Correlation Between JD SPORTS and ENTREPARTICULIERS
Can any of the company-specific risk be diversified away by investing in both JD SPORTS and ENTREPARTICULIERS 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 ENTREPARTICULIERS 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 ENTREPARTICULIERS EO 10, you can compare the effects of market volatilities on JD SPORTS and ENTREPARTICULIERS 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 ENTREPARTICULIERS. Check out your portfolio center. Please also check ongoing floating volatility patterns of JD SPORTS and ENTREPARTICULIERS.
Diversification Opportunities for JD SPORTS and ENTREPARTICULIERS
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between 9JD and ENTREPARTICULIERS is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding JD SPORTS FASH and ENTREPARTICULIERS EO 10 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ENTREPARTICULIERS EO 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 ENTREPARTICULIERS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ENTREPARTICULIERS EO has no effect on the direction of JD SPORTS i.e., JD SPORTS and ENTREPARTICULIERS go up and down completely randomly.
Pair Corralation between JD SPORTS and ENTREPARTICULIERS
Assuming the 90 days horizon JD SPORTS FASH is expected to generate 1.35 times more return on investment than ENTREPARTICULIERS. However, JD SPORTS is 1.35 times more volatile than ENTREPARTICULIERS EO 10. It trades about -0.14 of its potential returns per unit of risk. ENTREPARTICULIERS EO 10 is currently generating about -0.32 per unit of risk. If you would invest 143.00 in JD SPORTS FASH on September 12, 2024 and sell it today you would lose (19.00) from holding JD SPORTS FASH or give up 13.29% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 95.65% |
| Values | Daily Returns |
JD SPORTS FASH vs. ENTREPARTICULIERS EO 10
Performance |
| Timeline |
| JD SPORTS FASH |
| ENTREPARTICULIERS EO |
JD SPORTS and ENTREPARTICULIERS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with JD SPORTS and ENTREPARTICULIERS
The main advantage of trading using opposite JD SPORTS and ENTREPARTICULIERS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JD SPORTS position performs unexpectedly, ENTREPARTICULIERS 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 ENTREPARTICULIERS will offset losses from the drop in ENTREPARTICULIERS's long position.| JD SPORTS vs. FAST RETAIL ADR | JD SPORTS vs. CCC SA | JD SPORTS vs. AOYAMA TRADING | JD SPORTS vs. Superior Plus Corp |
| ENTREPARTICULIERS vs. Air New Zealand | ENTREPARTICULIERS vs. LAir Liquide SA | ENTREPARTICULIERS vs. Corsair Gaming | ENTREPARTICULIERS vs. Japan Post Insurance |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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