| Dow Jones vs. Vistra Energy Corp | Dow Jones vs. Fluence Energy | Dow Jones vs. Old Republic International | Dow Jones vs. Empresa Distribuidora y |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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