Correlation Between Choil Aluminum and LG Energy
Can any of the company-specific risk be diversified away by investing in both Choil Aluminum and LG Energy 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 Choil Aluminum and LG Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Choil Aluminum and LG Energy Solution, you can compare the effects of market volatilities on Choil Aluminum and LG Energy 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 Choil Aluminum with a short position of LG Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Choil Aluminum and LG Energy.
Diversification Opportunities for Choil Aluminum and LG Energy
0.49 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Choil and 373220 is 0.49. Overlapping area represents the amount of risk that can be diversified away by holding Choil Aluminum and LG Energy Solution in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LG Energy Solution and Choil Aluminum 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 Choil Aluminum are associated (or correlated) with LG Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LG Energy Solution has no effect on the direction of Choil Aluminum i.e., Choil Aluminum and LG Energy go up and down completely randomly.
Pair Corralation between Choil Aluminum and LG Energy
Assuming the 90 days trading horizon Choil Aluminum is expected to under-perform the LG Energy. In addition to that, Choil Aluminum is 1.24 times more volatile than LG Energy Solution. It trades about -0.02 of its total potential returns per unit of risk. LG Energy Solution is currently generating about 0.0 per unit of volatility. If you would invest 45,750,000 in LG Energy Solution on September 16, 2024 and sell it today you would lose (5,750,000) from holding LG Energy Solution or give up 12.57% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Choil Aluminum vs. LG Energy Solution
Performance |
| Timeline |
| Choil Aluminum |
| LG Energy Solution |
Choil Aluminum and LG Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Choil Aluminum and LG Energy
The main advantage of trading using opposite Choil Aluminum and LG Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Choil Aluminum position performs unexpectedly, LG Energy 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 Energy will offset losses from the drop in LG Energy's long position.| Choil Aluminum vs. Nable Communications | Choil Aluminum vs. Polaris Office Corp | Choil Aluminum vs. Shinsegae Information Communication | Choil Aluminum vs. KT Submarine Telecom |
| LG Energy vs. Dongbang Transport Logistics | LG Energy vs. Choil Aluminum | LG Energy vs. Neungyule Education | LG Energy vs. Inzi Display 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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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