Correlation Between DISTRICT METALS and KB Financial
Can any of the company-specific risk be diversified away by investing in both DISTRICT METALS and KB Financial 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 DISTRICT METALS and KB Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DISTRICT METALS and KB Financial Group, you can compare the effects of market volatilities on DISTRICT METALS and KB Financial 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 DISTRICT METALS with a short position of KB Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of DISTRICT METALS and KB Financial.
Diversification Opportunities for DISTRICT METALS and KB Financial
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between DISTRICT and KBIA is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding DISTRICT METALS and KB Financial Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KB Financial Group and DISTRICT METALS 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 DISTRICT METALS are associated (or correlated) with KB Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KB Financial Group has no effect on the direction of DISTRICT METALS i.e., DISTRICT METALS and KB Financial go up and down completely randomly.
Pair Corralation between DISTRICT METALS and KB Financial
Assuming the 90 days trading horizon DISTRICT METALS is expected to under-perform the KB Financial. In addition to that, DISTRICT METALS is 1.63 times more volatile than KB Financial Group. It trades about -0.14 of its total potential returns per unit of risk. KB Financial Group is currently generating about -0.22 per unit of volatility. If you would invest 5,850 in KB Financial Group on December 5, 2024 and sell it today you would lose (650.00) from holding KB Financial Group or give up 11.11% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
DISTRICT METALS vs. KB Financial Group
Performance |
| Timeline |
| DISTRICT METALS |
| KB Financial Group |
DISTRICT METALS and KB Financial Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DISTRICT METALS and KB Financial
The main advantage of trading using opposite DISTRICT METALS and KB Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DISTRICT METALS position performs unexpectedly, KB Financial 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 KB Financial will offset losses from the drop in KB Financial's long position.| DISTRICT METALS vs. BROADPEAK SA EO | DISTRICT METALS vs. CENTURIA OFFICE REIT | DISTRICT METALS vs. NAGOYA RAILROAD | DISTRICT METALS vs. SAFEROADS HLDGS |
| KB Financial vs. Guangdong Investment Limited | KB Financial vs. Harmony Gold Mining | KB Financial vs. Scottish Mortgage Investment | KB Financial vs. Eurasia Mining Plc |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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