Correlation Between KCC Engineering and Seoam Machinery
Can any of the company-specific risk be diversified away by investing in both KCC Engineering and Seoam 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 KCC Engineering and Seoam Machinery into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KCC Engineering Construction and Seoam Machinery Industry, you can compare the effects of market volatilities on KCC Engineering and Seoam 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 KCC Engineering with a short position of Seoam Machinery. Check out your portfolio center. Please also check ongoing floating volatility patterns of KCC Engineering and Seoam Machinery.
Diversification Opportunities for KCC Engineering and Seoam Machinery
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between KCC and Seoam is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding KCC Engineering Construction and Seoam Machinery Industry in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Seoam Machinery Industry and KCC Engineering 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 KCC Engineering Construction are associated (or correlated) with Seoam Machinery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Seoam Machinery Industry has no effect on the direction of KCC Engineering i.e., KCC Engineering and Seoam Machinery go up and down completely randomly.
Pair Corralation between KCC Engineering and Seoam Machinery
Assuming the 90 days trading horizon KCC Engineering Construction is expected to generate 0.73 times more return on investment than Seoam Machinery. However, KCC Engineering Construction is 1.38 times less risky than Seoam Machinery. It trades about 0.11 of its potential returns per unit of risk. Seoam Machinery Industry is currently generating about -0.19 per unit of risk. If you would invest 388,500 in KCC Engineering Construction on December 10, 2024 and sell it today you would earn a total of 10,500 from holding KCC Engineering Construction or generate 2.7% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
KCC Engineering Construction vs. Seoam Machinery Industry
Performance |
Timeline |
KCC Engineering Cons |
Seoam Machinery Industry |
KCC Engineering and Seoam Machinery Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KCC Engineering and Seoam Machinery
The main advantage of trading using opposite KCC Engineering and Seoam Machinery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KCC Engineering position performs unexpectedly, Seoam 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 Seoam Machinery will offset losses from the drop in Seoam Machinery's long position.KCC Engineering vs. Choil Aluminum | KCC Engineering vs. Display Tech Co | KCC Engineering vs. Dongbang Transport Logistics | KCC Engineering vs. Sejong Telecom |
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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 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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