Correlation Between Regional Container and Thai OPP
Can any of the company-specific risk be diversified away by investing in both Regional Container and Thai OPP 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 Regional Container and Thai OPP into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Regional Container Lines and Thai OPP Public, you can compare the effects of market volatilities on Regional Container and Thai OPP 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 Regional Container with a short position of Thai OPP. Check out your portfolio center. Please also check ongoing floating volatility patterns of Regional Container and Thai OPP.
Diversification Opportunities for Regional Container and Thai OPP
-0.64 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Regional and Thai is -0.64. Overlapping area represents the amount of risk that can be diversified away by holding Regional Container Lines and Thai OPP Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Thai OPP Public and Regional Container 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 Regional Container Lines are associated (or correlated) with Thai OPP. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Thai OPP Public has no effect on the direction of Regional Container i.e., Regional Container and Thai OPP go up and down completely randomly.
Pair Corralation between Regional Container and Thai OPP
Assuming the 90 days trading horizon Regional Container is expected to generate 36.56 times less return on investment than Thai OPP. But when comparing it to its historical volatility, Regional Container Lines is 16.49 times less risky than Thai OPP. It trades about 0.02 of its potential returns per unit of risk. Thai OPP Public is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 15,390 in Thai OPP Public on October 9, 2024 and sell it today you would earn a total of 1,310 from holding Thai OPP Public or generate 8.51% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 99.8% |
Values | Daily Returns |
Regional Container Lines vs. Thai OPP Public
Performance |
Timeline |
Regional Container Lines |
Thai OPP Public |
Regional Container and Thai OPP Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Regional Container and Thai OPP
The main advantage of trading using opposite Regional Container and Thai OPP positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Regional Container position performs unexpectedly, Thai OPP 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 Thai OPP will offset losses from the drop in Thai OPP's long position.Regional Container vs. Precious Shipping Public | Regional Container vs. Thoresen Thai Agencies | Regional Container vs. The Siam Cement | Regional Container vs. Hana Microelectronics Public |
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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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