Correlation Between Mastercard and Alibaba Group
Can any of the company-specific risk be diversified away by investing in both Mastercard 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 Mastercard and Alibaba Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mastercard and Alibaba Group Holdings, you can compare the effects of market volatilities on Mastercard 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 Mastercard with a short position of Alibaba Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mastercard and Alibaba Group.
Diversification Opportunities for Mastercard and Alibaba Group
-0.05 | Correlation Coefficient |
Good diversification
The 3 months correlation between Mastercard and Alibaba is -0.05. Overlapping area represents the amount of risk that can be diversified away by holding Mastercard and Alibaba Group Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alibaba Group Holdings and Mastercard 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 Mastercard 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 Holdings has no effect on the direction of Mastercard i.e., Mastercard and Alibaba Group go up and down completely randomly.
Pair Corralation between Mastercard and Alibaba Group
Assuming the 90 days horizon Mastercard is expected to generate 0.48 times more return on investment than Alibaba Group. However, Mastercard is 2.07 times less risky than Alibaba Group. It trades about 0.07 of its potential returns per unit of risk. Alibaba Group Holdings is currently generating about -0.01 per unit of risk. If you would invest 33,646 in Mastercard on January 30, 2024 and sell it today you would earn a total of 9,379 from holding Mastercard or generate 27.88% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Mastercard vs. Alibaba Group Holdings
Performance |
Timeline |
Mastercard |
Alibaba Group Holdings |
Mastercard and Alibaba Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mastercard and Alibaba Group
The main advantage of trading using opposite Mastercard and Alibaba Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mastercard 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.Mastercard vs. Visa Inc | Mastercard vs. PayPal Holdings | Mastercard vs. Capital One Financial | Mastercard vs. Discover Financial Services |
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 ETFs module to find actively traded Exchange Traded Funds (ETF) from around the world.
Other Complementary Tools
Portfolio Suggestion Get suggestions outside of your existing asset allocation including your own model portfolios | |
Analyst Advice Analyst recommendations and target price estimates broken down by several categories | |
Odds Of Bankruptcy Get analysis of equity chance of financial distress in the next 2 years | |
Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum | |
Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk | |
Portfolio Optimization Compute new portfolio that will generate highest expected return given your specified tolerance for risk |