Correlation Between SK Chemicals and Duksan Hi
Can any of the company-specific risk be diversified away by investing in both SK Chemicals and Duksan Hi 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 SK Chemicals and Duksan Hi into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SK Chemicals Co and Duksan Hi Metal, you can compare the effects of market volatilities on SK Chemicals and Duksan Hi 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 SK Chemicals with a short position of Duksan Hi. Check out your portfolio center. Please also check ongoing floating volatility patterns of SK Chemicals and Duksan Hi.
Diversification Opportunities for SK Chemicals and Duksan Hi
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between 285130 and Duksan is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding SK Chemicals Co and Duksan Hi Metal in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Duksan Hi Metal and SK Chemicals 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 SK Chemicals Co are associated (or correlated) with Duksan Hi. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Duksan Hi Metal has no effect on the direction of SK Chemicals i.e., SK Chemicals and Duksan Hi go up and down completely randomly.
Pair Corralation between SK Chemicals and Duksan Hi
Assuming the 90 days trading horizon SK Chemicals Co is expected to under-perform the Duksan Hi. But the stock apears to be less risky and, when comparing its historical volatility, SK Chemicals Co is 1.65 times less risky than Duksan Hi. The stock trades about -0.43 of its potential returns per unit of risk. The Duksan Hi Metal is currently generating about -0.18 of returns per unit of risk over similar time horizon. If you would invest 412,000 in Duksan Hi Metal on November 5, 2024 and sell it today you would lose (24,500) from holding Duksan Hi Metal or give up 5.95% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
SK Chemicals Co vs. Duksan Hi Metal
Performance |
| Timeline |
| SK Chemicals |
| Duksan Hi Metal |
SK Chemicals and Duksan Hi Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SK Chemicals and Duksan Hi
The main advantage of trading using opposite SK Chemicals and Duksan Hi positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SK Chemicals position performs unexpectedly, Duksan Hi 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 Duksan Hi will offset losses from the drop in Duksan Hi's long position.| SK Chemicals vs. Dong A Steel Technology | SK Chemicals vs. Finebesteel | SK Chemicals vs. Moonbae Steel | SK Chemicals vs. Sam Yang Foods |
| Duksan Hi vs. Ssangyong Information Communication | Duksan Hi vs. Lotte Data Communication | Duksan Hi vs. Display Tech Co | Duksan Hi vs. Homecast CoLtd |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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