Correlation Between DAEDUCK ELECTRONICS and Kosdaq Composite
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By analyzing existing cross correlation between DAEDUCK ELECTRONICS CoLtd and Kosdaq Composite Index, you can compare the effects of market volatilities on DAEDUCK ELECTRONICS and Kosdaq Composite 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 DAEDUCK ELECTRONICS with a short position of Kosdaq Composite. Check out your portfolio center. Please also check ongoing floating volatility patterns of DAEDUCK ELECTRONICS and Kosdaq Composite.
Diversification Opportunities for DAEDUCK ELECTRONICS and Kosdaq Composite
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between DAEDUCK and Kosdaq is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding DAEDUCK ELECTRONICS CoLtd and Kosdaq Composite Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kosdaq Composite Index and DAEDUCK ELECTRONICS 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 DAEDUCK ELECTRONICS CoLtd are associated (or correlated) with Kosdaq Composite. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kosdaq Composite Index has no effect on the direction of DAEDUCK ELECTRONICS i.e., DAEDUCK ELECTRONICS and Kosdaq Composite go up and down completely randomly.
Pair Corralation between DAEDUCK ELECTRONICS and Kosdaq Composite
Assuming the 90 days trading horizon DAEDUCK ELECTRONICS CoLtd is expected to under-perform the Kosdaq Composite. In addition to that, DAEDUCK ELECTRONICS is 1.22 times more volatile than Kosdaq Composite Index. It trades about -0.01 of its total potential returns per unit of risk. Kosdaq Composite Index is currently generating about 0.0 per unit of volatility. If you would invest 73,352 in Kosdaq Composite Index on November 7, 2024 and sell it today you would lose (615.00) from holding Kosdaq Composite Index or give up 0.84% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 98.28% |
| Values | Daily Returns |
DAEDUCK ELECTRONICS CoLtd vs. Kosdaq Composite Index
Performance |
| Timeline |
DAEDUCK ELECTRONICS and Kosdaq Composite Volatility Contrast
Predicted Return Density |
| Returns |
DAEDUCK ELECTRONICS CoLtd
Pair trading matchups for DAEDUCK ELECTRONICS
Kosdaq Composite Index
Pair trading matchups for Kosdaq Composite
Pair Trading with DAEDUCK ELECTRONICS and Kosdaq Composite
The main advantage of trading using opposite DAEDUCK ELECTRONICS and Kosdaq Composite positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DAEDUCK ELECTRONICS position performs unexpectedly, Kosdaq Composite 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 Kosdaq Composite will offset losses from the drop in Kosdaq Composite's long position.| DAEDUCK ELECTRONICS vs. Lotte Chilsung Beverage | DAEDUCK ELECTRONICS vs. Korea Computer | DAEDUCK ELECTRONICS vs. LG Display Co | DAEDUCK ELECTRONICS vs. Iljin Display |
| Kosdaq Composite vs. Dongwoo Farm To | Kosdaq Composite vs. Kyeryong Construction Industrial | Kosdaq Composite vs. T3 Entertainment Co | Kosdaq Composite vs. FNC Entertainment Co |
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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