Correlation Between KB Financial and DIGITAL CHOSUN
Can any of the company-specific risk be diversified away by investing in both KB Financial and DIGITAL CHOSUN 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 KB Financial and DIGITAL CHOSUN into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KB Financial Group and DIGITAL CHOSUN, you can compare the effects of market volatilities on KB Financial and DIGITAL CHOSUN 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 KB Financial with a short position of DIGITAL CHOSUN. Check out your portfolio center. Please also check ongoing floating volatility patterns of KB Financial and DIGITAL CHOSUN.
Diversification Opportunities for KB Financial and DIGITAL CHOSUN
-0.07 | Correlation Coefficient |
Good diversification
The 3 months correlation between 105560 and DIGITAL is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding KB Financial Group and DIGITAL CHOSUN in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DIGITAL CHOSUN and KB Financial 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 KB Financial Group are associated (or correlated) with DIGITAL CHOSUN. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DIGITAL CHOSUN has no effect on the direction of KB Financial i.e., KB Financial and DIGITAL CHOSUN go up and down completely randomly.
Pair Corralation between KB Financial and DIGITAL CHOSUN
Assuming the 90 days trading horizon KB Financial Group is expected to generate 1.04 times more return on investment than DIGITAL CHOSUN. However, KB Financial is 1.04 times more volatile than DIGITAL CHOSUN. It trades about 0.06 of its potential returns per unit of risk. DIGITAL CHOSUN is currently generating about -0.03 per unit of risk. If you would invest 5,365,721 in KB Financial Group on October 15, 2024 and sell it today you would earn a total of 3,414,279 from holding KB Financial Group or generate 63.63% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
KB Financial Group vs. DIGITAL CHOSUN
Performance |
| Timeline |
| KB Financial Group |
| DIGITAL CHOSUN |
KB Financial and DIGITAL CHOSUN Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with KB Financial and DIGITAL CHOSUN
The main advantage of trading using opposite KB Financial and DIGITAL CHOSUN positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KB Financial position performs unexpectedly, DIGITAL CHOSUN 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 DIGITAL CHOSUN will offset losses from the drop in DIGITAL CHOSUN's long position.| KB Financial vs. N2Tech Co | KB Financial vs. Asiana Airlines | KB Financial vs. Daiyang Metal Co | KB Financial vs. DRB Industrial Co |
| DIGITAL CHOSUN vs. N2Tech Co | DIGITAL CHOSUN vs. Lion Chemtech Co | DIGITAL CHOSUN vs. Hankook Furniture Co | DIGITAL CHOSUN vs. A Tech Solution 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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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