Correlation Between CHINA HUARONG and COMINTL BANK
Can any of the company-specific risk be diversified away by investing in both CHINA HUARONG and COMINTL 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 CHINA HUARONG and COMINTL BANK into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CHINA HUARONG ENERHD 50 and COMINTL BANK ADR1, you can compare the effects of market volatilities on CHINA HUARONG and COMINTL 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 CHINA HUARONG with a short position of COMINTL BANK. Check out your portfolio center. Please also check ongoing floating volatility patterns of CHINA HUARONG and COMINTL BANK.
Diversification Opportunities for CHINA HUARONG and COMINTL BANK
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between CHINA and COMINTL is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding CHINA HUARONG ENERHD 50 and COMINTL BANK ADR1 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on COMINTL BANK ADR1 and CHINA HUARONG 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 CHINA HUARONG ENERHD 50 are associated (or correlated) with COMINTL BANK. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of COMINTL BANK ADR1 has no effect on the direction of CHINA HUARONG i.e., CHINA HUARONG and COMINTL BANK go up and down completely randomly.
Pair Corralation between CHINA HUARONG and COMINTL BANK
Assuming the 90 days trading horizon CHINA HUARONG ENERHD 50 is expected to under-perform the COMINTL BANK. In addition to that, CHINA HUARONG is 11.17 times more volatile than COMINTL BANK ADR1. It trades about -0.03 of its total potential returns per unit of risk. COMINTL BANK ADR1 is currently generating about -0.02 per unit of volatility. If you would invest 129.00 in COMINTL BANK ADR1 on September 12, 2024 and sell it today you would lose (1.00) from holding COMINTL BANK ADR1 or give up 0.78% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
CHINA HUARONG ENERHD 50 vs. COMINTL BANK ADR1
Performance |
| Timeline |
| CHINA HUARONG ENERHD |
| COMINTL BANK ADR1 |
CHINA HUARONG and COMINTL BANK Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CHINA HUARONG and COMINTL BANK
The main advantage of trading using opposite CHINA HUARONG and COMINTL BANK positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CHINA HUARONG position performs unexpectedly, COMINTL 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 COMINTL BANK will offset losses from the drop in COMINTL BANK's long position.| CHINA HUARONG vs. Air Transport Services | CHINA HUARONG vs. Liberty Broadband | CHINA HUARONG vs. TEXAS ROADHOUSE | CHINA HUARONG vs. NORWEGIAN AIR SHUT |
| COMINTL BANK vs. Superior Plus Corp | COMINTL BANK vs. SIVERS SEMICONDUCTORS AB | COMINTL BANK vs. CHINA HUARONG ENERHD 50 | COMINTL BANK vs. NORDIC HALIBUT AS |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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