Correlation Between Berkeley Group and ZALANDO SE
Can any of the company-specific risk be diversified away by investing in both Berkeley Group and ZALANDO SE 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 Berkeley Group and ZALANDO SE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Berkeley Group Holdings and ZALANDO SE ADR, you can compare the effects of market volatilities on Berkeley Group and ZALANDO SE 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 Berkeley Group with a short position of ZALANDO SE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Berkeley Group and ZALANDO SE.
Diversification Opportunities for Berkeley Group and ZALANDO SE
-0.33 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Berkeley and ZALANDO is -0.33. Overlapping area represents the amount of risk that can be diversified away by holding Berkeley Group Holdings and ZALANDO SE ADR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ZALANDO SE ADR and Berkeley Group 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 Berkeley Group Holdings are associated (or correlated) with ZALANDO SE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ZALANDO SE ADR has no effect on the direction of Berkeley Group i.e., Berkeley Group and ZALANDO SE go up and down completely randomly.
Pair Corralation between Berkeley Group and ZALANDO SE
Assuming the 90 days horizon Berkeley Group Holdings is expected to under-perform the ZALANDO SE. But the pink sheet apears to be less risky and, when comparing its historical volatility, Berkeley Group Holdings is 1.58 times less risky than ZALANDO SE. The pink sheet trades about -0.19 of its potential returns per unit of risk. The ZALANDO SE ADR is currently generating about 0.27 of returns per unit of risk over similar time horizon. If you would invest 1,183 in ZALANDO SE ADR on September 12, 2024 and sell it today you would earn a total of 624.00 from holding ZALANDO SE ADR or generate 52.75% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Berkeley Group Holdings vs. ZALANDO SE ADR
Performance |
Timeline |
Berkeley Group Holdings |
ZALANDO SE ADR |
Berkeley Group and ZALANDO SE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Berkeley Group and ZALANDO SE
The main advantage of trading using opposite Berkeley Group and ZALANDO SE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Berkeley Group position performs unexpectedly, ZALANDO SE 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 ZALANDO SE will offset losses from the drop in ZALANDO SE's long position.Berkeley Group vs. Barratt Developments PLC | Berkeley Group vs. Persimmon Plc | Berkeley Group vs. Britvic PLC ADR | Berkeley Group vs. Proximus NV ADR |
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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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