Correlation Between Kumho Ind and Daekyung Machinery
Can any of the company-specific risk be diversified away by investing in both Kumho Ind and Daekyung Machinery 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 Kumho Ind and Daekyung Machinery into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kumho Ind and Daekyung Machinery Engineering, you can compare the effects of market volatilities on Kumho Ind and Daekyung Machinery 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 Kumho Ind with a short position of Daekyung Machinery. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kumho Ind and Daekyung Machinery.
Diversification Opportunities for Kumho Ind and Daekyung Machinery
0.09 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Kumho and Daekyung is 0.09. Overlapping area represents the amount of risk that can be diversified away by holding Kumho Ind and Daekyung Machinery Engineering in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daekyung Machinery and Kumho Ind 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 Kumho Ind are associated (or correlated) with Daekyung Machinery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daekyung Machinery has no effect on the direction of Kumho Ind i.e., Kumho Ind and Daekyung Machinery go up and down completely randomly.
Pair Corralation between Kumho Ind and Daekyung Machinery
Assuming the 90 days trading horizon Kumho Ind is expected to generate 8.61 times less return on investment than Daekyung Machinery. But when comparing it to its historical volatility, Kumho Ind is 1.18 times less risky than Daekyung Machinery. It trades about 0.05 of its potential returns per unit of risk. Daekyung Machinery Engineering is currently generating about 0.37 of returns per unit of risk over similar time horizon. If you would invest 39,900 in Daekyung Machinery Engineering on September 4, 2024 and sell it today you would earn a total of 11,600 from holding Daekyung Machinery Engineering or generate 29.07% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 81.82% |
Values | Daily Returns |
Kumho Ind vs. Daekyung Machinery Engineering
Performance |
Timeline |
Kumho Ind |
Daekyung Machinery |
Kumho Ind and Daekyung Machinery Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kumho Ind and Daekyung Machinery
The main advantage of trading using opposite Kumho Ind and Daekyung Machinery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kumho Ind position performs unexpectedly, Daekyung Machinery 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 Daekyung Machinery will offset losses from the drop in Daekyung Machinery's long position.Kumho Ind vs. Daekyung Machinery Engineering | Kumho Ind vs. Dongbang Ship Machinery | Kumho Ind vs. WooDeumGee Farm Co, | Kumho Ind vs. Daewoo Engineering Construction |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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