Correlation Between Ivy Apollo and American Funds
Can any of the company-specific risk be diversified away by investing in both Ivy Apollo and American Funds 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 Ivy Apollo and American Funds into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ivy Apollo Multi Asset and American Funds Income, you can compare the effects of market volatilities on Ivy Apollo and American Funds 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 Ivy Apollo with a short position of American Funds. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ivy Apollo and American Funds.
Diversification Opportunities for Ivy Apollo and American Funds
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Ivy and American is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Ivy Apollo Multi Asset and American Funds Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on American Funds Income and Ivy Apollo 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 Ivy Apollo Multi Asset are associated (or correlated) with American Funds. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of American Funds Income has no effect on the direction of Ivy Apollo i.e., Ivy Apollo and American Funds go up and down completely randomly.
Pair Corralation between Ivy Apollo and American Funds
Assuming the 90 days horizon Ivy Apollo Multi Asset is expected to generate 0.69 times more return on investment than American Funds. However, Ivy Apollo Multi Asset is 1.45 times less risky than American Funds. It trades about -0.37 of its potential returns per unit of risk. American Funds Income is currently generating about -0.26 per unit of risk. If you would invest 963.00 in Ivy Apollo Multi Asset on October 12, 2024 and sell it today you would lose (37.00) from holding Ivy Apollo Multi Asset or give up 3.84% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Ivy Apollo Multi Asset vs. American Funds Income
Performance |
Timeline |
Ivy Apollo Multi |
American Funds Income |
Ivy Apollo and American Funds Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ivy Apollo and American Funds
The main advantage of trading using opposite Ivy Apollo and American Funds positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ivy Apollo position performs unexpectedly, American Funds 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 American Funds will offset losses from the drop in American Funds' long position.Ivy Apollo vs. Ivy International E | Ivy Apollo vs. Ivy E Equity | Ivy Apollo vs. Ivy E Equity | Ivy Apollo vs. Ivy Large Cap |
American Funds vs. Ivy Large Cap | American Funds vs. Ivy Small Cap | American Funds vs. Ivy High Income | American Funds vs. Ivy Apollo Multi Asset |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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