Correlation Between Telecom Argentina and SINGAPORE AIRLINES
Can any of the company-specific risk be diversified away by investing in both Telecom Argentina and SINGAPORE AIRLINES 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 SINGAPORE AIRLINES into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Telecom Argentina SA and SINGAPORE AIRLINES, you can compare the effects of market volatilities on Telecom Argentina and SINGAPORE AIRLINES 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 SINGAPORE AIRLINES. Check out your portfolio center. Please also check ongoing floating volatility patterns of Telecom Argentina and SINGAPORE AIRLINES.
Diversification Opportunities for Telecom Argentina and SINGAPORE AIRLINES
-0.04 | Correlation Coefficient |
Good diversification
The 3 months correlation between Telecom and SINGAPORE is -0.04. Overlapping area represents the amount of risk that can be diversified away by holding Telecom Argentina SA and SINGAPORE AIRLINES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SINGAPORE AIRLINES 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 SA are associated (or correlated) with SINGAPORE AIRLINES. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SINGAPORE AIRLINES has no effect on the direction of Telecom Argentina i.e., Telecom Argentina and SINGAPORE AIRLINES go up and down completely randomly.
Pair Corralation between Telecom Argentina and SINGAPORE AIRLINES
Assuming the 90 days horizon Telecom Argentina SA is expected to under-perform the SINGAPORE AIRLINES. In addition to that, Telecom Argentina is 2.44 times more volatile than SINGAPORE AIRLINES. It trades about -0.05 of its total potential returns per unit of risk. SINGAPORE AIRLINES is currently generating about -0.02 per unit of volatility. If you would invest 457.00 in SINGAPORE AIRLINES on May 8, 2025 and sell it today you would lose (11.00) from holding SINGAPORE AIRLINES or give up 2.41% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Telecom Argentina SA vs. SINGAPORE AIRLINES
Performance |
Timeline |
Telecom Argentina |
SINGAPORE AIRLINES |
Telecom Argentina and SINGAPORE AIRLINES Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Telecom Argentina and SINGAPORE AIRLINES
The main advantage of trading using opposite Telecom Argentina and SINGAPORE AIRLINES positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Telecom Argentina position performs unexpectedly, SINGAPORE AIRLINES 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 SINGAPORE AIRLINES will offset losses from the drop in SINGAPORE AIRLINES's long position.Telecom Argentina vs. CORNISH METALS INC | Telecom Argentina vs. GRIFFIN MINING LTD | Telecom Argentina vs. Metallurgical of | Telecom Argentina vs. FIREWEED METALS P |
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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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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