Correlation Between Macquarie Bank and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Macquarie Bank and Dow Jones 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 Macquarie Bank and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Macquarie Bank Limited and Dow Jones Industrial, you can compare the effects of market volatilities on Macquarie Bank and Dow Jones 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 Macquarie Bank with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Macquarie Bank and Dow Jones.
Diversification Opportunities for Macquarie Bank and Dow Jones
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Macquarie and Dow is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Macquarie Bank Limited and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and Macquarie Bank 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 Macquarie Bank Limited are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Macquarie Bank i.e., Macquarie Bank and Dow Jones go up and down completely randomly.
Pair Corralation between Macquarie Bank and Dow Jones
Assuming the 90 days trading horizon Macquarie Bank is expected to generate 3.4 times less return on investment than Dow Jones. But when comparing it to its historical volatility, Macquarie Bank Limited is 1.56 times less risky than Dow Jones. It trades about 0.09 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.2 of returns per unit of risk over similar time horizon. If you would invest 4,093,693 in Dow Jones Industrial on September 3, 2024 and sell it today you would earn a total of 397,372 from holding Dow Jones Industrial or generate 9.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.46% |
Values | Daily Returns |
Macquarie Bank Limited vs. Dow Jones Industrial
Performance |
Timeline |
Macquarie Bank and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Macquarie Bank Limited
Pair trading matchups for Macquarie Bank
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Macquarie Bank and Dow Jones
The main advantage of trading using opposite Macquarie Bank and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Macquarie Bank position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.Macquarie Bank vs. NEWMONT PORATION CDI | Macquarie Bank vs. Ora Banda Mining | Macquarie Bank vs. Polymetals Resources | Macquarie Bank vs. Champion Iron |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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