Correlation Between Ivy Apollo and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Ivy Apollo 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 Ivy Apollo and Dow Jones 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 Dow Jones Industrial, you can compare the effects of market volatilities on Ivy Apollo 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 Ivy Apollo with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ivy Apollo and Dow Jones.
Diversification Opportunities for Ivy Apollo and Dow Jones
-0.25 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Ivy and Dow is -0.25. Overlapping area represents the amount of risk that can be diversified away by holding Ivy Apollo Multi Asset 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 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 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 Ivy Apollo i.e., Ivy Apollo and Dow Jones go up and down completely randomly.
Pair Corralation between Ivy Apollo and Dow Jones
Assuming the 90 days horizon Ivy Apollo Multi Asset is expected to under-perform the Dow Jones. But the mutual fund apears to be less risky and, when comparing its historical volatility, Ivy Apollo Multi Asset is 1.96 times less risky than Dow Jones. The mutual fund trades about -0.01 of its potential returns per unit of risk. The Dow Jones Industrial is currently generating about 0.27 of returns per unit of risk over similar time horizon. If you would invest 4,223,305 in Dow Jones Industrial on August 30, 2024 and sell it today you would earn a total of 248,901 from holding Dow Jones Industrial or generate 5.89% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Ivy Apollo Multi Asset vs. Dow Jones Industrial
Performance |
Timeline |
Ivy Apollo and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Ivy Apollo Multi Asset
Pair trading matchups for Ivy Apollo
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Ivy Apollo and Dow Jones
The main advantage of trading using opposite Ivy Apollo and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ivy Apollo 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.Ivy Apollo vs. American Century High | Ivy Apollo vs. Gmo High Yield | Ivy Apollo vs. Ppm High Yield | Ivy Apollo vs. Msift High Yield |
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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 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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