Correlation Between Loma Negra and Alibaba Group
Can any of the company-specific risk be diversified away by investing in both Loma Negra and Alibaba Group 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 Loma Negra and Alibaba Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Loma Negra Compania and Alibaba Group Holding, you can compare the effects of market volatilities on Loma Negra and Alibaba Group 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 Loma Negra with a short position of Alibaba Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Loma Negra and Alibaba Group.
Diversification Opportunities for Loma Negra and Alibaba Group
-0.8 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Loma and Alibaba is -0.8. Overlapping area represents the amount of risk that can be diversified away by holding Loma Negra Compania and Alibaba Group Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alibaba Group Holding and Loma Negra 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 Loma Negra Compania are associated (or correlated) with Alibaba Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Alibaba Group Holding has no effect on the direction of Loma Negra i.e., Loma Negra and Alibaba Group go up and down completely randomly.
Pair Corralation between Loma Negra and Alibaba Group
Assuming the 90 days trading horizon Loma Negra Compania is expected to under-perform the Alibaba Group. In addition to that, Loma Negra is 1.73 times more volatile than Alibaba Group Holding. It trades about -0.1 of its total potential returns per unit of risk. Alibaba Group Holding is currently generating about 0.14 per unit of volatility. If you would invest 1,077,500 in Alibaba Group Holding on October 20, 2024 and sell it today you would earn a total of 52,500 from holding Alibaba Group Holding or generate 4.87% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Loma Negra Compania vs. Alibaba Group Holding
Performance |
| Timeline |
| Loma Negra Compania |
| Alibaba Group Holding |
Loma Negra and Alibaba Group Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Loma Negra and Alibaba Group
The main advantage of trading using opposite Loma Negra and Alibaba Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Loma Negra position performs unexpectedly, Alibaba Group 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 Alibaba Group will offset losses from the drop in Alibaba Group's long position.| Loma Negra vs. Harmony Gold Mining | Loma Negra vs. Transportadora de Gas | Loma Negra vs. Compania de Transporte | Loma Negra vs. Telecom Argentina |
| Alibaba Group vs. Amazon Inc | Alibaba Group vs. Compania de Transporte | Alibaba Group vs. Banco de Valores | Alibaba Group vs. Mirgor 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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