Correlation Between Dow Jones and Meta Data

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

Diversification Opportunities for Dow Jones and Meta Data

0.16

Correlation Coefficient

Dow Jones  Meta Data

Average diversification

The 3 months correlation between Dow and Meta is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Meta Data in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Meta Data 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 Meta Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Meta Data has no effect on the direction of Dow Jones i.e., Dow Jones and Meta Data go up and down completely randomly.

Pair Corralation between Dow Jones and Meta Data

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.08 times more return on investment than Meta Data. However, Dow Jones Industrial is 12.08 times less risky than Meta Data. It trades about 0.07 of its potential returns per unit of risk. Meta Data is currently generating about -0.06 per unit of risk. If you would invest  3,313,637  in Dow Jones Industrial on September 21, 2024 and sell it today you would earn a total of  920,587  from holding Dow Jones Industrial or generate 27.78% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	82.42%
Values	Daily Returns

Dow Jones Industrial  vs.  Meta Data

Pair Trading with Dow Jones and Meta Data

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

The idea behind Dow Jones Industrial and Meta 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.

Check out your portfolio center.

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 Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.