Correlation Between SCG PACKAGING and MCS Steel
Can any of the company-specific risk be diversified away by investing in both SCG PACKAGING and MCS Steel 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 SCG PACKAGING and MCS Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SCG PACKAGING PCL NVDR and MCS Steel Public, you can compare the effects of market volatilities on SCG PACKAGING and MCS Steel 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 SCG PACKAGING with a short position of MCS Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of SCG PACKAGING and MCS Steel.
Diversification Opportunities for SCG PACKAGING and MCS Steel
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between SCG and MCS is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding SCG PACKAGING PCL NVDR and MCS Steel Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MCS Steel Public and SCG PACKAGING 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 SCG PACKAGING PCL NVDR are associated (or correlated) with MCS Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MCS Steel Public has no effect on the direction of SCG PACKAGING i.e., SCG PACKAGING and MCS Steel go up and down completely randomly.
Pair Corralation between SCG PACKAGING and MCS Steel
Assuming the 90 days trading horizon SCG PACKAGING PCL NVDR is expected to under-perform the MCS Steel. In addition to that, SCG PACKAGING is 5.45 times more volatile than MCS Steel Public. It trades about -0.26 of its total potential returns per unit of risk. MCS Steel Public is currently generating about -0.12 per unit of volatility. If you would invest 740.00 in MCS Steel Public on September 1, 2024 and sell it today you would lose (30.00) from holding MCS Steel Public or give up 4.05% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
SCG PACKAGING PCL NVDR vs. MCS Steel Public
Performance |
| Timeline |
| SCG PACKAGING PCL |
| MCS Steel Public |
SCG PACKAGING and MCS Steel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SCG PACKAGING and MCS Steel
The main advantage of trading using opposite SCG PACKAGING and MCS Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SCG PACKAGING position performs unexpectedly, MCS Steel 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 MCS Steel will offset losses from the drop in MCS Steel's long position.| SCG PACKAGING vs. PTT Public | SCG PACKAGING vs. Kasikornbank Public | SCG PACKAGING vs. The Siam Cement | SCG PACKAGING vs. OSOTSPA PCL NVDR |
| MCS Steel vs. AAPICO Hitech Public | MCS Steel vs. AP Public | MCS Steel vs. Aikchol Hospital Public | MCS Steel vs. Bank of Ayudhya |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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