Correlation Between CARSALES and HAPAG LLOYD
Can any of the company-specific risk be diversified away by investing in both CARSALES and HAPAG LLOYD 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 CARSALES and HAPAG LLOYD into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CARSALESCOM and HAPAG LLOYD UNSPADR 12, you can compare the effects of market volatilities on CARSALES and HAPAG LLOYD 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 CARSALES with a short position of HAPAG LLOYD. Check out your portfolio center. Please also check ongoing floating volatility patterns of CARSALES and HAPAG LLOYD.
Diversification Opportunities for CARSALES and HAPAG LLOYD
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between CARSALES and HAPAG is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding CARSALESCOM and HAPAG LLOYD UNSPADR 12 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on HAPAG LLOYD UNSPADR and CARSALES 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 CARSALESCOM are associated (or correlated) with HAPAG LLOYD. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of HAPAG LLOYD UNSPADR has no effect on the direction of CARSALES i.e., CARSALES and HAPAG LLOYD go up and down completely randomly.
Pair Corralation between CARSALES and HAPAG LLOYD
Assuming the 90 days trading horizon CARSALES is expected to generate 1.46 times less return on investment than HAPAG LLOYD. But when comparing it to its historical volatility, CARSALESCOM is 2.89 times less risky than HAPAG LLOYD. It trades about 0.11 of its potential returns per unit of risk. HAPAG LLOYD UNSPADR 12 is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 5,012 in HAPAG LLOYD UNSPADR 12 on September 4, 2024 and sell it today you would earn a total of 2,388 from holding HAPAG LLOYD UNSPADR 12 or generate 47.65% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
CARSALESCOM vs. HAPAG LLOYD UNSPADR 12
Performance |
| Timeline |
| CARSALESCOM |
| HAPAG LLOYD UNSPADR |
CARSALES and HAPAG LLOYD Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CARSALES and HAPAG LLOYD
The main advantage of trading using opposite CARSALES and HAPAG LLOYD positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CARSALES position performs unexpectedly, HAPAG LLOYD 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 HAPAG LLOYD will offset losses from the drop in HAPAG LLOYD's long position.| CARSALES vs. Mitsui Chemicals | CARSALES vs. USWE SPORTS AB | CARSALES vs. PLAYTIKA HOLDING DL 01 | CARSALES vs. COVIVIO HOTELS INH |
| HAPAG LLOYD vs. Zurich Insurance Group | HAPAG LLOYD vs. Motorcar Parts of | HAPAG LLOYD vs. Commercial Vehicle Group | HAPAG LLOYD vs. CarsalesCom |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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