Correlation Between Daejoo Electronic and Kyung Chang
Can any of the company-specific risk be diversified away by investing in both Daejoo Electronic and Kyung Chang 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 Daejoo Electronic and Kyung Chang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daejoo Electronic Materials and Kyung Chang Industrial, you can compare the effects of market volatilities on Daejoo Electronic and Kyung Chang 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 Daejoo Electronic with a short position of Kyung Chang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daejoo Electronic and Kyung Chang.
Diversification Opportunities for Daejoo Electronic and Kyung Chang
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Daejoo and Kyung is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Daejoo Electronic Materials and Kyung Chang Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kyung Chang Industrial and Daejoo Electronic 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 Daejoo Electronic Materials are associated (or correlated) with Kyung Chang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kyung Chang Industrial has no effect on the direction of Daejoo Electronic i.e., Daejoo Electronic and Kyung Chang go up and down completely randomly.
Pair Corralation between Daejoo Electronic and Kyung Chang
Assuming the 90 days trading horizon Daejoo Electronic Materials is expected to generate 1.09 times more return on investment than Kyung Chang. However, Daejoo Electronic is 1.09 times more volatile than Kyung Chang Industrial. It trades about 0.02 of its potential returns per unit of risk. Kyung Chang Industrial is currently generating about 0.0 per unit of risk. If you would invest 8,300,107 in Daejoo Electronic Materials on September 4, 2024 and sell it today you would earn a total of 259,893 from holding Daejoo Electronic Materials or generate 3.13% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Daejoo Electronic Materials vs. Kyung Chang Industrial
Performance |
Timeline |
Daejoo Electronic |
Kyung Chang Industrial |
Daejoo Electronic and Kyung Chang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Daejoo Electronic and Kyung Chang
The main advantage of trading using opposite Daejoo Electronic and Kyung Chang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daejoo Electronic position performs unexpectedly, Kyung Chang 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 Kyung Chang will offset losses from the drop in Kyung Chang's long position.Daejoo Electronic vs. Dongsin Engineering Construction | Daejoo Electronic vs. Doosan Fuel Cell | Daejoo Electronic vs. Daishin Balance 1 | Daejoo Electronic vs. Total Soft Bank |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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