Correlation Between Kumho Industrial and Daejung Chemicals
Can any of the company-specific risk be diversified away by investing in both Kumho Industrial and Daejung Chemicals 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 Kumho Industrial and Daejung Chemicals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kumho Industrial Co and Daejung Chemicals Metals, you can compare the effects of market volatilities on Kumho Industrial and Daejung Chemicals 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 Kumho Industrial with a short position of Daejung Chemicals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kumho Industrial and Daejung Chemicals.
Diversification Opportunities for Kumho Industrial and Daejung Chemicals
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Kumho and Daejung is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Kumho Industrial Co and Daejung Chemicals Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daejung Chemicals Metals and Kumho Industrial 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 Kumho Industrial Co are associated (or correlated) with Daejung Chemicals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daejung Chemicals Metals has no effect on the direction of Kumho Industrial i.e., Kumho Industrial and Daejung Chemicals go up and down completely randomly.
Pair Corralation between Kumho Industrial and Daejung Chemicals
Assuming the 90 days trading horizon Kumho Industrial Co is expected to under-perform the Daejung Chemicals. In addition to that, Kumho Industrial is 1.51 times more volatile than Daejung Chemicals Metals. It trades about -0.07 of its total potential returns per unit of risk. Daejung Chemicals Metals is currently generating about -0.08 per unit of volatility. If you would invest 1,441,000 in Daejung Chemicals Metals on September 17, 2024 and sell it today you would lose (129,000) from holding Daejung Chemicals Metals or give up 8.95% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Kumho Industrial Co vs. Daejung Chemicals Metals
Performance |
Timeline |
Kumho Industrial |
Daejung Chemicals Metals |
Kumho Industrial and Daejung Chemicals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kumho Industrial and Daejung Chemicals
The main advantage of trading using opposite Kumho Industrial and Daejung Chemicals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kumho Industrial position performs unexpectedly, Daejung Chemicals 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 Daejung Chemicals will offset losses from the drop in Daejung Chemicals' long position.Kumho Industrial vs. Samsung Electronics Co | Kumho Industrial vs. Samsung Electronics Co | Kumho Industrial vs. SK Hynix | Kumho Industrial vs. POSCO Holdings |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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