Correlation Between NEO and MOF

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

Diversification Opportunities for NEO and MOF

0.0
  Correlation Coefficient
 NEO
 MOF

Pay attention - limited upside

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

Pair Corralation between NEO and MOF

If you would invest  1,571  in NEO on January 26, 2024 and sell it today you would earn a total of  235.00  from holding NEO or generate 14.96% return on investment over 90 days.
Time Period3 Months [change]
DirectionFlat 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

NEO  vs.  MOF

 Performance 
       Timeline  
NEO 

Risk-Adjusted Performance

12 of 100

 
Weak
 
Strong
Good
Compared to the overall equity markets, risk-adjusted returns on investments in NEO are ranked lower than 12 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, NEO exhibited solid returns over the last few months and may actually be approaching a breakup point.
MOF 

Risk-Adjusted Performance

0 of 100

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

NEO and MOF Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NEO and MOF

The main advantage of trading using opposite NEO and MOF positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NEO position performs unexpectedly, MOF 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 MOF will offset losses from the drop in MOF's long position.
The idea behind NEO and MOF 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.

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