Correlation Between Daejung Chemicals and Sang A
Can any of the company-specific risk be diversified away by investing in both Daejung Chemicals and Sang A 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 Daejung Chemicals and Sang A into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daejung Chemicals Metals and Sang A Frontec CoLtd, you can compare the effects of market volatilities on Daejung Chemicals and Sang A 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 Daejung Chemicals with a short position of Sang A. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daejung Chemicals and Sang A.
Diversification Opportunities for Daejung Chemicals and Sang A
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Daejung and Sang is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding Daejung Chemicals Metals and Sang A Frontec CoLtd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sang A Frontec and Daejung Chemicals 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 Daejung Chemicals Metals are associated (or correlated) with Sang A. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sang A Frontec has no effect on the direction of Daejung Chemicals i.e., Daejung Chemicals and Sang A go up and down completely randomly.
Pair Corralation between Daejung Chemicals and Sang A
Assuming the 90 days trading horizon Daejung Chemicals Metals is expected to generate 0.63 times more return on investment than Sang A. However, Daejung Chemicals Metals is 1.58 times less risky than Sang A. It trades about 0.15 of its potential returns per unit of risk. Sang A Frontec CoLtd is currently generating about -0.24 per unit of risk. If you would invest 1,258,377 in Daejung Chemicals Metals on October 17, 2024 and sell it today you would earn a total of 38,623 from holding Daejung Chemicals Metals or generate 3.07% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 95.0% |
| Values | Daily Returns |
Daejung Chemicals Metals vs. Sang A Frontec CoLtd
Performance |
| Timeline |
| Daejung Chemicals Metals |
| Sang A Frontec |
Daejung Chemicals and Sang A Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Daejung Chemicals and Sang A
The main advantage of trading using opposite Daejung Chemicals and Sang A positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daejung Chemicals position performs unexpectedly, Sang A 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 Sang A will offset losses from the drop in Sang A's long position.| Daejung Chemicals vs. Settlebank | Daejung Chemicals vs. Industrial Bank | Daejung Chemicals vs. Incar Financial Service | Daejung Chemicals vs. Daiyang Metal Co |
| Sang A vs. DONGKUK TED METAL | Sang A vs. Korea Investment Holdings | Sang A vs. Kukdong Oil Chemicals | Sang A vs. Daejung Chemicals Metals |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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