Correlation Between New America and Macquariefirst
Can any of the company-specific risk be diversified away by investing in both New America and Macquariefirst 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 New America and Macquariefirst into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between New America High and Macquariefirst Tr Global, you can compare the effects of market volatilities on New America and Macquariefirst 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 New America with a short position of Macquariefirst. Check out your portfolio center. Please also check ongoing floating volatility patterns of New America and Macquariefirst.
Diversification Opportunities for New America and Macquariefirst
0.12 | Correlation Coefficient |
Average diversification
The 3 months correlation between New and Macquariefirst is 0.12. Overlapping area represents the amount of risk that can be diversified away by holding New America High and Macquariefirst Tr Global in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Macquariefirst Tr Global and New America 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 New America High are associated (or correlated) with Macquariefirst. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Macquariefirst Tr Global has no effect on the direction of New America i.e., New America and Macquariefirst go up and down completely randomly.
Pair Corralation between New America and Macquariefirst
Considering the 90-day investment horizon New America High is expected to generate 0.78 times more return on investment than Macquariefirst. However, New America High is 1.29 times less risky than Macquariefirst. It trades about 0.09 of its potential returns per unit of risk. Macquariefirst Tr Global is currently generating about 0.04 per unit of risk. If you would invest 605.00 in New America High on September 3, 2024 and sell it today you would earn a total of 225.00 from holding New America High or generate 37.19% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 90.1% |
| Values | Daily Returns |
New America High vs. Macquariefirst Tr Global
Performance |
| Timeline |
| New America High |
| Macquariefirst Tr Global |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Weak
New America and Macquariefirst Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with New America and Macquariefirst
The main advantage of trading using opposite New America and Macquariefirst positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if New America position performs unexpectedly, Macquariefirst 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 Macquariefirst will offset losses from the drop in Macquariefirst's long position.| New America vs. Pioneer Municipal High | New America vs. DWS Municipal Income | New America vs. RiverNorth Specialty Finance | New America vs. Putnam Managed Municipal |
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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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