Correlation Between NYSE Composite and Hormel Foods

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

Diversification Opportunities for NYSE Composite and Hormel Foods

-0.49
  Correlation Coefficient

Very good diversification

The 3 months correlation between NYSE and Hormel is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Hormel Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hormel Foods and NYSE Composite 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 NYSE Composite are associated (or correlated) with Hormel Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hormel Foods has no effect on the direction of NYSE Composite i.e., NYSE Composite and Hormel Foods go up and down completely randomly.
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Pair Corralation between NYSE Composite and Hormel Foods

Assuming the 90 days trading horizon NYSE Composite is expected to generate 0.54 times more return on investment than Hormel Foods. However, NYSE Composite is 1.84 times less risky than Hormel Foods. It trades about 0.02 of its potential returns per unit of risk. Hormel Foods is currently generating about -0.01 per unit of risk. If you would invest  1,907,793  in NYSE Composite on December 30, 2024 and sell it today you would earn a total of  19,237  from holding NYSE Composite or generate 1.01% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

NYSE Composite  vs.  Hormel Foods

 Performance 
       Timeline  

NYSE Composite and Hormel Foods Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and Hormel Foods

The main advantage of trading using opposite NYSE Composite and Hormel Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Hormel Foods 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 Hormel Foods will offset losses from the drop in Hormel Foods' long position.
The idea behind NYSE Composite and Hormel Foods 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.

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