Correlation Between BANK OF CHINA and STRAITS TRADG
Can any of the company-specific risk be diversified away by investing in both BANK OF CHINA and STRAITS TRADG 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 BANK OF CHINA and STRAITS TRADG into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BANK OF CHINA and STRAITS TRADG SD, you can compare the effects of market volatilities on BANK OF CHINA and STRAITS TRADG 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 BANK OF CHINA with a short position of STRAITS TRADG. Check out your portfolio center. Please also check ongoing floating volatility patterns of BANK OF CHINA and STRAITS TRADG.
Diversification Opportunities for BANK OF CHINA and STRAITS TRADG
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between BANK and STRAITS is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding BANK OF CHINA and STRAITS TRADG SD in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on STRAITS TRADG SD and BANK OF CHINA 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 BANK OF CHINA are associated (or correlated) with STRAITS TRADG. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of STRAITS TRADG SD has no effect on the direction of BANK OF CHINA i.e., BANK OF CHINA and STRAITS TRADG go up and down completely randomly.
Pair Corralation between BANK OF CHINA and STRAITS TRADG
Assuming the 90 days trading horizon BANK OF CHINA is expected to generate 12.07 times more return on investment than STRAITS TRADG. However, BANK OF CHINA is 12.07 times more volatile than STRAITS TRADG SD. It trades about 0.23 of its potential returns per unit of risk. STRAITS TRADG SD is currently generating about 0.0 per unit of risk. If you would invest 36.00 in BANK OF CHINA on November 7, 2024 and sell it today you would earn a total of 14.00 from holding BANK OF CHINA or generate 38.89% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BANK OF CHINA vs. STRAITS TRADG SD
Performance |
| Timeline |
| BANK OF CHINA |
| STRAITS TRADG SD |
BANK OF CHINA and STRAITS TRADG Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BANK OF CHINA and STRAITS TRADG
The main advantage of trading using opposite BANK OF CHINA and STRAITS TRADG positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BANK OF CHINA position performs unexpectedly, STRAITS TRADG 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 STRAITS TRADG will offset losses from the drop in STRAITS TRADG's long position.| BANK OF CHINA vs. Australian Agricultural | BANK OF CHINA vs. ALBIS LEASING AG | BANK OF CHINA vs. Air Lease | BANK OF CHINA vs. FUYO GENERAL LEASE |
| STRAITS TRADG vs. BE Semiconductor Industries | STRAITS TRADG vs. GMO Internet | STRAITS TRADG vs. Computershare Limited | STRAITS TRADG vs. Semiconductor Manufacturing International |
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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