Correlation Between Petroleo Brasileiro and Adidas AG
Can any of the company-specific risk be diversified away by investing in both Petroleo Brasileiro and Adidas AG 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 Petroleo Brasileiro and Adidas AG into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Petroleo Brasileiro Petrobras and adidas AG, you can compare the effects of market volatilities on Petroleo Brasileiro and Adidas AG 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 Petroleo Brasileiro with a short position of Adidas AG. Check out your portfolio center. Please also check ongoing floating volatility patterns of Petroleo Brasileiro and Adidas AG.
Diversification Opportunities for Petroleo Brasileiro and Adidas AG
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Petroleo and Adidas is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Petroleo Brasileiro Petrobras and adidas AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on adidas AG and Petroleo Brasileiro 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 Petroleo Brasileiro Petrobras are associated (or correlated) with Adidas AG. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of adidas AG has no effect on the direction of Petroleo Brasileiro i.e., Petroleo Brasileiro and Adidas AG go up and down completely randomly.
Pair Corralation between Petroleo Brasileiro and Adidas AG
Considering the 90-day investment horizon Petroleo Brasileiro Petrobras is expected to under-perform the Adidas AG. But the stock apears to be less risky and, when comparing its historical volatility, Petroleo Brasileiro Petrobras is 1.06 times less risky than Adidas AG. The stock trades about -0.01 of its potential returns per unit of risk. The adidas AG is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 23,680 in adidas AG on October 14, 2024 and sell it today you would earn a total of 700.00 from holding adidas AG or generate 2.96% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 98.39% |
Values | Daily Returns |
Petroleo Brasileiro Petrobras vs. adidas AG
Performance |
Timeline |
Petroleo Brasileiro |
adidas AG |
Petroleo Brasileiro and Adidas AG Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Petroleo Brasileiro and Adidas AG
The main advantage of trading using opposite Petroleo Brasileiro and Adidas AG positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Petroleo Brasileiro position performs unexpectedly, Adidas AG 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 Adidas AG will offset losses from the drop in Adidas AG's long position.Petroleo Brasileiro vs. Ecopetrol SA ADR | Petroleo Brasileiro vs. Equinor ASA ADR | Petroleo Brasileiro vs. Eni SpA ADR | Petroleo Brasileiro vs. Cenovus Energy |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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