Correlation Between Hankook Furniture and Dongil Metal
Can any of the company-specific risk be diversified away by investing in both Hankook Furniture and Dongil Metal 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 Hankook Furniture and Dongil Metal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hankook Furniture Co and Dongil Metal Co, you can compare the effects of market volatilities on Hankook Furniture and Dongil Metal 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 Hankook Furniture with a short position of Dongil Metal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hankook Furniture and Dongil Metal.
Diversification Opportunities for Hankook Furniture and Dongil Metal
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between Hankook and Dongil is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Hankook Furniture Co and Dongil Metal Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dongil Metal and Hankook Furniture 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 Hankook Furniture Co are associated (or correlated) with Dongil Metal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dongil Metal has no effect on the direction of Hankook Furniture i.e., Hankook Furniture and Dongil Metal go up and down completely randomly.
Pair Corralation between Hankook Furniture and Dongil Metal
Assuming the 90 days trading horizon Hankook Furniture is expected to generate 7.45 times less return on investment than Dongil Metal. But when comparing it to its historical volatility, Hankook Furniture Co is 3.59 times less risky than Dongil Metal. It trades about 0.1 of its potential returns per unit of risk. Dongil Metal Co is currently generating about 0.2 of returns per unit of risk over similar time horizon. If you would invest 810,000 in Dongil Metal Co on October 30, 2024 and sell it today you would earn a total of 69,000 from holding Dongil Metal Co or generate 8.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Hankook Furniture Co vs. Dongil Metal Co
Performance |
Timeline |
Hankook Furniture |
Dongil Metal |
Hankook Furniture and Dongil Metal Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hankook Furniture and Dongil Metal
The main advantage of trading using opposite Hankook Furniture and Dongil Metal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hankook Furniture position performs unexpectedly, Dongil Metal 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 Dongil Metal will offset losses from the drop in Dongil Metal's long position.Hankook Furniture vs. Samsung Electronics Co | Hankook Furniture vs. Samsung Electronics Co | Hankook Furniture vs. KB Financial Group | Hankook Furniture vs. Shinhan Financial Group |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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