Correlation Between Telecom Argentina and San Miguel
Can any of the company-specific risk be diversified away by investing in both Telecom Argentina and San Miguel 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 Telecom Argentina and San Miguel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Telecom Argentina and San Miguel AG, you can compare the effects of market volatilities on Telecom Argentina and San Miguel 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 Telecom Argentina with a short position of San Miguel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Telecom Argentina and San Miguel.
Diversification Opportunities for Telecom Argentina and San Miguel
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Telecom and San is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding Telecom Argentina and San Miguel AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on San Miguel AG and Telecom Argentina 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 Telecom Argentina are associated (or correlated) with San Miguel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of San Miguel AG has no effect on the direction of Telecom Argentina i.e., Telecom Argentina and San Miguel go up and down completely randomly.
Pair Corralation between Telecom Argentina and San Miguel
Assuming the 90 days trading horizon Telecom Argentina is expected to generate 3.19 times less return on investment than San Miguel. In addition to that, Telecom Argentina is 1.03 times more volatile than San Miguel AG. It trades about 0.15 of its total potential returns per unit of risk. San Miguel AG is currently generating about 0.49 per unit of volatility. If you would invest 98,800 in San Miguel AG on September 12, 2024 and sell it today you would earn a total of 41,700 from holding San Miguel AG or generate 42.21% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Telecom Argentina vs. San Miguel AG
Performance |
| Timeline |
| Telecom Argentina |
| San Miguel AG |
Telecom Argentina and San Miguel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Telecom Argentina and San Miguel
The main advantage of trading using opposite Telecom Argentina and San Miguel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Telecom Argentina position performs unexpectedly, San Miguel 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 San Miguel will offset losses from the drop in San Miguel's long position.| Telecom Argentina vs. Grupo Televisa SAB | Telecom Argentina vs. Cablevision Holding SA | Telecom Argentina vs. Edesa Holding SA | Telecom Argentina vs. Vista Energy, SAB |
| San Miguel vs. Molinos Agro SA | San Miguel vs. Ledesma SAAI | San Miguel vs. Edesa Holding SA | San Miguel vs. Vista Energy, SAB |
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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