Correlation Between Dow Jones and Beowulf Mining

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

Diversification Opportunities for Dow Jones and Beowulf Mining

-0.86

Correlation Coefficient

Dow Jones  Beowulf Mining

Pay attention - limited upside

The 3 months correlation between Dow and Beowulf is -0.86. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Beowulf Mining PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Beowulf Mining PLC 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 Beowulf Mining. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Beowulf Mining PLC has no effect on the direction of Dow Jones i.e., Dow Jones and Beowulf Mining go up and down completely randomly.

Pair Corralation between Dow Jones and Beowulf Mining

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.22 times more return on investment than Beowulf Mining. However, Dow Jones Industrial is 4.6 times less risky than Beowulf Mining. It trades about 0.16 of its potential returns per unit of risk. Beowulf Mining PLC is currently generating about -0.28 per unit of risk. If you would invest  4,109,677  in Dow Jones Industrial on September 12, 2024 and sell it today you would earn a total of  315,106  from holding Dow Jones Industrial or generate 7.67% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Significant
Accuracy	98.44%
Values	Daily Returns

Dow Jones Industrial  vs.  Beowulf Mining PLC

Pair Trading with Dow Jones and Beowulf Mining

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

The idea behind Dow Jones Industrial and Beowulf Mining PLC 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.