Correlation Between Dow Jones and Bank of Queensland

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

Diversification Opportunities for Dow Jones and Bank of Queensland

0.34

Correlation Coefficient

Dow Jones  Bank of Queensland

Weak diversification

The 3 months correlation between Dow and Bank is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Bank of Queensland in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank of Queensland 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 Bank of Queensland. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank of Queensland has no effect on the direction of Dow Jones i.e., Dow Jones and Bank of Queensland go up and down completely randomly.

Pair Corralation between Dow Jones and Bank of Queensland

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 2.79 times more return on investment than Bank of Queensland. However, Dow Jones is 2.79 times more volatile than Bank of Queensland. It trades about 0.04 of its potential returns per unit of risk. Bank of Queensland is currently generating about 0.08 per unit of risk. If you would invest  4,212,465  in Dow Jones Industrial on September 21, 2024 and sell it today you would earn a total of  71,561  from holding Dow Jones Industrial or generate 1.7% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Very Weak
Accuracy	98.46%
Values	Daily Returns

Dow Jones Industrial  vs.  Bank of Queensland

Pair Trading with Dow Jones and Bank of Queensland

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

The idea behind Dow Jones Industrial and Bank of Queensland 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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.