Correlation Between Telecom Argentina and Dow Jones

Can any of the company-specific risk be diversified away by investing in both Telecom Argentina and Dow Jones 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 Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Telecom Argentina and Dow Jones Industrial, you can compare the effects of market volatilities on Telecom Argentina and Dow Jones 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 Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Telecom Argentina and Dow Jones.

Diversification Opportunities for Telecom Argentina and Dow Jones

-0.11

Correlation Coefficient

Telecom Argentina  Dow Jones

Good diversification

The 3 months correlation between Telecom and Dow is -0.11. Overlapping area represents the amount of risk that can be diversified away by holding Telecom Argentina and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial 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 Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Telecom Argentina i.e., Telecom Argentina and Dow Jones go up and down completely randomly.

Pair Corralation between Telecom Argentina and Dow Jones

Assuming the 90 days trading horizon Telecom Argentina is expected to generate 3.34 times more return on investment than Dow Jones. However, Telecom Argentina is 3.34 times more volatile than Dow Jones Industrial. It trades about 0.07 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.1 per unit of risk. If you would invest  246,500  in Telecom Argentina on May 11, 2025 and sell it today you would earn a total of  22,500  from holding Telecom Argentina or generate 9.13% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Insignificant
Accuracy	100.0%
Values	Daily Returns

Telecom Argentina  vs.  Dow Jones Industrial

Pair Trading with Telecom Argentina and Dow Jones

The main advantage of trading using opposite Telecom Argentina and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Telecom Argentina position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.

The idea behind Telecom Argentina and Dow Jones Industrial pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.