Correlation Between DISTRICT METALS and Alibaba Group
Can any of the company-specific risk be diversified away by investing in both DISTRICT METALS and Alibaba Group 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 DISTRICT METALS and Alibaba Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DISTRICT METALS and Alibaba Group Holding, you can compare the effects of market volatilities on DISTRICT METALS and Alibaba Group 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 DISTRICT METALS with a short position of Alibaba Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of DISTRICT METALS and Alibaba Group.
Diversification Opportunities for DISTRICT METALS and Alibaba Group
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between DISTRICT and Alibaba is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding DISTRICT METALS and Alibaba Group Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alibaba Group Holding and DISTRICT METALS 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 DISTRICT METALS are associated (or correlated) with Alibaba Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Alibaba Group Holding has no effect on the direction of DISTRICT METALS i.e., DISTRICT METALS and Alibaba Group go up and down completely randomly.
Pair Corralation between DISTRICT METALS and Alibaba Group
Assuming the 90 days trading horizon DISTRICT METALS is expected to generate 1.54 times more return on investment than Alibaba Group. However, DISTRICT METALS is 1.54 times more volatile than Alibaba Group Holding. It trades about 0.15 of its potential returns per unit of risk. Alibaba Group Holding is currently generating about 0.07 per unit of risk. If you would invest 16.00 in DISTRICT METALS on September 18, 2024 and sell it today you would earn a total of 8.00 from holding DISTRICT METALS or generate 50.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
DISTRICT METALS vs. Alibaba Group Holding
Performance |
Timeline |
DISTRICT METALS |
Alibaba Group Holding |
DISTRICT METALS and Alibaba Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with DISTRICT METALS and Alibaba Group
The main advantage of trading using opposite DISTRICT METALS and Alibaba Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DISTRICT METALS position performs unexpectedly, Alibaba Group 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 Alibaba Group will offset losses from the drop in Alibaba Group's long position.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 |
Alibaba Group vs. Apple Inc | Alibaba Group vs. Apple Inc | Alibaba Group vs. Apple Inc | Alibaba Group vs. Apple Inc |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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