Correlation Between Daehan Synthetic and Sam Yang
Can any of the company-specific risk be diversified away by investing in both Daehan Synthetic and Sam Yang 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 Synthetic and Sam Yang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daehan Synthetic Fiber and Sam Yang Foods, you can compare the effects of market volatilities on Daehan Synthetic and Sam Yang 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 Synthetic with a short position of Sam Yang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daehan Synthetic and Sam Yang.
Diversification Opportunities for Daehan Synthetic and Sam Yang
-0.05 | Correlation Coefficient |
Good diversification
The 3 months correlation between Daehan and Sam is -0.05. Overlapping area represents the amount of risk that can be diversified away by holding Daehan Synthetic Fiber and Sam Yang Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sam Yang Foods and Daehan Synthetic 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 Synthetic Fiber are associated (or correlated) with Sam Yang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sam Yang Foods has no effect on the direction of Daehan Synthetic i.e., Daehan Synthetic and Sam Yang go up and down completely randomly.
Pair Corralation between Daehan Synthetic and Sam Yang
Assuming the 90 days trading horizon Daehan Synthetic Fiber is expected to under-perform the Sam Yang. But the stock apears to be less risky and, when comparing its historical volatility, Daehan Synthetic Fiber is 5.36 times less risky than Sam Yang. The stock trades about -0.29 of its potential returns per unit of risk. The Sam Yang Foods is currently generating about 0.4 of returns per unit of risk over similar time horizon. If you would invest 54,400,000 in Sam Yang Foods on September 19, 2024 and sell it today you would earn a total of 19,200,000 from holding Sam Yang Foods or generate 35.29% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Daehan Synthetic Fiber vs. Sam Yang Foods
Performance |
| Timeline |
| Daehan Synthetic Fiber |
| Sam Yang Foods |
Daehan Synthetic and Sam Yang Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Daehan Synthetic and Sam Yang
The main advantage of trading using opposite Daehan Synthetic and Sam Yang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daehan Synthetic position performs unexpectedly, Sam Yang 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 Sam Yang will offset losses from the drop in Sam Yang's long position.| Daehan Synthetic vs. Samsung Electronics Co | Daehan Synthetic vs. Samsung Electronics Co | Daehan Synthetic vs. SK Hynix | Daehan Synthetic vs. POSCO Holdings |
| Sam Yang vs. Dongil Metal Co | Sam Yang vs. PJ Metal Co | Sam Yang vs. Daehan Synthetic Fiber | Sam Yang vs. TK Chemical |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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