Correlation Between LG Household and Korea Petro
Can any of the company-specific risk be diversified away by investing in both LG Household and Korea Petro 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 Household and Korea Petro into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LG Household Healthcare and Korea Petro Chemical, you can compare the effects of market volatilities on LG Household and Korea Petro 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 Household with a short position of Korea Petro. Check out your portfolio center. Please also check ongoing floating volatility patterns of LG Household and Korea Petro.
Diversification Opportunities for LG Household and Korea Petro
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between 051900 and Korea is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding LG Household Healthcare and Korea Petro Chemical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Korea Petro Chemical and LG Household 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 Household Healthcare are associated (or correlated) with Korea Petro. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Korea Petro Chemical has no effect on the direction of LG Household i.e., LG Household and Korea Petro go up and down completely randomly.
Pair Corralation between LG Household and Korea Petro
Assuming the 90 days trading horizon LG Household Healthcare is expected to generate 1.02 times more return on investment than Korea Petro. However, LG Household is 1.02 times more volatile than Korea Petro Chemical. It trades about -0.1 of its potential returns per unit of risk. Korea Petro Chemical is currently generating about -0.46 per unit of risk. If you would invest 33,200,000 in LG Household Healthcare on September 2, 2024 and sell it today you would lose (2,150,000) from holding LG Household Healthcare or give up 6.48% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
LG Household Healthcare vs. Korea Petro Chemical
Performance |
| Timeline |
| LG Household Healthcare |
| Korea Petro Chemical |
LG Household and Korea Petro Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with LG Household and Korea Petro
The main advantage of trading using opposite LG Household and Korea Petro positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LG Household position performs unexpectedly, Korea Petro 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 Korea Petro will offset losses from the drop in Korea Petro's long position.| LG Household vs. Korea Real Estate | LG Household vs. Korea Ratings Co | LG Household vs. IQuest Co | LG Household vs. Wonbang Tech Co |
| Korea Petro vs. LG Chemicals | Korea Petro vs. POSCO Holdings | Korea Petro vs. Hanwha Solutions | Korea Petro 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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