Correlation Between Daebo Magnetic and Automobile
Can any of the company-specific risk be diversified away by investing in both Daebo Magnetic and Automobile 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 Daebo Magnetic and Automobile into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daebo Magnetic CoLtd and Automobile Pc, you can compare the effects of market volatilities on Daebo Magnetic and Automobile 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 Daebo Magnetic with a short position of Automobile. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daebo Magnetic and Automobile.
Diversification Opportunities for Daebo Magnetic and Automobile
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Daebo and Automobile is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding Daebo Magnetic CoLtd and Automobile Pc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Automobile Pc and Daebo Magnetic 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 Daebo Magnetic CoLtd are associated (or correlated) with Automobile. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Automobile Pc has no effect on the direction of Daebo Magnetic i.e., Daebo Magnetic and Automobile go up and down completely randomly.
Pair Corralation between Daebo Magnetic and Automobile
Assuming the 90 days trading horizon Daebo Magnetic CoLtd is expected to generate 1.08 times more return on investment than Automobile. However, Daebo Magnetic is 1.08 times more volatile than Automobile Pc. It trades about -0.04 of its potential returns per unit of risk. Automobile Pc is currently generating about -0.06 per unit of risk. If you would invest 1,347,000 in Daebo Magnetic CoLtd on September 14, 2024 and sell it today you would lose (79,000) from holding Daebo Magnetic CoLtd or give up 5.86% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Daebo Magnetic CoLtd vs. Automobile Pc
Performance |
| Timeline |
| Daebo Magnetic CoLtd |
| Automobile Pc |
Daebo Magnetic and Automobile Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Daebo Magnetic and Automobile
The main advantage of trading using opposite Daebo Magnetic and Automobile positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daebo Magnetic position performs unexpectedly, Automobile 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 Automobile will offset losses from the drop in Automobile's long position.| Daebo Magnetic vs. Moonbae Steel | Daebo Magnetic vs. Dongbu Steel Co | Daebo Magnetic vs. Foodnamoo | Daebo Magnetic vs. Dong A Steel Technology |
| Automobile vs. Daou Data Corp | Automobile vs. Solution Advanced Technology | Automobile vs. Busan Industrial Co | Automobile vs. Busan Ind |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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