Correlation Between KB Financial and CASI Pharmaceuticals
Can any of the company-specific risk be diversified away by investing in both KB Financial and CASI Pharmaceuticals 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 CASI Pharmaceuticals 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 CASI Pharmaceuticals, you can compare the effects of market volatilities on KB Financial and CASI Pharmaceuticals 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 CASI Pharmaceuticals. Check out your portfolio center. Please also check ongoing floating volatility patterns of KB Financial and CASI Pharmaceuticals.
Diversification Opportunities for KB Financial and CASI Pharmaceuticals
-0.81 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between KB Financial and CASI is -0.81. Overlapping area represents the amount of risk that can be diversified away by holding KB Financial Group and CASI Pharmaceuticals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CASI Pharmaceuticals 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 CASI Pharmaceuticals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CASI Pharmaceuticals has no effect on the direction of KB Financial i.e., KB Financial and CASI Pharmaceuticals go up and down completely randomly.
Pair Corralation between KB Financial and CASI Pharmaceuticals
Allowing for the 90-day total investment horizon KB Financial Group is expected to generate 0.44 times more return on investment than CASI Pharmaceuticals. However, KB Financial Group is 2.3 times less risky than CASI Pharmaceuticals. It trades about 0.24 of its potential returns per unit of risk. CASI Pharmaceuticals is currently generating about -0.06 per unit of risk. If you would invest 6,034 in KB Financial Group on April 28, 2025 and sell it today you would earn a total of 2,557 from holding KB Financial Group or generate 42.38% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
KB Financial Group vs. CASI Pharmaceuticals
Performance |
Timeline |
KB Financial Group |
CASI Pharmaceuticals |
KB Financial and CASI Pharmaceuticals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KB Financial and CASI Pharmaceuticals
The main advantage of trading using opposite KB Financial and CASI Pharmaceuticals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KB Financial position performs unexpectedly, CASI Pharmaceuticals 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 CASI Pharmaceuticals will offset losses from the drop in CASI Pharmaceuticals' long position.KB Financial vs. Shinhan Financial Group | KB Financial vs. Woori Financial Group | KB Financial vs. Korea Electric Power | KB Financial vs. Orix Corp Ads |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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