Correlation Between BIT Computer and LG Household
Can any of the company-specific risk be diversified away by investing in both BIT Computer 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 BIT Computer and LG Household into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BIT Computer Co and LG Household Healthcare, you can compare the effects of market volatilities on BIT Computer 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 BIT Computer with a short position of LG Household. Check out your portfolio center. Please also check ongoing floating volatility patterns of BIT Computer and LG Household.
Diversification Opportunities for BIT Computer and LG Household
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between BIT and 051900 is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding BIT Computer Co 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 BIT Computer 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 BIT Computer Co 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 BIT Computer i.e., BIT Computer and LG Household go up and down completely randomly.
Pair Corralation between BIT Computer and LG Household
Assuming the 90 days trading horizon BIT Computer Co is expected to generate 0.55 times more return on investment than LG Household. However, BIT Computer Co is 1.82 times less risky than LG Household. It trades about -0.07 of its potential returns per unit of risk. LG Household Healthcare is currently generating about -0.14 per unit of risk. If you would invest 523,000 in BIT Computer Co on August 29, 2024 and sell it today you would lose (22,000) from holding BIT Computer Co or give up 4.21% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BIT Computer Co vs. LG Household Healthcare
Performance |
| Timeline |
| BIT Computer |
| LG Household Healthcare |
BIT Computer and LG Household Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BIT Computer and LG Household
The main advantage of trading using opposite BIT Computer and LG Household positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BIT Computer 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.| BIT Computer vs. Samsung Electronics Co | BIT Computer vs. Samsung Electronics Co | BIT Computer vs. LG Energy Solution | BIT Computer vs. SK Hynix |
| LG Household vs. Samsung Electronics Co | LG Household vs. Samsung Electronics Co | LG Household vs. Hyundai Motor Co | LG Household vs. Hyundai Motor |
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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