Correlation Between GM and Track Data

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Can any of the company-specific risk be diversified away by investing in both GM and Track 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 GM and Track Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Track Data, you can compare the effects of market volatilities on GM and Track 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 GM with a short position of Track Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Track Data.

Diversification Opportunities for GM and Track Data

0.41
  Correlation Coefficient

Very weak diversification

The 3 months correlation between GM and Track is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Track Data in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Track Data and GM 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 General Motors are associated (or correlated) with Track Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Track Data has no effect on the direction of GM i.e., GM and Track Data go up and down completely randomly.

Pair Corralation between GM and Track Data

If you would invest  4,484  in General Motors on August 31, 2024 and sell it today you would earn a total of  1,066  from holding General Motors or generate 23.77% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy2.27%
ValuesDaily Returns

General Motors  vs.  Track Data

 Performance 
       Timeline  
General Motors 

Risk-Adjusted Performance

7 of 100

 
Weak
 
Strong
OK
Compared to the overall equity markets, risk-adjusted returns on investments in General Motors are ranked lower than 7 (%) of all global equities and portfolios over the last 90 days. In spite of very weak primary indicators, GM displayed solid returns over the last few months and may actually be approaching a breakup point.
Track Data 

Risk-Adjusted Performance

0 of 100

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

GM and Track Data Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with GM and Track Data

The main advantage of trading using opposite GM and Track Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Track 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 Track Data will offset losses from the drop in Track Data's long position.
The idea behind General Motors and Track 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.
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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 Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.

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