Correlation Between LB Investment and Keum Kang
Can any of the company-specific risk be diversified away by investing in both LB Investment and Keum Kang 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 LB Investment and Keum Kang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LB Investment and Keum Kang Steel, you can compare the effects of market volatilities on LB Investment and Keum Kang 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 LB Investment with a short position of Keum Kang. Check out your portfolio center. Please also check ongoing floating volatility patterns of LB Investment and Keum Kang.
Diversification Opportunities for LB Investment and Keum Kang
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between 309960 and Keum is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding LB Investment and Keum Kang Steel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Keum Kang Steel and LB Investment 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 LB Investment are associated (or correlated) with Keum Kang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Keum Kang Steel has no effect on the direction of LB Investment i.e., LB Investment and Keum Kang go up and down completely randomly.
Pair Corralation between LB Investment and Keum Kang
Assuming the 90 days trading horizon LB Investment is expected to under-perform the Keum Kang. But the stock apears to be less risky and, when comparing its historical volatility, LB Investment is 2.16 times less risky than Keum Kang. The stock trades about -0.28 of its potential returns per unit of risk. The Keum Kang Steel is currently generating about -0.12 of returns per unit of risk over similar time horizon. If you would invest 459,500 in Keum Kang Steel on September 5, 2024 and sell it today you would lose (44,500) from holding Keum Kang Steel or give up 9.68% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
LB Investment vs. Keum Kang Steel
Performance |
| Timeline |
| LB Investment |
| Keum Kang Steel |
LB Investment and Keum Kang Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with LB Investment and Keum Kang
The main advantage of trading using opposite LB Investment and Keum Kang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LB Investment position performs unexpectedly, Keum Kang 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 Keum Kang will offset losses from the drop in Keum Kang's long position.| LB Investment vs. Display Tech Co | LB Investment vs. Nice Information Telecommunication | LB Investment vs. Lotte Data Communication | LB Investment vs. Shinsegae Information Communication |
| Keum Kang vs. LG Chemicals | Keum Kang vs. Lotte Chemical Corp | Keum Kang vs. Hyundai Steel | Keum Kang 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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