Correlation Between Dow Jones and Mfs Low

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

Diversification Opportunities for Dow Jones and Mfs Low

0.91
  Correlation Coefficient

Almost no diversification

The 3 months correlation between Dow and Mfs is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Mfs Low Volatility in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Low Volatility and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with Mfs Low. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Low Volatility has no effect on the direction of Dow Jones i.e., Dow Jones and Mfs Low go up and down completely randomly.
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Pair Corralation between Dow Jones and Mfs Low

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 1.27 times more return on investment than Mfs Low. However, Dow Jones is 1.27 times more volatile than Mfs Low Volatility. It trades about 0.1 of its potential returns per unit of risk. Mfs Low Volatility is currently generating about 0.11 per unit of risk. If you would invest  3,898,983  in Dow Jones Industrial on August 29, 2024 and sell it today you would earn a total of  573,223  from holding Dow Jones Industrial or generate 14.7% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Strong
Accuracy100.0%
ValuesDaily Returns

Dow Jones Industrial  vs.  Mfs Low Volatility

 Performance 
       Timeline  

Dow Jones and Mfs Low Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Dow Jones and Mfs Low

The main advantage of trading using opposite Dow Jones and Mfs Low positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Mfs Low 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 Mfs Low will offset losses from the drop in Mfs Low's long position.
The idea behind Dow Jones Industrial and Mfs Low Volatility 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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.

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