Correlation Between KB Financial and KCC Engineering
Can any of the company-specific risk be diversified away by investing in both KB Financial and KCC Engineering 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 KCC Engineering 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 KCC Engineering Construction, you can compare the effects of market volatilities on KB Financial and KCC Engineering 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 KCC Engineering. Check out your portfolio center. Please also check ongoing floating volatility patterns of KB Financial and KCC Engineering.
Diversification Opportunities for KB Financial and KCC Engineering
-0.41 | Correlation Coefficient |
Very good diversification
The 3 months correlation between 105560 and KCC is -0.41. Overlapping area represents the amount of risk that can be diversified away by holding KB Financial Group and KCC Engineering Construction in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KCC Engineering Cons 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 KCC Engineering. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KCC Engineering Cons has no effect on the direction of KB Financial i.e., KB Financial and KCC Engineering go up and down completely randomly.
Pair Corralation between KB Financial and KCC Engineering
Assuming the 90 days trading horizon KB Financial Group is expected to under-perform the KCC Engineering. In addition to that, KB Financial is 2.38 times more volatile than KCC Engineering Construction. It trades about -0.17 of its total potential returns per unit of risk. KCC Engineering Construction is currently generating about 0.05 per unit of volatility. If you would invest 405,000 in KCC Engineering Construction on September 22, 2024 and sell it today you would earn a total of 5,000 from holding KCC Engineering Construction or generate 1.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
KB Financial Group vs. KCC Engineering Construction
Performance |
Timeline |
KB Financial Group |
KCC Engineering Cons |
KB Financial and KCC Engineering Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KB Financial and KCC Engineering
The main advantage of trading using opposite KB Financial and KCC Engineering positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KB Financial position performs unexpectedly, KCC Engineering 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 KCC Engineering will offset losses from the drop in KCC Engineering's long position.KB Financial vs. Atinum Investment Co | KB Financial vs. SV Investment | KB Financial vs. KyungIn Electronics Co | KB Financial vs. DSC Investment |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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