Correlation Between Seoam Machinery and CC International
Can any of the company-specific risk be diversified away by investing in both Seoam Machinery and CC International 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 Seoam Machinery and CC International into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Seoam Machinery Industry and CC International Corp, you can compare the effects of market volatilities on Seoam Machinery and CC International 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 Seoam Machinery with a short position of CC International. Check out your portfolio center. Please also check ongoing floating volatility patterns of Seoam Machinery and CC International.
Diversification Opportunities for Seoam Machinery and CC International
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Seoam and 352480 is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Seoam Machinery Industry and CC International Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CC International Corp and Seoam Machinery 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 Seoam Machinery Industry are associated (or correlated) with CC International. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CC International Corp has no effect on the direction of Seoam Machinery i.e., Seoam Machinery and CC International go up and down completely randomly.
Pair Corralation between Seoam Machinery and CC International
Assuming the 90 days trading horizon Seoam Machinery Industry is expected to generate 0.43 times more return on investment than CC International. However, Seoam Machinery Industry is 2.32 times less risky than CC International. It trades about 0.01 of its potential returns per unit of risk. CC International Corp is currently generating about -0.35 per unit of risk. If you would invest 386,000 in Seoam Machinery Industry on September 1, 2024 and sell it today you would lose (1,500) from holding Seoam Machinery Industry or give up 0.39% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 95.65% |
Values | Daily Returns |
Seoam Machinery Industry vs. CC International Corp
Performance |
Timeline |
Seoam Machinery Industry |
CC International Corp |
Seoam Machinery and CC International Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Seoam Machinery and CC International
The main advantage of trading using opposite Seoam Machinery and CC International positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Seoam Machinery position performs unexpectedly, CC International 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 CC International will offset losses from the drop in CC International's long position.Seoam Machinery vs. COWINTECH Co | Seoam Machinery vs. Young Poong Precision | Seoam Machinery vs. Haisung TPC 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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