Correlation Between Dow Jones and Mfs Emerging

Can any of the company-specific risk be diversified away by investing in both Dow Jones and Mfs Emerging 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 Emerging 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 Emerging Markets, you can compare the effects of market volatilities on Dow Jones and Mfs Emerging 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 Emerging. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Mfs Emerging.

Diversification Opportunities for Dow Jones and Mfs Emerging

-0.15

Correlation Coefficient

Dow Jones  Mfs Emerging

Good diversification

The 3 months correlation between Dow and Mfs is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Mfs Emerging Markets in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Emerging Markets 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 Emerging. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Emerging Markets has no effect on the direction of Dow Jones i.e., Dow Jones and Mfs Emerging go up and down completely randomly.

Pair Corralation between Dow Jones and Mfs Emerging

Assuming the 90 days trading horizon Dow Jones Industrial is expected to under-perform the Mfs Emerging. In addition to that, Dow Jones is 3.51 times more volatile than Mfs Emerging Markets. It trades about -0.01 of its total potential returns per unit of risk. Mfs Emerging Markets is currently generating about 0.15 per unit of volatility. If you would invest  1,179  in Mfs Emerging Markets on December 28, 2024 and sell it today you would earn a total of  26.00  from holding Mfs Emerging Markets or generate 2.21% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Insignificant
Accuracy	100.0%
Values	Daily Returns

Dow Jones Industrial  vs.  Mfs Emerging Markets

Pair Trading with Dow Jones and Mfs Emerging

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

The idea behind Dow Jones Industrial and Mfs Emerging Markets 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.