Correlation Between Uber Technologies and Tencent Holdings
Can any of the company-specific risk be diversified away by investing in both Uber Technologies and Tencent Holdings 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 Uber Technologies and Tencent Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Uber Technologies and Tencent Holdings Ltd, you can compare the effects of market volatilities on Uber Technologies and Tencent Holdings 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 Uber Technologies with a short position of Tencent Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Uber Technologies and Tencent Holdings.
Diversification Opportunities for Uber Technologies and Tencent Holdings
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Uber and Tencent is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding Uber Technologies and Tencent Holdings Ltd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tencent Holdings and Uber Technologies 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 Uber Technologies are associated (or correlated) with Tencent Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tencent Holdings has no effect on the direction of Uber Technologies i.e., Uber Technologies and Tencent Holdings go up and down completely randomly.
Pair Corralation between Uber Technologies and Tencent Holdings
Assuming the 90 days trading horizon Uber Technologies is expected to generate 1.07 times more return on investment than Tencent Holdings. However, Uber Technologies is 1.07 times more volatile than Tencent Holdings Ltd. It trades about 0.08 of its potential returns per unit of risk. Tencent Holdings Ltd is currently generating about 0.03 per unit of risk. If you would invest 2,696 in Uber Technologies on October 9, 2024 and sell it today you would earn a total of 3,714 from holding Uber Technologies or generate 137.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 99.8% |
Values | Daily Returns |
Uber Technologies vs. Tencent Holdings Ltd
Performance |
Timeline |
Uber Technologies |
Tencent Holdings |
Uber Technologies and Tencent Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Uber Technologies and Tencent Holdings
The main advantage of trading using opposite Uber Technologies and Tencent Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Uber Technologies position performs unexpectedly, Tencent Holdings 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 Tencent Holdings will offset losses from the drop in Tencent Holdings' long position.Uber Technologies vs. Molina Healthcare | Uber Technologies vs. HEALTHSTREAM | Uber Technologies vs. Planet Fitness | Uber Technologies vs. RCI Hospitality Holdings |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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