Correlation Between HMM and Dongil Steel
Can any of the company-specific risk be diversified away by investing in both HMM and Dongil Steel 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 HMM and Dongil Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between HMM Co and Dongil Steel Co, you can compare the effects of market volatilities on HMM and Dongil Steel 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 HMM with a short position of Dongil Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of HMM and Dongil Steel.
Diversification Opportunities for HMM and Dongil Steel
-0.03 | Correlation Coefficient |
Good diversification
The 3 months correlation between HMM and Dongil is -0.03. Overlapping area represents the amount of risk that can be diversified away by holding HMM Co and Dongil Steel Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dongil Steel and HMM 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 HMM Co are associated (or correlated) with Dongil Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dongil Steel has no effect on the direction of HMM i.e., HMM and Dongil Steel go up and down completely randomly.
Pair Corralation between HMM and Dongil Steel
Assuming the 90 days trading horizon HMM Co is expected to generate 2.38 times more return on investment than Dongil Steel. However, HMM is 2.38 times more volatile than Dongil Steel Co. It trades about 0.09 of its potential returns per unit of risk. Dongil Steel Co is currently generating about -0.17 per unit of risk. If you would invest 1,712,000 in HMM Co on September 1, 2024 and sell it today you would earn a total of 84,000 from holding HMM Co or generate 4.91% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
HMM Co vs. Dongil Steel Co
Performance |
Timeline |
HMM Co |
Dongil Steel |
HMM and Dongil Steel Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with HMM and Dongil Steel
The main advantage of trading using opposite HMM and Dongil Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if HMM position performs unexpectedly, Dongil Steel 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 Steel will offset losses from the drop in Dongil Steel's long position.The idea behind HMM Co and Dongil Steel Co pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Dongil Steel vs. Keum Kang Steel | Dongil Steel vs. Tplex Co | Dongil Steel vs. Gyeongnam Steel Co | Dongil Steel vs. Jeil Steel Mfg |
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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
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