Correlation Between Hong Kong and Uber Technologies
Can any of the company-specific risk be diversified away by investing in both Hong Kong and Uber Technologies 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 Hong Kong and Uber Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hong Kong Land and Uber Technologies, you can compare the effects of market volatilities on Hong Kong and Uber Technologies 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 Hong Kong with a short position of Uber Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hong Kong and Uber Technologies.
Diversification Opportunities for Hong Kong and Uber Technologies
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Hong and Uber is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Hong Kong Land and Uber Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Uber Technologies and Hong Kong 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 Hong Kong Land are associated (or correlated) with Uber Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Uber Technologies has no effect on the direction of Hong Kong i.e., Hong Kong and Uber Technologies go up and down completely randomly.
Pair Corralation between Hong Kong and Uber Technologies
Assuming the 90 days trading horizon Hong Kong is expected to generate 5.45 times less return on investment than Uber Technologies. But when comparing it to its historical volatility, Hong Kong Land is 10.02 times less risky than Uber Technologies. It trades about 0.09 of its potential returns per unit of risk. Uber Technologies is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 6,920 in Uber Technologies on September 3, 2024 and sell it today you would earn a total of 295.00 from holding Uber Technologies or generate 4.26% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Flat |
| Strength | Insignificant |
| Accuracy | 99.22% |
| Values | Daily Returns |
Hong Kong Land vs. Uber Technologies
Performance |
| Timeline |
| Hong Kong Land |
| Uber Technologies |
Hong Kong and Uber Technologies Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hong Kong and Uber Technologies
The main advantage of trading using opposite Hong Kong and Uber Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hong Kong position performs unexpectedly, Uber Technologies 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 Uber Technologies will offset losses from the drop in Uber Technologies' long position.| Hong Kong vs. Neometals | Hong Kong vs. McEwen Mining | Hong Kong vs. CompuGroup Medical AG | Hong Kong vs. Wheaton Precious Metals |
| Uber Technologies vs. Samsung Electronics Co | Uber Technologies vs. Samsung Electronics Co | Uber Technologies vs. Hyundai Motor | Uber Technologies vs. Toyota Motor Corp |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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