Correlation Between Macquarie Technology and Australia
Can any of the company-specific risk be diversified away by investing in both Macquarie Technology and Australia 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 Technology and Australia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Macquarie Technology Group and Australia and New, you can compare the effects of market volatilities on Macquarie Technology and Australia 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 Technology with a short position of Australia. Check out your portfolio center. Please also check ongoing floating volatility patterns of Macquarie Technology and Australia.
Diversification Opportunities for Macquarie Technology and Australia
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Macquarie and Australia is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Macquarie Technology Group and Australia and New in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Australia and New and Macquarie Technology 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 Technology Group are associated (or correlated) with Australia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Australia and New has no effect on the direction of Macquarie Technology i.e., Macquarie Technology and Australia go up and down completely randomly.
Pair Corralation between Macquarie Technology and Australia
Assuming the 90 days trading horizon Macquarie Technology Group is expected to generate 1.04 times more return on investment than Australia. However, Macquarie Technology is 1.04 times more volatile than Australia and New. It trades about -0.03 of its potential returns per unit of risk. Australia and New is currently generating about -0.11 per unit of risk. If you would invest 9,015 in Macquarie Technology Group on October 11, 2024 and sell it today you would lose (175.00) from holding Macquarie Technology Group or give up 1.94% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Macquarie Technology Group vs. Australia and New
Performance |
Timeline |
Macquarie Technology |
Australia and New |
Macquarie Technology and Australia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Macquarie Technology and Australia
The main advantage of trading using opposite Macquarie Technology and Australia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Macquarie Technology position performs unexpectedly, Australia 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 Australia will offset losses from the drop in Australia's long position.Macquarie Technology vs. WiseTech Global Limited | Macquarie Technology vs. Collins Foods | Macquarie Technology vs. TPG Telecom | Macquarie Technology vs. Beston Global Food |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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