Correlation Between Duksan Hi and Daewon Chemical
Can any of the company-specific risk be diversified away by investing in both Duksan Hi and Daewon Chemical 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 Duksan Hi and Daewon Chemical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Duksan Hi Metal and Daewon Chemical Co, you can compare the effects of market volatilities on Duksan Hi and Daewon Chemical 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 Duksan Hi with a short position of Daewon Chemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Duksan Hi and Daewon Chemical.
Diversification Opportunities for Duksan Hi and Daewon Chemical
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Duksan and Daewon is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding Duksan Hi Metal and Daewon Chemical Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daewon Chemical and Duksan Hi 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 Duksan Hi Metal are associated (or correlated) with Daewon Chemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daewon Chemical has no effect on the direction of Duksan Hi i.e., Duksan Hi and Daewon Chemical go up and down completely randomly.
Pair Corralation between Duksan Hi and Daewon Chemical
Assuming the 90 days trading horizon Duksan Hi Metal is expected to generate 1.1 times more return on investment than Daewon Chemical. However, Duksan Hi is 1.1 times more volatile than Daewon Chemical Co. It trades about -0.03 of its potential returns per unit of risk. Daewon Chemical Co is currently generating about -0.07 per unit of risk. If you would invest 712,000 in Duksan Hi Metal on October 16, 2024 and sell it today you would lose (320,500) from holding Duksan Hi Metal or give up 45.01% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Duksan Hi Metal vs. Daewon Chemical Co
Performance |
| Timeline |
| Duksan Hi Metal |
| Daewon Chemical |
Duksan Hi and Daewon Chemical Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Duksan Hi and Daewon Chemical
The main advantage of trading using opposite Duksan Hi and Daewon Chemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Duksan Hi position performs unexpectedly, Daewon Chemical 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 Daewon Chemical will offset losses from the drop in Daewon Chemical's long position.| Duksan Hi vs. Hanshin Construction Co | Duksan Hi vs. Seohee Construction Co | Duksan Hi vs. Inzi Display CoLtd | Duksan Hi vs. Nam Hwa Construction |
| Daewon Chemical vs. Keyang Electric Machinery | Daewon Chemical vs. Hanshin Construction Co | Daewon Chemical vs. Sewoon Medical Co | Daewon Chemical vs. Duksan Hi Metal |
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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