Correlation Between CSSC Offshore and TMBThanachart Bank
Can any of the company-specific risk be diversified away by investing in both CSSC Offshore and TMBThanachart Bank 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 CSSC Offshore and TMBThanachart Bank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CSSC Offshore Marine and TMBThanachart Bank Public, you can compare the effects of market volatilities on CSSC Offshore and TMBThanachart Bank 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 CSSC Offshore with a short position of TMBThanachart Bank. Check out your portfolio center. Please also check ongoing floating volatility patterns of CSSC Offshore and TMBThanachart Bank.
Diversification Opportunities for CSSC Offshore and TMBThanachart Bank
0.49 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between CSSC and TMBThanachart is 0.49. Overlapping area represents the amount of risk that can be diversified away by holding CSSC Offshore Marine and TMBThanachart Bank Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TMBThanachart Bank Public and CSSC Offshore 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 CSSC Offshore Marine are associated (or correlated) with TMBThanachart Bank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of TMBThanachart Bank Public has no effect on the direction of CSSC Offshore i.e., CSSC Offshore and TMBThanachart Bank go up and down completely randomly.
Pair Corralation between CSSC Offshore and TMBThanachart Bank
Assuming the 90 days trading horizon CSSC Offshore Marine is expected to under-perform the TMBThanachart Bank. In addition to that, CSSC Offshore is 2.26 times more volatile than TMBThanachart Bank Public. It trades about -0.07 of its total potential returns per unit of risk. TMBThanachart Bank Public is currently generating about -0.06 per unit of volatility. If you would invest 5.20 in TMBThanachart Bank Public on September 10, 2024 and sell it today you would lose (0.30) from holding TMBThanachart Bank Public or give up 5.77% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
CSSC Offshore Marine vs. TMBThanachart Bank Public
Performance |
Timeline |
CSSC Offshore Marine |
TMBThanachart Bank Public |
CSSC Offshore and TMBThanachart Bank Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CSSC Offshore and TMBThanachart Bank
The main advantage of trading using opposite CSSC Offshore and TMBThanachart Bank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CSSC Offshore position performs unexpectedly, TMBThanachart Bank 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 TMBThanachart Bank will offset losses from the drop in TMBThanachart Bank's long position.CSSC Offshore vs. Apple Inc | CSSC Offshore vs. Apple Inc | CSSC Offshore vs. Apple Inc | CSSC Offshore vs. Apple Inc |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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