Correlation Between Grupo SBF and Lojas Quero
Can any of the company-specific risk be diversified away by investing in both Grupo SBF and Lojas Quero 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 Grupo SBF and Lojas Quero into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Grupo SBF SA and Lojas Quero Quero SA, you can compare the effects of market volatilities on Grupo SBF and Lojas Quero 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 Grupo SBF with a short position of Lojas Quero. Check out your portfolio center. Please also check ongoing floating volatility patterns of Grupo SBF and Lojas Quero.
Diversification Opportunities for Grupo SBF and Lojas Quero
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Grupo and Lojas is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding Grupo SBF SA and Lojas Quero Quero SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lojas Quero Quero and Grupo SBF 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 Grupo SBF SA are associated (or correlated) with Lojas Quero. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lojas Quero Quero has no effect on the direction of Grupo SBF i.e., Grupo SBF and Lojas Quero go up and down completely randomly.
Pair Corralation between Grupo SBF and Lojas Quero
Assuming the 90 days trading horizon Grupo SBF is expected to generate 2.55 times less return on investment than Lojas Quero. But when comparing it to its historical volatility, Grupo SBF SA is 1.24 times less risky than Lojas Quero. It trades about 0.07 of its potential returns per unit of risk. Lojas Quero Quero SA is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 216.00 in Lojas Quero Quero SA on December 30, 2024 and sell it today you would earn a total of 79.00 from holding Lojas Quero Quero SA or generate 36.57% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Grupo SBF SA vs. Lojas Quero Quero SA
Performance |
Timeline |
Grupo SBF SA |
Lojas Quero Quero |
Grupo SBF and Lojas Quero Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Grupo SBF and Lojas Quero
The main advantage of trading using opposite Grupo SBF and Lojas Quero positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Grupo SBF position performs unexpectedly, Lojas Quero 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 Lojas Quero will offset losses from the drop in Lojas Quero's long position.Grupo SBF vs. Lojas Quero Quero SA | Grupo SBF vs. Pet Center Comrcio | Grupo SBF vs. Eneva SA | Grupo SBF vs. Mliuz SA |
Lojas Quero vs. Pet Center Comrcio | Lojas Quero vs. Mitre Realty Empreendimentos | Lojas Quero vs. Mliuz SA | Lojas Quero vs. Direcional Engenharia SA |
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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