Correlation Between Innodata and SQ Old

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

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

Diversification Opportunities for Innodata and SQ Old

0.0

Correlation Coefficient

Innodata  SQ Old

Pay attention - limited upside

The 3 months correlation between Innodata and SQ Old is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Innodata and SQ Old in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SQ Old and Innodata 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 Innodata are associated (or correlated) with SQ Old. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SQ Old has no effect on the direction of Innodata i.e., Innodata and SQ Old go up and down completely randomly.

Pair Corralation between Innodata and SQ Old

If you would invest  4,209  in Innodata on December 29, 2024 and sell it today you would lose (470.00) from holding Innodata or give up 11.17% of portfolio value over 90 days.

Time Period	3 Months [change]
Direction	Flat
Strength	Insignificant
Accuracy	0.0%
Values	Daily Returns

Innodata  vs.  SQ Old

Innodata

Risk-Adjusted Performance

Very Weak

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

SQ Old

Risk-Adjusted Performance

Very Weak

Over the last 90 days SQ Old has generated negative risk-adjusted returns adding no value to investors with long positions. Even with relatively invariable basic indicators, SQ Old is not utilizing all of its potentials. The latest stock price agitation, may contribute to short-term losses for the retail investors.

Pair Trading with Innodata and SQ Old

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

The idea behind Innodata and SQ Old 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 ETF Categories module to list of ETF categories grouped based on various criteria, such as the investment strategy or type of investments.