Correlation Between LG Chemicals and Hanil Chemical
Can any of the company-specific risk be diversified away by investing in both LG Chemicals and Hanil Chemical 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 LG Chemicals and Hanil Chemical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LG Chemicals and Hanil Chemical Ind, you can compare the effects of market volatilities on LG Chemicals and Hanil Chemical 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 LG Chemicals with a short position of Hanil Chemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of LG Chemicals and Hanil Chemical.
Diversification Opportunities for LG Chemicals and Hanil Chemical
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between 051910 and Hanil is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding LG Chemicals and Hanil Chemical Ind in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hanil Chemical Ind and LG 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 LG Chemicals are associated (or correlated) with Hanil Chemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hanil Chemical Ind has no effect on the direction of LG Chemicals i.e., LG Chemicals and Hanil Chemical go up and down completely randomly.
Pair Corralation between LG Chemicals and Hanil Chemical
Assuming the 90 days trading horizon LG Chemicals is expected to generate 2.16 times more return on investment than Hanil Chemical. However, LG Chemicals is 2.16 times more volatile than Hanil Chemical Ind. It trades about -0.16 of its potential returns per unit of risk. Hanil Chemical Ind is currently generating about -0.4 per unit of risk. If you would invest 25,800,000 in LG Chemicals on October 20, 2024 and sell it today you would lose (1,450,000) from holding LG Chemicals or give up 5.62% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
LG Chemicals vs. Hanil Chemical Ind
Performance |
| Timeline |
| LG Chemicals |
| Hanil Chemical Ind |
LG Chemicals and Hanil Chemical Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with LG Chemicals and Hanil Chemical
The main advantage of trading using opposite LG Chemicals and Hanil Chemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LG Chemicals position performs unexpectedly, Hanil Chemical 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 Hanil Chemical will offset losses from the drop in Hanil Chemical's long position.| LG Chemicals vs. DB Financial Investment | LG Chemicals vs. E Investment Development | LG Chemicals vs. SBI Investment KOREA | LG Chemicals vs. EBEST Investment Securities |
| Hanil Chemical vs. LG Chemicals | Hanil Chemical vs. POSCO Holdings | Hanil Chemical vs. Lotte Chemical Corp | Hanil Chemical vs. Hyundai Steel |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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