Correlation Between CHINA CONBANK and DISTRICT METALS
Can any of the company-specific risk be diversified away by investing in both CHINA CONBANK and DISTRICT METALS 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 CONBANK and DISTRICT METALS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CHINA BANK ADR20 and DISTRICT METALS, you can compare the effects of market volatilities on CHINA CONBANK and DISTRICT METALS 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 CONBANK with a short position of DISTRICT METALS. Check out your portfolio center. Please also check ongoing floating volatility patterns of CHINA CONBANK and DISTRICT METALS.
Diversification Opportunities for CHINA CONBANK and DISTRICT METALS
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between CHINA and DISTRICT is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding CHINA BANK ADR20 and DISTRICT METALS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DISTRICT METALS and CHINA CONBANK 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 BANK ADR20 are associated (or correlated) with DISTRICT METALS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DISTRICT METALS has no effect on the direction of CHINA CONBANK i.e., CHINA CONBANK and DISTRICT METALS go up and down completely randomly.
Pair Corralation between CHINA CONBANK and DISTRICT METALS
Assuming the 90 days trading horizon CHINA BANK ADR20 is expected to generate 0.36 times more return on investment than DISTRICT METALS. However, CHINA BANK ADR20 is 2.8 times less risky than DISTRICT METALS. It trades about 0.07 of its potential returns per unit of risk. DISTRICT METALS is currently generating about 0.02 per unit of risk. If you would invest 1,410 in CHINA BANK ADR20 on September 13, 2024 and sell it today you would earn a total of 70.00 from holding CHINA BANK ADR20 or generate 4.96% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
CHINA BANK ADR20 vs. DISTRICT METALS
Performance |
| Timeline |
| CHINA BANK ADR20 |
| DISTRICT METALS |
CHINA CONBANK and DISTRICT METALS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CHINA CONBANK and DISTRICT METALS
The main advantage of trading using opposite CHINA CONBANK and DISTRICT METALS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CHINA CONBANK position performs unexpectedly, DISTRICT METALS 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 DISTRICT METALS will offset losses from the drop in DISTRICT METALS's long position.| CHINA CONBANK vs. China Resources Beer | CHINA CONBANK vs. Micron Technology | CHINA CONBANK vs. Fevertree Drinks PLC | CHINA CONBANK vs. Amkor Technology |
| DISTRICT METALS vs. American Lithium Corp | DISTRICT METALS vs. ADRIATIC METALS LS 013355 | DISTRICT METALS vs. Superior Plus Corp | DISTRICT METALS vs. SIVERS SEMICONDUCTORS AB |
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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