Correlation Between ITC and DATA

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

By analyzing existing cross correlation between ITC and DATA, you can compare the effects of market volatilities on ITC and DATA 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 ITC with a short position of DATA. Check out your portfolio center. Please also check ongoing floating volatility patterns of ITC and DATA.

Diversification Opportunities for ITC and DATA

0.04

Correlation Coefficient

ITC  DATA

Significant diversification

The 3 months correlation between ITC and DATA is 0.04. Overlapping area represents the amount of risk that can be diversified away by holding ITC and DATA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DATA and ITC 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 ITC are associated (or correlated) with DATA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DATA has no effect on the direction of ITC i.e., ITC and DATA go up and down completely randomly.

Pair Corralation between ITC and DATA

If you would invest  3.81  in DATA on September 1, 2024 and sell it today you would earn a total of  1.17  from holding DATA or generate 30.71% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	1.54%
Values	Daily Returns

ITC  vs.  DATA

ITC

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days ITC has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound fundamental indicators, ITC is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.

DATA

Risk-Adjusted Performance

8 of 100

Modest

Compared to the overall equity markets, risk-adjusted returns on investments in DATA are ranked lower than 8 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, DATA exhibited solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with ITC and DATA

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

The idea behind ITC and DATA 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.

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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.