Correlation Between Sixt Leasing and Vicinity Centres
Can any of the company-specific risk be diversified away by investing in both Sixt Leasing and Vicinity Centres 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 Sixt Leasing and Vicinity Centres into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sixt Leasing SE and Vicinity Centres, you can compare the effects of market volatilities on Sixt Leasing and Vicinity Centres 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 Sixt Leasing with a short position of Vicinity Centres. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sixt Leasing and Vicinity Centres.
Diversification Opportunities for Sixt Leasing and Vicinity Centres
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Sixt and Vicinity is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Sixt Leasing SE and Vicinity Centres in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Vicinity Centres and Sixt Leasing 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 Sixt Leasing SE are associated (or correlated) with Vicinity Centres. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Vicinity Centres has no effect on the direction of Sixt Leasing i.e., Sixt Leasing and Vicinity Centres go up and down completely randomly.
Pair Corralation between Sixt Leasing and Vicinity Centres
Assuming the 90 days trading horizon Sixt Leasing SE is expected to under-perform the Vicinity Centres. In addition to that, Sixt Leasing is 1.0 times more volatile than Vicinity Centres. It trades about -0.06 of its total potential returns per unit of risk. Vicinity Centres is currently generating about 0.06 per unit of volatility. If you would invest 106.00 in Vicinity Centres on October 12, 2024 and sell it today you would earn a total of 17.00 from holding Vicinity Centres or generate 16.04% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Sixt Leasing SE vs. Vicinity Centres
Performance |
Timeline |
Sixt Leasing SE |
Vicinity Centres |
Sixt Leasing and Vicinity Centres Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sixt Leasing and Vicinity Centres
The main advantage of trading using opposite Sixt Leasing and Vicinity Centres positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sixt Leasing position performs unexpectedly, Vicinity Centres 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 Vicinity Centres will offset losses from the drop in Vicinity Centres' long position.Sixt Leasing vs. SYSTEMAIR AB | Sixt Leasing vs. Entravision Communications | Sixt Leasing vs. FORWARD AIR P | Sixt Leasing vs. Cogent Communications Holdings |
Vicinity Centres vs. SENECA FOODS A | Vicinity Centres vs. Sixt Leasing SE | Vicinity Centres vs. Lifeway Foods | Vicinity Centres vs. ALBIS LEASING AG |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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