Correlation Between Hyundai Engineering and Korea New
Can any of the company-specific risk be diversified away by investing in both Hyundai Engineering and Korea New 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 Hyundai Engineering and Korea New into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hyundai Engineering Construction and Korea New Network, you can compare the effects of market volatilities on Hyundai Engineering and Korea New 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 Hyundai Engineering with a short position of Korea New. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hyundai Engineering and Korea New.
Diversification Opportunities for Hyundai Engineering and Korea New
-0.3 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Hyundai and Korea is -0.3. Overlapping area represents the amount of risk that can be diversified away by holding Hyundai Engineering Constructi and Korea New Network in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Korea New Network and Hyundai Engineering 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 Hyundai Engineering Construction are associated (or correlated) with Korea New. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Korea New Network has no effect on the direction of Hyundai Engineering i.e., Hyundai Engineering and Korea New go up and down completely randomly.
Pair Corralation between Hyundai Engineering and Korea New
Assuming the 90 days trading horizon Hyundai Engineering Construction is expected to generate 1.18 times more return on investment than Korea New. However, Hyundai Engineering is 1.18 times more volatile than Korea New Network. It trades about 0.17 of its potential returns per unit of risk. Korea New Network is currently generating about 0.07 per unit of risk. If you would invest 2,745,000 in Hyundai Engineering Construction on November 29, 2024 and sell it today you would earn a total of 805,000 from holding Hyundai Engineering Construction or generate 29.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Hyundai Engineering Constructi vs. Korea New Network
Performance |
Timeline |
Hyundai Engineering |
Korea New Network |
Hyundai Engineering and Korea New Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hyundai Engineering and Korea New
The main advantage of trading using opposite Hyundai Engineering and Korea New positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hyundai Engineering position performs unexpectedly, Korea New 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 New will offset losses from the drop in Korea New's long position.Hyundai Engineering vs. Wave Electronics Co | Hyundai Engineering vs. Samji Electronics Co | Hyundai Engineering vs. Shinhan Inverse Silver | Hyundai Engineering vs. Polaris Office Corp |
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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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