Correlation Between DATANG INTL and VULCAN MATERIALS
Can any of the company-specific risk be diversified away by investing in both DATANG INTL and VULCAN MATERIALS 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 DATANG INTL and VULCAN MATERIALS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DATANG INTL POW and VULCAN MATERIALS, you can compare the effects of market volatilities on DATANG INTL and VULCAN MATERIALS 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 DATANG INTL with a short position of VULCAN MATERIALS. Check out your portfolio center. Please also check ongoing floating volatility patterns of DATANG INTL and VULCAN MATERIALS.
Diversification Opportunities for DATANG INTL and VULCAN MATERIALS
-0.59 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between DATANG and VULCAN is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding DATANG INTL POW and VULCAN MATERIALS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on VULCAN MATERIALS and DATANG INTL 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 DATANG INTL POW are associated (or correlated) with VULCAN MATERIALS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of VULCAN MATERIALS has no effect on the direction of DATANG INTL i.e., DATANG INTL and VULCAN MATERIALS go up and down completely randomly.
Pair Corralation between DATANG INTL and VULCAN MATERIALS
Assuming the 90 days trading horizon DATANG INTL POW is expected to generate 1.95 times more return on investment than VULCAN MATERIALS. However, DATANG INTL is 1.95 times more volatile than VULCAN MATERIALS. It trades about 0.07 of its potential returns per unit of risk. VULCAN MATERIALS is currently generating about -0.1 per unit of risk. If you would invest 16.00 in DATANG INTL POW on December 31, 2024 and sell it today you would earn a total of 2.00 from holding DATANG INTL POW or generate 12.5% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
DATANG INTL POW vs. VULCAN MATERIALS
Performance |
Timeline |
DATANG INTL POW |
VULCAN MATERIALS |
DATANG INTL and VULCAN MATERIALS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with DATANG INTL and VULCAN MATERIALS
The main advantage of trading using opposite DATANG INTL and VULCAN MATERIALS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DATANG INTL position performs unexpectedly, VULCAN MATERIALS 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 VULCAN MATERIALS will offset losses from the drop in VULCAN MATERIALS's long position.DATANG INTL vs. Gladstone Investment | DATANG INTL vs. East Africa Metals | DATANG INTL vs. 24SEVENOFFICE GROUP AB | DATANG INTL vs. Keck Seng Investments |
VULCAN MATERIALS vs. Fevertree Drinks PLC | VULCAN MATERIALS vs. United Utilities Group | VULCAN MATERIALS vs. KENEDIX OFFICE INV | VULCAN MATERIALS vs. CITY OFFICE REIT |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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