Correlation Between Kukdong Oil and Daewoo Engineering
Can any of the company-specific risk be diversified away by investing in both Kukdong Oil and Daewoo Engineering 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 Kukdong Oil and Daewoo Engineering into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kukdong Oil Chemicals and Daewoo Engineering Construction, you can compare the effects of market volatilities on Kukdong Oil and Daewoo Engineering 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 Kukdong Oil with a short position of Daewoo Engineering. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kukdong Oil and Daewoo Engineering.
Diversification Opportunities for Kukdong Oil and Daewoo Engineering
0.5 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Kukdong and Daewoo is 0.5. Overlapping area represents the amount of risk that can be diversified away by holding Kukdong Oil Chemicals and Daewoo Engineering Constructio in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daewoo Engineering and Kukdong Oil 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 Kukdong Oil Chemicals are associated (or correlated) with Daewoo Engineering. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daewoo Engineering has no effect on the direction of Kukdong Oil i.e., Kukdong Oil and Daewoo Engineering go up and down completely randomly.
Pair Corralation between Kukdong Oil and Daewoo Engineering
Assuming the 90 days trading horizon Kukdong Oil is expected to generate 4.1 times less return on investment than Daewoo Engineering. In addition to that, Kukdong Oil is 1.09 times more volatile than Daewoo Engineering Construction. It trades about 0.03 of its total potential returns per unit of risk. Daewoo Engineering Construction is currently generating about 0.15 per unit of volatility. If you would invest 329,500 in Daewoo Engineering Construction on April 24, 2025 and sell it today you would earn a total of 67,000 from holding Daewoo Engineering Construction or generate 20.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Kukdong Oil Chemicals vs. Daewoo Engineering Constructio
Performance |
Timeline |
Kukdong Oil Chemicals |
Daewoo Engineering |
Kukdong Oil and Daewoo Engineering Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kukdong Oil and Daewoo Engineering
The main advantage of trading using opposite Kukdong Oil and Daewoo Engineering positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kukdong Oil position performs unexpectedly, Daewoo Engineering 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 Daewoo Engineering will offset losses from the drop in Daewoo Engineering's long position.Kukdong Oil vs. SBI Investment KOREA | Kukdong Oil vs. Sam Yang Foods | Kukdong Oil vs. Samyung Trading Co | Kukdong Oil vs. Lotte Rental Co |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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