Correlation Between DONGKUK STEEL and LG Chemicals
Can any of the company-specific risk be diversified away by investing in both DONGKUK STEEL and LG Chemicals 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 DONGKUK STEEL and LG Chemicals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DONGKUK STEEL MILL and LG Chemicals, you can compare the effects of market volatilities on DONGKUK STEEL and LG Chemicals 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 DONGKUK STEEL with a short position of LG Chemicals. Check out your portfolio center. Please also check ongoing floating volatility patterns of DONGKUK STEEL and LG Chemicals.
Diversification Opportunities for DONGKUK STEEL and LG Chemicals
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between DONGKUK and 051910 is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding DONGKUK STEEL MILL and LG Chemicals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LG Chemicals and DONGKUK STEEL 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 DONGKUK STEEL MILL are associated (or correlated) with LG Chemicals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LG Chemicals has no effect on the direction of DONGKUK STEEL i.e., DONGKUK STEEL and LG Chemicals go up and down completely randomly.
Pair Corralation between DONGKUK STEEL and LG Chemicals
Assuming the 90 days trading horizon DONGKUK STEEL MILL is expected to generate 0.74 times more return on investment than LG Chemicals. However, DONGKUK STEEL MILL is 1.36 times less risky than LG Chemicals. It trades about -0.06 of its potential returns per unit of risk. LG Chemicals is currently generating about -0.14 per unit of risk. If you would invest 855,000 in DONGKUK STEEL MILL on August 25, 2024 and sell it today you would lose (27,000) from holding DONGKUK STEEL MILL or give up 3.16% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
DONGKUK STEEL MILL vs. LG Chemicals
Performance |
| Timeline |
| DONGKUK STEEL MILL |
| LG Chemicals |
DONGKUK STEEL and LG Chemicals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DONGKUK STEEL and LG Chemicals
The main advantage of trading using opposite DONGKUK STEEL and LG Chemicals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DONGKUK STEEL position performs unexpectedly, LG Chemicals 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 LG Chemicals will offset losses from the drop in LG Chemicals' long position.| DONGKUK STEEL vs. Samsung Electronics Co | DONGKUK STEEL vs. Samsung Electronics Co | DONGKUK STEEL vs. LG Energy Solution | DONGKUK STEEL vs. SK Hynix |
| LG Chemicals vs. POSCO Holdings | LG Chemicals vs. Lotte Chemical Corp | LG Chemicals vs. Hyundai Steel | LG Chemicals vs. Dongkuk Steel Mill |
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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