Correlation Between Doosan Heavy and LG Household
Can any of the company-specific risk be diversified away by investing in both Doosan Heavy and LG Household 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 Doosan Heavy and LG Household into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Doosan Heavy Ind and LG Household Healthcare, you can compare the effects of market volatilities on Doosan Heavy and LG Household 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 Doosan Heavy with a short position of LG Household. Check out your portfolio center. Please also check ongoing floating volatility patterns of Doosan Heavy and LG Household.
Diversification Opportunities for Doosan Heavy and LG Household
-0.48 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Doosan and 051900 is -0.48. Overlapping area represents the amount of risk that can be diversified away by holding Doosan Heavy Ind and LG Household Healthcare in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LG Household Healthcare and Doosan Heavy 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 Doosan Heavy Ind are associated (or correlated) with LG Household. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LG Household Healthcare has no effect on the direction of Doosan Heavy i.e., Doosan Heavy and LG Household go up and down completely randomly.
Pair Corralation between Doosan Heavy and LG Household
Assuming the 90 days trading horizon Doosan Heavy Ind is expected to generate 1.3 times more return on investment than LG Household. However, Doosan Heavy is 1.3 times more volatile than LG Household Healthcare. It trades about 0.0 of its potential returns per unit of risk. LG Household Healthcare is currently generating about -0.05 per unit of risk. If you would invest 1,771,000 in Doosan Heavy Ind on September 12, 2024 and sell it today you would lose (53,000) from holding Doosan Heavy Ind or give up 2.99% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Doosan Heavy Ind vs. LG Household Healthcare
Performance |
Timeline |
Doosan Heavy Ind |
LG Household Healthcare |
Doosan Heavy and LG Household Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Doosan Heavy and LG Household
The main advantage of trading using opposite Doosan Heavy and LG Household positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Doosan Heavy position performs unexpectedly, LG Household 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 Household will offset losses from the drop in LG Household's long position.Doosan Heavy vs. Histeel | Doosan Heavy vs. Alton Sports CoLtd | Doosan Heavy vs. Hankuk Steel Wire | Doosan Heavy vs. Samhyun Steel Co |
LG Household vs. Korea New Network | LG Household vs. ICD Co | LG Household vs. DYPNF CoLtd | LG Household vs. Solution Advanced Technology |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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