Correlation Between Dow Jones and Mercuries Data

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

Diversification Opportunities for Dow Jones and Mercuries Data

0.05

Correlation Coefficient

Dow Jones  Mercuries Data

Significant diversification

The 3 months correlation between Dow and Mercuries is 0.05. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Mercuries Data Systems in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mercuries Data Systems 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 Mercuries Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mercuries Data Systems has no effect on the direction of Dow Jones i.e., Dow Jones and Mercuries Data go up and down completely randomly.

Pair Corralation between Dow Jones and Mercuries Data

Assuming the 90 days trading horizon Dow Jones Industrial is expected to under-perform the Mercuries Data. But the index apears to be less risky and, when comparing its historical volatility, Dow Jones Industrial is 2.53 times less risky than Mercuries Data. The index trades about -0.04 of its potential returns per unit of risk. The Mercuries Data Systems is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest  2,620  in Mercuries Data Systems on December 28, 2024 and sell it today you would earn a total of  125.00  from holding Mercuries Data Systems or generate 4.77% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	91.8%
Values	Daily Returns

Dow Jones Industrial  vs.  Mercuries Data Systems

Pair Trading with Dow Jones and Mercuries Data

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

The idea behind Dow Jones Industrial and Mercuries Data Systems 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 Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.