Correlation Between Seoam Machinery and Formetal
Can any of the company-specific risk be diversified away by investing in both Seoam Machinery and Formetal 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 Formetal 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 Formetal Co, you can compare the effects of market volatilities on Seoam Machinery and Formetal 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 Formetal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Seoam Machinery and Formetal.
Diversification Opportunities for Seoam Machinery and Formetal
0.08 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Seoam and Formetal is 0.08. Overlapping area represents the amount of risk that can be diversified away by holding Seoam Machinery Industry and Formetal Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Formetal 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 Formetal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Formetal has no effect on the direction of Seoam Machinery i.e., Seoam Machinery and Formetal go up and down completely randomly.
Pair Corralation between Seoam Machinery and Formetal
Assuming the 90 days trading horizon Seoam Machinery is expected to generate 4.58 times less return on investment than Formetal. But when comparing it to its historical volatility, Seoam Machinery Industry is 3.06 times less risky than Formetal. It trades about 0.22 of its potential returns per unit of risk. Formetal Co is currently generating about 0.32 of returns per unit of risk over similar time horizon. If you would invest 300,000 in Formetal Co on October 29, 2024 and sell it today you would earn a total of 80,500 from holding Formetal Co or generate 26.83% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Seoam Machinery Industry vs. Formetal Co
Performance |
| Timeline |
| Seoam Machinery Industry |
| Formetal |
Seoam Machinery and Formetal Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Seoam Machinery and Formetal
The main advantage of trading using opposite Seoam Machinery and Formetal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Seoam Machinery position performs unexpectedly, Formetal 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 Formetal will offset losses from the drop in Formetal's long position.| Seoam Machinery vs. Busan Industrial Co | Seoam Machinery vs. Busan Ind | Seoam Machinery vs. RPBio Inc | Seoam Machinery vs. Finebesteel |
| Formetal vs. Hanjoo Light Metal | Formetal vs. Hyundai Home Shopping | Formetal vs. Duksan Hi Metal | Formetal vs. Daeduck Electronics Co |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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