Correlation Between Nam Hwa and Korea Alcohol
Can any of the company-specific risk be diversified away by investing in both Nam Hwa and Korea Alcohol 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 Nam Hwa and Korea Alcohol into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Nam Hwa Construction and Korea Alcohol Industrial, you can compare the effects of market volatilities on Nam Hwa and Korea Alcohol 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 Nam Hwa with a short position of Korea Alcohol. Check out your portfolio center. Please also check ongoing floating volatility patterns of Nam Hwa and Korea Alcohol.
Diversification Opportunities for Nam Hwa and Korea Alcohol
-0.21 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Nam and Korea is -0.21. Overlapping area represents the amount of risk that can be diversified away by holding Nam Hwa Construction and Korea Alcohol Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Korea Alcohol Industrial and Nam Hwa 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 Nam Hwa Construction are associated (or correlated) with Korea Alcohol. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Korea Alcohol Industrial has no effect on the direction of Nam Hwa i.e., Nam Hwa and Korea Alcohol go up and down completely randomly.
Pair Corralation between Nam Hwa and Korea Alcohol
Assuming the 90 days trading horizon Nam Hwa Construction is expected to under-perform the Korea Alcohol. In addition to that, Nam Hwa is 1.43 times more volatile than Korea Alcohol Industrial. It trades about -0.03 of its total potential returns per unit of risk. Korea Alcohol Industrial is currently generating about -0.05 per unit of volatility. If you would invest 997,868 in Korea Alcohol Industrial on October 12, 2024 and sell it today you would lose (137,868) from holding Korea Alcohol Industrial or give up 13.82% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Nam Hwa Construction vs. Korea Alcohol Industrial
Performance |
Timeline |
Nam Hwa Construction |
Korea Alcohol Industrial |
Nam Hwa and Korea Alcohol Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Nam Hwa and Korea Alcohol
The main advantage of trading using opposite Nam Hwa and Korea Alcohol positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Nam Hwa position performs unexpectedly, Korea Alcohol 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 Korea Alcohol will offset losses from the drop in Korea Alcohol's long position.Nam Hwa vs. PI Advanced Materials | Nam Hwa vs. Solus Advanced Materials | Nam Hwa vs. Daejoo Electronic Materials | Nam Hwa vs. PJ Metal Co |
Korea Alcohol vs. Samji Electronics Co | Korea Alcohol vs. GS Engineering Construction | Korea Alcohol vs. Hansol Homedeco Co | Korea Alcohol vs. Polaris Office Corp |
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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