Correlation Between Daehan Steel and Finebesteel
Can any of the company-specific risk be diversified away by investing in both Daehan Steel and Finebesteel 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 Daehan Steel and Finebesteel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daehan Steel and Finebesteel, you can compare the effects of market volatilities on Daehan Steel and Finebesteel 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 Daehan Steel with a short position of Finebesteel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daehan Steel and Finebesteel.
Diversification Opportunities for Daehan Steel and Finebesteel
0.45 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Daehan and Finebesteel is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding Daehan Steel and Finebesteel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Finebesteel and Daehan Steel 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 Daehan Steel are associated (or correlated) with Finebesteel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Finebesteel has no effect on the direction of Daehan Steel i.e., Daehan Steel and Finebesteel go up and down completely randomly.
Pair Corralation between Daehan Steel and Finebesteel
Assuming the 90 days trading horizon Daehan Steel is expected to generate 14.98 times less return on investment than Finebesteel. But when comparing it to its historical volatility, Daehan Steel is 3.82 times less risky than Finebesteel. It trades about 0.07 of its potential returns per unit of risk. Finebesteel is currently generating about 0.29 of returns per unit of risk over similar time horizon. If you would invest 92,100 in Finebesteel on November 5, 2024 and sell it today you would earn a total of 14,400 from holding Finebesteel or generate 15.64% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Daehan Steel vs. Finebesteel
Performance |
| Timeline |
| Daehan Steel |
| Finebesteel |
Daehan Steel and Finebesteel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Daehan Steel and Finebesteel
The main advantage of trading using opposite Daehan Steel and Finebesteel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daehan Steel position performs unexpectedly, Finebesteel 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 Finebesteel will offset losses from the drop in Finebesteel's long position.| Daehan Steel vs. Aprogen Healthcare Games | Daehan Steel vs. Netmarble Games Corp | Daehan Steel vs. Kg Chemical | Daehan Steel vs. KPX Green Chemical |
| Finebesteel vs. Camus Engineering Construction | Finebesteel vs. SEOJEON ELECTRIC MACHINERY | Finebesteel vs. Woori Technology | Finebesteel vs. KEPCO Engineering Construction |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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