Correlation Between JD SPORTS and Uber Technologies
Can any of the company-specific risk be diversified away by investing in both JD SPORTS 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 JD SPORTS and Uber Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between JD SPORTS FASH and Uber Technologies, you can compare the effects of market volatilities on JD SPORTS 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 JD SPORTS with a short position of Uber Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of JD SPORTS and Uber Technologies.
Diversification Opportunities for JD SPORTS and Uber Technologies
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between 9JD and Uber is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding JD SPORTS FASH and Uber Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Uber Technologies and JD SPORTS 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 JD SPORTS FASH 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 JD SPORTS i.e., JD SPORTS and Uber Technologies go up and down completely randomly.
Pair Corralation between JD SPORTS and Uber Technologies
Assuming the 90 days horizon JD SPORTS FASH is expected to under-perform the Uber Technologies. In addition to that, JD SPORTS is 1.15 times more volatile than Uber Technologies. It trades about -0.01 of its total potential returns per unit of risk. Uber Technologies is currently generating about 0.07 per unit of volatility. If you would invest 2,776 in Uber Technologies on October 11, 2024 and sell it today you would earn a total of 3,517 from holding Uber Technologies or generate 126.69% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
JD SPORTS FASH vs. Uber Technologies
Performance |
Timeline |
JD SPORTS FASH |
Uber Technologies |
JD SPORTS and Uber Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with JD SPORTS and Uber Technologies
The main advantage of trading using opposite JD SPORTS and Uber Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JD SPORTS 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.JD SPORTS vs. FAIR ISAAC | JD SPORTS vs. Brockhaus Capital Management | JD SPORTS vs. Q2M Managementberatung AG | JD SPORTS vs. SYSTEMAIR AB |
Uber Technologies vs. Semiconductor Manufacturing International | Uber Technologies vs. JD SPORTS FASH | Uber Technologies vs. UNIVERSAL MUSIC GROUP | Uber Technologies vs. ELMOS SEMICONDUCTOR |
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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